EY Reinvents Its People Advisory Services, Leaning on a Single Methodology to Drive Successful Change

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In late April, TBR visited with EY’s People Advisory Services (PAS) team at the firm’s Boston office. Rapid changes in the HR role, along with the need to effectively manage the workforce amid ongoing transformation and increased technology adoption, have driven greater investment in the function and a need to effectively manage the changes. The discussion centered on how these external drivers led to changes in EY’s services. First was a thorough review of the global EY Change Experience (ChX) method, which is an updated, data-driven change management approach that focuses on achieving business outcomes through behavior change. Second was a preview of EY’s CHRO (chief human resources officer) 2030 study, which was published in early June and emphasizes the need for talent readiness and business focus.

Transformation within EY’s PAS

Starting off the discussion, Randy Beck, EY’s Global Organization and People leader, spoke at length about the major market priorities and activities that have been the focus in 2025 to provide leading methodologies and thought leadership to their clients. EY’s PAS guides client workforce strategies, impacting people experience, organization and workforce transformation, HR transformation, rewards and people transactions, and people mobility.

 

A key area of emphasis was updating the change management service offering to align with market needs. This year, EY implemented a single global, modernized change management methodology, moving away from the over 33 different methodologies previously used across PAS engagements. This unified methodology distinguishes EY from its competitors, enhances global consistency, improves the employee experience, and ensures that clients’ transformations through PAS are more successful and enduring. The methodology seeks to create a data-driven, proactive rather than reactive approach to change, enabling clients to prepare and adjust to the transformation turning points. As part of the launch and to support consistency, EY retrained 2,600 employees in the practice across 60-plus countries using e-learning to recertify its staff. This mandatory training ensures EY’s practitioners will follow the same methodology moving forward.

 

In structuring the methodology, EY sought to embrace modularity and scalability, enabling the company to meet clients at their current maturity point and prepare them for future changes. EY consultants collaborate with clients as change management solution architects to design suitable project approaches, utilizing appropriate tools and technologies to address their requirements.

 

EY sets itself apart from its peers through the methodology, backing its transformation with data and technology and addressing the people side of organizational change. In the methodology, EY calls out Meaning, Empowerment and Growth as the change conditions, or guiding principles, which are applied at the individual, team and organization levels throughout a project to make change stick. Each project approach is also centered on delivering change components under the four change pillars: leadership, engagement, confidence and proficiency.

 

To align with the company’s overall vision and better guide change, EY ensures that members of clients’ leadership teams are in position to guide the transformation. Throughout the engagement, EY provides resources and training for clients, enabling them to support and uphold their transformations. Fostering confidence using data, metrics and established governance exemplifies the need for change and encourages support across the organization. Lastly, the need for skilled individuals to lead and uphold change highlights the importance of ongoing skills development, underscoring the pillar of proficiency.

 

EY shared six additional practices that differentiate the company in the market. One key feature that practice EY leaders demonstrated to TBR was the Network Analysis tool, which plays a critical role in driving effective organizational change. The tool maps trusted networks within the organization and identifies influential leaders, enabling them to champion change and help ensure it takes hold.

 

The development of the Modernization Change Experience methodology reflects EY’s PAS practicewide commitment to a more modular, proactive and people-centric approach to change. Using the platform, EY seeks to better guide change for its clients and establish “change as a muscle,” enabling the company to be proactive and a part of clients’ normal operations. While acknowledging that change is necessary, EY also recognizes that change can be personal, highlighting the importance of change as an experience that fully engages client talent to make the transformation more successful. Further, the platform drives the value of outcomes, reflecting an industrywide shift toward outcomes-based engagements and risk-sharing on projects.

Conclusion

As workforce and employee experience grow increasingly critical in the era of rapid technological advancement, EY’s refreshed approach within PAS — centered on a unified methodology and a stronger focus on people experience — helps distinguish the firm from its peers and better aligns with technology-driven transformation initiatives. Further, taking a global approach to retraining and methodology creates a more unified approach within the firm to better engage with clients and navigate market change.

 

EY has structured its portfolio to meet clients where they are in their transformation journey, delivering solutions that empower them to embrace change and lead their own initiatives effectively. Integrating experience and continuous change into people advisory and workforce transformation strengthens EY’s competitive edge while enabling clients to sustain long-term progress, anchored by technology.

AI Inferencing Takes Center Stage at Red Hat Summit 2025

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In late May, Red Hat welcomed thousands of developers, IT decision makers and partners to its annual Red Hat Summit at the Boston Convention and Exhibition Center (BCEC). Like the rest of the market, Red Hat has pivoted around AI inferencing, and this conference marked the company’s entry into the market with the productization of vLLM, the open-source project that has been shaping AI model execution over the past two years. Though Red Hat’s push into AI inferencing does not necessarily suggest a deemphasis on model alignment use cases (e.g., fine-tuning, distillation), which was the company’s big strategic focus last year, it is a recognition that AI inferencing is a production environment and that the process of running models to generate responses is where the business value lies. Red Hat’s ability to embed open-source innovation within its products and lower the cost per model token presents a sizable opportunity. Interestingly, Red Hat’s prospects are also evolving in more traditional markets. For instance, Red Hat’s virtualization customer base has tripled over the past year, with virtualization emerging as a strategic driver throughout the company’s broader business, including for communication service providers (CSPs) adopting virtualized RAN and within other domains such as their IT stacks and the mobile core.

Red Hat pivots around AI inferencing

Rooted in Linux, the basis of OpenShift, Red Hat has always had a unique ability to resolution assets to expand into new markets and use cases. Of course, AI is the most relevant example, and two years ago, Red Hat formally entered the market with Red Hat Enterprise Linux (RHEL) AI — the tool Red Hat uses to engage AI developers — and OpenShift AI, for model lifecycle management and MLOps (machine learning operations) at scale. These assets have made up the Red Hat AI platform, but at the Red Hat Summit, the company introduced a third component with AI Inference Server, in addition to new partnerships and integrations further designed to make agentic AI and inferencing realities within the enterprise.

 

AI and generative AI (GenAI) are rapidly evolving, but the associated core challenges and adoption barriers, including the high cost of AI models and the sometimes arduous nature of providing business context, remain largely unchanged. Between IBM’s small language models (SLMs) and Red Hat’s focus on reducing alignment complexity, both companies have crafted a strategy focused on addressing these challenges; they aim not to develop the next big AI algorithm, but rather to serve tangible enterprise use cases in both the cloud and the data center.

 

Everyone is aware of Red Hat’s track record of delivering enterprise-grade open-source innovation, and if Red Hat’s disruption with Linux over two decades ago is any indication, the company is well positioned to make real, cost-effective solutions for the enterprise based on reasoning models and AI inferencing.

Red Hat productizes vLLM to mark entry into AI inferencing

Though perhaps lesser known, most large language models (LLMs) today are leveraging vLLM, an upstream open-source project boasting roughly half a million downloads in any given week. At its core, vLLM is an inference server that helps address “inference-time scaling,” or the budding notion that the longer the model runs or “thinks,” the better the result will be. Of course, the challenge with this approach is the cost of running the model for a longer period of time, but vLLM’s single-server architecture is designed to optimize GPU utilization, ultimately reducing the cost per token of the AI model. Various industry leaders — namely NVIDIA, despite having its own AI model serving stack; Google; and Neural Magic, which Red Hat acquired earlier this year — are leading contributors to the project.

 

Leveraging its rich history of turning open-source projects into enterprise products, Red Hat launched AI Inference Server, based on vLLM, marking Red Hat’s first offering from the Neural Magic acquisition. AI Inference Server is included with both RHEL AI and OpenShift AI but can also run as its own stand-alone server. Though perhaps inclined to emphasize IBM’s watsonx models, Red Hat is extending its values of flexibility, choice and meeting customers where they are to AI Inference Server. This new offering supports accelerators outside IBM, including NVIDIA, AMD, Intel, Amazon Web Services (AWS) and Google Cloud, and offers Day 0 support for a range of LLMs. This means that as soon as a new model is released, Red Hat works with the provider to optimize the model for vLLM and validate it on Red Hat’s platform.

 

Building on vLLM’s early success, Red Hat launched LLM-d, a new open-source project, announced at the Red Hat Summit. LLM-d transcends vLLM’s single-server architecture, allowing inference to run in a distributed manner, further reducing the cost per token. Due to the cost, most will agree that inferencing will necessitate distributed infrastructure, and there are several recent examples across the tech landscape that have alluded to this. LLM-d is being launched with support from many of vLLM’s same contributors, including NVIDIA and Google (LLM-d runs on both GPUs and TPUs [tensor processing units]).

Partnership with Meta around MCP is all about empowering developers and making agentic AI enterprise-ready

If Google’s launch of A2A (Agent2Agent) protocol is any indication, Anthropic’s Model Context Protocol (MCP), which aims to standardize how LLMs discern context, is gaining traction. At the Red Hat Summit, Red Hat committed to MCP by announcing it will deliver Meta’s Llama Stack, integrated with MCP, in OpenShift AI and RHEL AI.

 

To be clear, Red Hat supports a range of models, but Meta went the open-source route early on, bringing Llama Stack, an open-source framework for building specifically on Llama models, into the Red Hat environment. This not only exposes Red Hat to another ecosystem but also provides APIs around it. Enlisting Meta at the API layer is an important aspect of this solution, as it enables customers to consume the solution and build new agentic applications with MCP playing a key role in contextualizing those applications within the AI enterprise. It is still early days for MCP, and making the protocol truly relevant in enterprise use cases will take some time and advancement in security and governance. But Red Hat indirectly supporting MCP within its products signals the framework’s potential and Red Hat’s role in bringing it to the enterprise.

Who would have thought we would be discussing virtualization in 2025?

In 2025 and the world of AI, you don’t often hear of a company putting virtualization at the top of its strategic imperatives list. However, everyone has seen how Broadcom’s takeover of VMware has caused a ripple in the market, with customers seeking cheaper, more flexible alternatives that will not disrupt their current cloud transformation journeys. In fact, when we surveyed enterprise IT decision makers, 42% of respondents indicated they still intend to use VMware, but most plan to do so in a reduced capacity. Of those planning to continue using VMware, a notable 83% are still evaluating other options*.

 

“Options both have increased the prices across the board, 20% to 30%, which is pretty significant. So, you could say myself and my peers are not very happy with the Broadcom method on that, and we’re looking at, you know, definitely options to migrate off VMware when possible. We’re definitely looking at Citrix, and then options from Red Hat and Microsoft.” — CTO Portfolio Manager, Consumer Packaged Goods

 

As a reminder, after Red Hat revolutionized Linux in the early 2000s, the company’s next big endeavor was virtualization. With the rise of cloud-native architectures, Red Hat quickly pivoted around containers, and this is where the company remains most relevant today. However, through the KVM (kernel-based virtual machine) hypervisor, which would eventually be integrated with OpenShift, virtualization has always been a part of the portfolio. Over the past year, given the opportunity surrounding the VMware customer base, Red Hat has actively revisited its virtualization roots in a few primary ways.

 

First, given the risky nature of switching virtualization platforms, Red Hat crafted a portfolio of high-touch services around OpenShift Virtualization, including Migration Factory and a fixed-price offering called Virtualization Migration Assessment. These services from Red Hat Consulting, which are offered in close alignment with global systems integrator (GSI) partners, help customers migrate virtual machines (VMs) as quickly as possible while minimizing risk, which largely stems from helping customers migrate VMs before modernizing them.

 

Secondly, Red Hat has focused on increasing public cloud support. Red Hat announced at the summit that OpenShift Virtualization is now available on Microsoft Azure, Google Cloud and Oracle Cloud Infrastructure (OCI), in addition to previously announced support for IBM Cloud and AWS, officially making the platform available on all major public clouds. Making OpenShift Virtualization applicable across the entire cloud ecosystem reinforces how serious Red Hat is about capturing these virtualization opportunities. These integrations will make it easier for customers to use their existing cloud spend commitments to offload VMware workloads to any cloud of their choice while maintaining the same cloud-native experience they are used to.

 

Of course, there will always be a level of overlap between Red Hat and the hyperscalers, but ultimately the hyperscalers recognize Red Hat’s role in addressing the hybrid reality and enterprises’ need to move workloads consistently across clouds and within data centers, and they welcome a more feature-rich platform like OpenShift that will spin the meter on their infrastructure.

With virtualization, Red Hat is allowing partners to sell infrastructure modernization and AI as part of the same story

At the conference, we heard from established Red Hat customers that have extended their Linux and container investments to virtualization. Examples included Ford and Emirates NBD, which has over 37,000 containers in production and is now migrating 9,000 VMs to Red Hat OpenShift Virtualization for a more consistent tech stack. Based on our conversations with customers, these scenarios — where VMs and containers run side by side — are not an easy sell and require a level of buy-in across the organization.

 

That said, if customers can overcome some of these change management hurdles, this side-by-side approach can offer numerous benefits, largely by creating greater consistency between legacy and cloud-native applications without significant refactoring. Though some GSIs may be better suited to the infrastructure layer than others, partners should recognize the opportunity to use OpenShift Virtualization to have client discussions around broader AI transformations. One of the compelling aspects of Red Hat is that even as it progressed through different phases — Linux, virtualization, containers and now AI — the hybrid platform foundation has remained unchanged. If customers can modernize their infrastructure on the same platform, introducing AI models via OpenShift AI becomes much more compelling.

Virtualization remains a key driver of telecom operator uptake of Red Hat solutions, but AI presents a significant upsell opportunity

Over the past few years, Red Hat has leveraged its virtualization technology in the CSP market, making significant progress in landing new CSP accounts and expanding its account share within this unique vertical. The company’s growth in this market has been aided by factors such as Broadcom’s acquisition of VMware, which initially caused a wave of CSPs to migrate to Red Hat due to the uncertainty surrounding VMware’s portfolio road map. Broadcom’s price hikes are causing a second wave of switching that TBR anticipates will continue for several years.

 

However, Red Hat has also succeeded in more deeply penetrating the telecom vertical due to its savvy marketing, which at times emphasizes that its solutions are “carrier-grade,” along with persistent efforts to raise awareness within the CIO and CTO organizations of CSPs that virtualization and hybrid multicloud strategies will have significant ROI for CSPs. This has led to strong adoption of Red Hat OpenStack and OpenShift, although the Ansible automation platform has lagged in terms of CSP adoption, as this customer segment prefers to use the free, open-source version of Ansible.

 

As CSPs iterate on their AI strategies, Red Hat has the opportunity to play a significant role, including with its new Red Hat Inference Server, as CSPs increasingly embrace edge compute investments. CSPs need to invest upfront to capitalize on the cost efficiency and revenue generation opportunities offered by AI, and Red Hat can help guide them in this direction. CSPs have difficulty moving quickly when new, disruptive technologies emerge, and, with AI specifically, have trouble evaluating and testing AI models themselves due to a lack of in-house expertise. Additionally, they feel constrained by regulations and are concerned about compromising data privacy. Red Hat’s dedicated telecom vertical services can help alleviate these concerns and accelerate CSPs’ investments in AI infrastructure.

Final thoughts

Based on our best estimate, roughly 85% of AI’s current use is focused on training and only 15% on inferencing, but the inverse could be true in the not-too-distant future. Not only that, but AI inferencing will likely occur at distributed locations for the purposes of latency and scale — which, due to its hybrid platform and ability to help customers “write once, deploy anywhere,” remains core to Red Hat’s value proposition. That is one of the compelling aspects of a platform-first approach; even as new components such as AI models are introduced, the core foundation remains unchanged.

 

Though all of Red Hat’s new innovations, including AI Inference Server and the LLM-d project, do not necessarily suggest a deemphasis on model alignment with assets like InstructLab, it is clear Red Hat is pivoting to address the inference opportunity. With its trusted experience productizing open-source innovation and its ability to exist within a broad technology ecosystem of hyperscalers, OEMs and chip providers, Red Hat is in a somewhat unique position to help transition AI inference from an ideal to an enterprise reality.

 

Further, Red Hat’s virtualization prospects are growing, as TBR’s interactions with customers continue to indicate that they are looking for new alternatives. If the hyperscalers’ recent earnings reports are any indication, the GenAI hype is waning, and we suspect many enterprises will refocus on infrastructure modernization to ultimately move beyond basic chatbots and lay the groundwork for the more strategic applications that inferencing will enable. It will be interesting to see how Red Hat capitalizes on new virtualization opportunities with its hyperscaler and services partners as part of a joint effort to bring customers to a modern platform, where VMs and containers can coexist and drive discussions around AI.

 

*From TBR’s 2H25 IT Infrastructure Customer Research

A Challenger Mindset Transforms HCLTech’s Approach to Financial Services to Achieve Success Through AI

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HCLTech hosted industry analysts and advisers on May 13 at the ASPIRE at One World Observatory in New York City. Throughout the afternoon, HCLTech executives, leaders and clients spoke at length about the company’s financial services positioning, direction and activities amid disruption from AI and digital acceleration.

Introduction

During the event, HCLTech leaders consistently highlighted how the company’s culture, deep engineering expertise and unique approach to AI set it apart from its peers and strengthen client relationships. These points were echoed by two financial services clients during a panel discussion. Differentiation remains a challenge for all vendors, yet HCLTech emphasized that although the company may not be different in what it does, it is unique in its approach.

Balancing risk, innovation and talent investment

The event began with a presentation by HCLTech CEO and Managing Director C Vijayakumar (CVK), who gave an overview of the company’s current positioning and future plans. The session centered on HCLTech’s evolution toward an engineering and platform-based mindset and its transformation from a traditional model that no longer remains relevant amid a changing balance between revenue and talent volumes. To adapt its business model and better align itself with the needs of clients and the market, CVK announced HCLTech’s goal of doubling its revenue with only half of its previous headcount.

 

As roles within the organization have begun to change with the integration of new technology, including AI, HCLTech has had to begin transforming the company’s structure. Revenue per employee has always been a KPI for HCLTech to ensure the company decouples revenue growth from headcount growth. HCLTech’s attention to the metric is reflected in its ability to maintain peer-leading levels relative to Cognizant, Infosys, Tata Consultancy Services (TCS) and Wipro IT Services (ITS), whose trailing 12-month (TTM) revenue per employee was $59,304, $60,338, 49,692 and 45,270, respectively, in 1Q25 — each below HCLTech’s figure of $62,360.

 

It is a lofty goal to deliver the same quality of service at the same speed with fewer people, even with the support of AI tools and strong partnerships. To achieve this goal, HCLTech will rely on its culture and talent, combined with its strategic technology investments including AI, digital and software solutions. CVK emphasized that HCLTech’s culture is deeply embedded in the company’s DNA, making it difficult for competitors to replicate. This culture fosters strong client trust and deepens relationships, as it consistently comes through in conversations with clients. By building on this foundation, HCLTech effectively leverages AI technologies to strengthen existing partnerships and secure new projects.

 

HCLTech’s client management and retention strategy reflects the company’s ability to embed itself within the client environment and serve as a key partner. HCLTech’s deep relationships have enabled the company to better identify and address client challenges as well as opportunities to recommend transformations to clients. As complexity increases across the technology landscape, HCLTech has had to evolve its approach to both new and existing clients. Client willingness to adopt AI tools can be tempered by concerns over managing multiple platforms and the associated risks.

 

As a result, HCLTech often takes a more measured and gradual approach with new clients, focusing on building trust and easing them into transformation. In contrast, with existing clients, HCLTech adopts a more assertive strategy — leveraging its deep understanding of their technology landscapes and industry-specific needs to drive adoption and deliver results more rapidly.

 

CVK closed his presentation by emphasizing the need to be proactive and carry a “paranoid mindset” to stay ahead of technology trends and remain relevant. HCLTech’s ability to build strong relationships with clients enables the company to guide transformations, equipping clients with the tools and services to be proactive and effectively leverage technology across their organizations. With a greater focus on outcomes, HCLTech’s positioning and relationships with clients provide a foundation for the company to grow its wallet share with clients as it balances risks with innovation and invests for future growth.

Demand for modernization and AI influences client needs within the financial services space

Srinivasan (Srini) Seshadri, HCLTech’s chief growth officer and Financial Services lead, discussed the company’s 50,000-person Financial Services practice, which as HCLTech’s largest industry group generated $2.9 billion in revenue during FY25. During the presentation, Seshadri emphasized five main features of the company’s Financial Services practice that help it drive value for clients: engineering DNA, outcome orientation, challenger mindset, verticalized services and innovation. The benefit of verticalized services stood out to TBR. A few years ago, HCLTech moved all its service lines under one vertical, creating a unified go-to-market strategy, enabling it to deepen its client relationships and positioning around transformation. As vertical and industry expertise does not provide differentiation on its own, HCLTech took it a step further, pairing its industry experience with service lines to better communicate its portfolio and drive value. Taking this approach pulls together HCLTech’s strengths and drives outcomes.

 

Key items influencing HCLTech’s Financial Services activities include adapting to changing regulations, increasing use of Global Capability Centers, and creating and implementing composable products. Aligning its portfolio and resources to help clients navigate current trends and operate more effectively guides HCLTech’s client approach.

 

For example, with the permeation of generative AI (GenAI) and increased adoption of the technology by clients seeking to remain relevant, Seshadri spoke about the evolution of GenAI from a buzzword to actual engagement and usage, including using GenAI to reimagine an autonomous future for Financial Services. HCLTech seeks to integrate GenAI solutions and tools within its clients’ operations, depending on maturity level and understanding, to drive end-to-end value chain transformation.

 

Helping clients use AI to make internal processes better and more efficient and to achieve their goals enhances HCLTech’s value proposition in the financial services industry and enables the company to gain new projects in sensitive areas such as regulation, governance and security.

Prioritizing the main areas within engineering, platform modernization and GenAI aligns HCLTech’s financial services expertise with its key service line strengths around business optimization, design and innovation and enables the company to support client transformations. Seshadri closed his presentation by acknowledging that transformation “is up to the client to implement.” HCLTech’s approach to deal generation is shaped by its deep understanding of culture and clients’ readiness to sustain transformation. By viewing AI as a means to enhance processes and operations — and by factoring in the longevity of each client relationship — HCLTech tailors the pace and intensity of technology integration. This ability to meet clients where they are and ensure lasting transformation distinguishes HCLTech from its peers.

Experience is key to client engagement

Building on Srini’s discussion, Ananth Subramanya, HCLTech’s EVP of Digital Business Services, talked about the industrywide shift in consumer loyalty from a physical product to the experience, with the experience driving the engagement. As clients increasingly demand rapid, relevant transformations that drive business outcomes, Subramanya emphasized the importance of balancing speed with stability — acknowledging that while stability may at times constrain velocity, it is essential for sustainable progress. The strategy helps users build resilience, enabling the customer experience (CX) to permeate the product and platform layers to ensure it influences each aspect of the client transformation.

 

HCLTech’s CX-centric delivery approach — anchored in both business processes and user interface (UI) design — deeply embeds the experience within clients’ operations and functions. This foundation empowers clients to engage more effectively and drive meaningful change. Additionally, by enabling end users to experience improvements more rapidly, the approach fosters stronger client loyalty and supports the development of long-term, strategic projects.

AI permeates approach to transformation

Diving more deeply into the impact of AI on financial services activities and client investments, Vijay Guntur, HCLTech’s CTO and head of Ecosystems, discussed the primary needs within financial operations: operational efficiency, accelerated innovation, CX and risk management. Key challenges around data quality and collection, the use of legacy system, and scalability also remain critical within the financial services space. HCLTech’s investments across AI platforms and solutions have enabled the company to deliver on these needs while embedding industry knowledge to address key client concerns. The company’s four main AI and GenAI offerings are AI Force, AI Foundry, AI Labs and AI/GenAI Engineering. Through these offerings, HCLTech helps clients execute on decision making and handle complex workflows.

 

Using its AI Labs, with six different locations in the U.S., the U.K., Germany, India and Singapore, HCLTech can build and scale AI for clients, helping them work through early stages and identify where they can add value through the use of technology. The labs encapsulate HCLTech’s AI portfolio offerings and create opportunities for the implementation of tools and solutions with the goal of driving value. As clients undergo transformation and modernization services, lowering risk while increasing AI efficiency across IT operations, the labs showcase HCLTech’s portfolio offerings and solutions, helping clients lead AI transformations.

 

The primary AI offering, AI Force, launched in March 2024, takes a platform approach to apply AI technologies within software development and engineering life cycle processes. Further development of the platform has enabled interoperability and greater adoption and AI usage. Guntur emphasized that the platform improves efficiency and shortens time to market, allowing clients to more quickly respond to market needs and remain relevant against peers. With agentic AI emerging as a much-needed use of the technology, AI Force’s ability to embed agentic workflows enhances efficiency and adds value.

 

The second product, AI Foundry, accelerates product development and remodels the value stream using AI and data. With a focus on value streams, modernizing data, and AI that is built within a cognitive infrastructure, AI Foundry uses technology to help clients improve their business operations.

 

HCLTech has a long history working with AI, building off its DRYiCE platform, the company’s original automation platform. This heritage equips HCLTech with the background and trusted technical expertise, backed by its engineering prowess. to deliver on clients’ AI transformation needs. Further, HCLTech can pursue larger-scale and more aggressive AI-led transformations, helping the company accelerate ahead of its peers in terms of client engagement and growth.

Consulting serves as an entry point to broader financial services activities

In a panel discussion with financial services clients, HCLTech leaders discussed the company’s consulting services and main service line areas. Although consulting has not been a primary investment focus for HCLTech, the company has selectively built out consulting capabilities to address clients’ end-to-end modernization and technology needs. For example, in March 2019, HCLTech acquired Strong-Bridge Envision, a digital consulting firm that complemented its digital and analytics capabilities. Embedding this expertise across its portfolio strengthens the company’s ability to drive AI and platform adoption.

 

The company’s AI Labs are a central part of HCLTech’s consulting offerings. Through the labs, HCLTech delivers technology consulting services, helping clients to identify areas where they would most benefit from AI. As many clients, particularly within the financial services space, look to accelerate innovation to create new products and business models that enable them to remain relevant, technology consulting services bring in essential offerings to help address key areas of client transformations.

 

Looking at the data aspect, consulting is required for many clients to organize and manage datasets. Ensuring data is protected and structured remains vital to valuable and trusted AI usage, increasing the importance of HCLTech’s ability to deliver on data needs in a timely manner.

While these consulting investments may offer limited scale, they are sufficient to remain competitive with peers and to guide clients effectively on AI adoption. This expertise aligns well with the company’s client management strategy, particularly in expanding relationships with existing clients — where HCLTech can lead with a proactive and open-minded approach.

Conclusion

HCLTech concluded the event with a wrap-up by CMO Jill Kouri, who noted key points about HCLTech’s positioning and direction as the company navigates client needs around AI. The main comment that struck TBR analysts referenced the need for a challenger mindset companywide. This approach will help HCLTech transform the way it delivers services and solutions to clients. Leading with a proactive and paranoid mindset embodies the challenger focus, allowing HCLTech to stay ahead of AI and technology trends while complementing its existing strengths.

 

The goal of doubling revenue with half the people will certainly present challenges for HCLTech, but the company’s culture and robust AI portfolio, which provides the technology, engineering expertise and resources needed to deliver on consulting services, will help the company move in the right direction. Further, leveraging an AI-intrinsic point of view, as opposed to an AI-first point of view, secures HCLTech’s positioning around AI and its trust-based relationships with clients, to effectively address key market needs around efficiency and modernization.

Sage Analyst Summit: Keeping the Winning Playbook While Evaluating Emerging Changes to the Game

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Connect, grow, deliver

TBR spent two days in Atlanta, listening to and speaking with Sage’s management team as part of the company’s annual Analyst Summit, and we walked away impressed. This is a company that knows itself and its strengths. It knows where it needs to improve. It knows where the pain points and constraints are, and has always done a good job of navigating between the two.

 

Most importantly, the company knows its customers, which should come as no surprise considering how long Sage has been serving its SMB install base. Sage has leveraged these strengths and established a large, sticky install base from which to pursue opportunities adjacent to its core business.

 

Sage is focused on three interlocking areas — connect, grow, deliver — which President Dan Miller described during the event:

  • Connect through trusted partner networks
  • Grow by winning new logos through a verticalized suite motion
  • Deliver real, measurable productivity using AI

Each pillar represents a separate part of the company’s go-to-market strategy, but Grow stands out as the most vital to the company’s growth trajectory. Landing and expanding with new logos is the company’s greatest source of revenue growth, with vertical-specific and business operations solutions offering some of the greatest upsell potential. Aligned with this strategy, the company is a disciplined but active acquirer, onboarding new IP to enhance these sales motions.

 

Long-term, AI presents opportunities for the company to upsell into its finance and accounting (F&A) core. As Sage leans into its strengths while building for the future, its ability to scale AI and industry depth across a known and trusted customer base may prove to be the company’s most valuable asset.

Landing with F&A, then expanding with payroll, HR and operations management

Sage’s land-and-expand strategy starts with a stronghold in finance and builds outward through operational adjacencies. Most customers enter through core accounting —typically via Intacct — and expand into areas like payroll, HR, and inventory or distribution management as their needs mature. Vertical-specific modules are critical to this motion, especially in midmarket industries where Sage can tailor functionality to operational nuances.

 

The company reinforces expansion by packaging these capabilities into suites, streamlining procurement and positioning itself as more than just a financial system. Sales teams are trained to identify expansion triggers early; signs like API adoption, workflow customization or manual process bottlenecks often indicate opportunities. Although the company’s product maturity varies across the portfolio, Sage has seen success in service- and product-centric verticals, enabling the company to upsell and cross-sell. This approach, combined with a focus on ease of integration and strong partner involvement, is helping Sage grow account value without overpromising in its product road map.

AI at Sage: Workflow-first, ROI-driven

Sage management spent much time discussing its ambitions in AI. From TBR’s perspective, the tone was very grounded. Although the company will never be at the cutting edge of AI innovation, management did a great job of articulating the current opportunities to upsell AI capabilities. Finance and accounting workflows offer many sales opportunities for Sage to pursue, and the company is investing in R&D to capitalize on them. Similar to many of its application peers, Sage intends to approach agentic AI and generative AI development on a use-case-by-use-case basis. In Sage’s case, this is even more prudent as SMB customers face greater budgetary restrictions and require ROI to be realized in the first year.

 

Sage management highlighted AP automation, time-saving prompts and variance analysis as key areas where the company is achieving success with AI-powered automation. Like several peers, the company’s Copilot solution serves as the unified user interface (UI) for engaging embedded AI tools. Long-term, management expects to see this UI become more adaptive, guiding the user through an automated workflow. Guided prompting was another area of focus, and the company is building a library of prompts for end users to leverage as they perform specific tasks. Under the hood, the company intends to run its AI tools on internally trained models built on top of a third-party. CTO Aaron Harris discussed two of these tools: Sage Accounting LLM and APDoc2Vec.

 

As a reminder, Sage partnered with Amazon Web Services (AWS) over a year ago to collaborate on F&A models, and management highlighted the continued effort to build a new multitenant, dependency-based stack.

 

Long-term, TBR expects this work to be pivotal in reducing the cost of running AI workloads, while internally developed models with lower parameter counts than big-name large language models (LLMs) will further enhance cost efficiency at inference. Meanwhile, Sage is still figuring out how to monetize AI, but the industry default is to implement a tiered system. Some high-compute copilots may eventually carry usage-based fees, especially in forecasting, but for now, the priority is to show clear value and price accordingly.

 

In 2025 no conversation is complete without recognizing the platform implications of agentic workflows. Behind the scenes, Sage is preparing for an agent-first architecture by integrating emerging frameworks, such as Model Context Protocol (MCP) or Agent 2 Agent (A2A), directly into its platforms. The long-term goal is to coordinate these through super agents and plug into the broader agent ecosystem (Salesforce, Microsoft, Google), but this is still only part of the long-term road map.

 

That said, the company is building for the future, with an emphasis on data model consistency, dependency-based deployment, and orchestration layers capable of managing multi-agent chains. This is all being done with AWS in the background, keeping the platform anchored at the infrastructure layer.

Sage deepens its partner relationships

Sage’s partner and go-to-market strategy is built for focus and leverage. The company cannot cover every vertical or service need on its own, so partners are central to how it sells, delivers and scales. The revamped Sage Partner Network is tighter, with clear roles across sell, build and serve motions, and expectations tied to growth, not just activity. Multiyear vertical plans, coinvestment and execution discipline are now baseline requirements.

 

Internally, the GTM engine runs through SIGMA, which ties product planning to what the direct and partner channels sell. Sales teams are trained to package suites, identify expansion triggers, and position the platform by vertical need, rather than a feature checklist. To prepare for the platform’s evolution, Sage is already laying the groundwork for a more extensible ecosystem, including plans for an agent marketplace that would give partners a direct path into the next wave of product delivery.

Staying the course and preparing for what lies ahead

Sage’s story at its annual Analyst Summit was not necessarily one of reinvention. Land and expand has been the company’s strategy for years, and it has worked well so far. By anchoring in finance, expanding through vertical suites and operation management, and keeping partners close to the motion, Sage is executing with clarity around who it serves and how it wins. Meanwhile, the platform is evolving, AI is taking shape, and the architecture is catching up to the ambition. None of the company’s claims felt like overpromising.

 

In a market filled with transformation stories, Sage is running a disciplined play. The question is whether it can maintain that discipline as it scales and converts its product investments, especially in AI and agentic workflows, into tangible value for the customers it already knows best.

SAP Sapphire 2025: Legacy Application Leader Moving Confidently Into a Data and AI Future

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Staking a claim in a best-of-suite future

At SAP Sapphire 2025, one thing became immediately clear: SAP is no longer chasing the cloud market — it is positioning itself to define it. While best-of-breed has long been the enterprise default, a growing segment of the market is leaning toward consolidation: fewer vendors, tighter integration, faster outcomes. SAP sees an opening. With its dominance as a system of record and a broad portfolio spanning platforms and line-of-business (LOB) suites, the company believes it is uniquely equipped to serve these best-of-suite buyers and made a compelling case at Sapphire that it is actively working to turn this vision into reality.

 

SAP’s messaging has focused heavily on customers already operating in the cloud, shifting attention away from the sizable portion of its base still tethered to ECC (ERP Central Component). The forward-looking emphasis may be warranted. Although cloud migrations remain a strategic priority, they have been at the center of SAP’s story for the better part of a decade. While the customer mix still skews toward legacy deployments, TBR estimates that cloud revenue accounts for more than 60% of SAP’s total corporate revenue, presenting a solid base from which to expand contract sizes.

 

In addition to migration efforts, the company has built out a suite of integration, robotic process automation and data assets — many with high attach rates — that are driving much of its commercial cloud momentum. While TBR believes SAP will continue steadily transitioning legacy customers to the cloud, its land-and-expand strategy among new logos (born-in-the-cloud, midmarket) and existing customers leaning into modernization will provide ample growth opportunities to build on top of migration-related gains. For this reason, TBR believes SAP was justified in prioritizing its platform-centric cloud strategy at Sapphire 2025. The company has built a compelling cloud business, and that road map deserves to be in the spotlight.

Building an agentic flywheel

SAP’s central metaphor this year — the “flywheel” — describes a loop in which enterprise applications feed business data into a semantic layer, which powers AI agents that act on the data and push outcomes back into the apps. Put simply: if you own the context, you control the outcome. SAP believes its depth of structured business data gives it a defensible advantage in the race toward agentic AI. Fragmented stacks, the company argues, are the Achilles’ heel of enterprise automation. SAP promises to reduce the cost and complexity of AI adoption by delivering deeply integrated, outcome-oriented capabilities across its entire suite of products.

The state of Joule as a UI for the AI era

SAP wants 2025 to be the year agents move from prototype to production. Joule remains the user interface (UI), but it is now positioned as an orchestration layer, not just a chatbot. The company showcased use cases ranging from accounts receivable prioritization to automated financial close and proactive risk flagging. These scenarios emphasized traceability. For example, each step is visible to the end user, and each recommendation is auditable. That transparency, enabled by LeanIX, signals SAP’s commitment to building enterprise-grade controls around automation.

 

Today, most of these agents are operating in relatively structured environments. Financial workflows, inventory management and procurement tasks offer well-bounded problems. The leap to agents that navigate fuzzier terrain — customer onboarding, scenario planning or partner collaboration — has not happened yet. Agentic systems will continue to be built on a use-case-by-use-case basis, which takes time. SAP is developing more tasks and, at the event, showed a demo of Joule working through a tariff shock scenario. It featured each member of a fictional C-Suite reacting in real time using embedded AI: the CFO reallocating capital, the chief revenue officer rerouting demand, the COO managing supply constraints, and the chief human resources officer rebalancing skills.

 

In TBR’s opinion, the demo felt like an oversimplification of a complex issue, but we were still impressed by the information an agent could gather and the actions it was able to execute. Obviously, agentic AI stands to be highly disruptive to SaaS workflows, and TBR believes SAP is playing the game well. Long-term, the breadth of the company’s ERP and LOB portfolios offers a massive amount of whitespace for innovation, enabling the company to continue attacking the opportunity on a use-case-by-use-case basis as it rides the wave.

Prioritizing semantic cohesion over data consolidation

SAP has spent years refining its data strategy. While Datasphere offered value in real-time processing, it was never intended to serve as a central data platform — especially with Snowflake, Databricks and Google Cloud leading in that space. The launch of Business Data Cloud (BDC) acknowledges this external reliance, advancing the same ambition Datasphere once aimed for: a harmonized, semantically enriched, agent-ready data layer.

 

BDC’s zero-copy architecture and native integrations with platforms like Databricks reflect this evolution. SAP is betting on semantic fabrics, not data lakes. Knowledge graphs across HR, finance and procurement add structure, while embedded governance ensures auditability. This plays to SAP’s strengths. The offering feels tailored to existing customers and midmarket newcomers, especially those with aggressive AI ambitions.

 

That said, harmonized data remains one of the hardest problems in enterprise IT. BDC assumes a level of data maturity that many SAP customers have not yet achieved. A large portion of the install base remains on premises, but for those already in the cloud — or willing to invest — the value proposition is becoming clearer. And SAP’s traction among net-new logos suggests the offering resonates with digital-native buyers looking to operationalize AI quickly.

Turning channel partners into strategic collaborators

The biggest partner takeaway from Sapphire was that SAP is no longer content with resell-and-implement motions. It wants deeper collaboration. The flywheel — applications, data, AI — only spins fast enough when partners are embedded into engineering, orchestration and execution. That shift has forced SAP to rearchitect how it manages partner access, tools and territory, with trust becoming a central pillar of its partner strategy.

 

SAP is also handing over the sales motions for its innovation stack. Partners now have access to the same internal tools used to build and deploy agents: Joule Studio, Prompt Optimizer, LeanIX, SAP Build and WalkMe. This is not only enablement but also an invitation to build within the stack. But access comes with expectation. These tools require fluency, not just familiarity. SAP wants to work with a deeper class of partner that can move from implementation to cocreation.

 

Equally important: territory. SAP is expanding partner-led coverage, particularly in North America and Europe. The new SAP Referral Program, scheduled to launch in 3Q25, formalizes this shift. Strategic partners will now own more of the Customer Value Journey — sales, delivery and post-sales engagement — especially in midmarket and vertical contexts.

 

Perhaps the most strategic move, though, is cultural. SAP is not just training partners; it is also increasingly transferring responsibility. KPMG is delivering structured Joule certifications. Accenture is codeveloping production agents. Capgemini is integrating Databricks into SAP’s data stack. Meanwhile, PartnerEdge, SAP’s overall partner program, is evolving to reward cloud performance, AI capability and vertical differentiation. Success in these areas will see the greatest investment and visibility from SAP.

SAP moves ahead with strategic clarity

All told, Sapphire 2025 marked a turning point, not because SAP introduced a radically new vision but because the company finally appears ready to execute on the one it has been quietly building for years. The narrative has matured, the tools are in place, and the platform is coherent. And the partners, customers and product ecosystem are starting to move together. Some heavy lifting remains, such as around migrations, data harmonization and partner fluency, but if SAP can stay focused on delivering scalable value through agentic AI, integrated data platforms and partner-enabled execution, the next chapter of the company’s growth story will look a lot less like catching up to the cloud and a lot more like leading in it.

Hitachi Digital Services Brings IT + OT + AI to Mission-critical Systems

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From May 20 to 21, 2026, in Dallas, Hitachi Digital Services hosted close to 100 analysts and advisers for a two-day summit featuring Hitachi leaders, clients and technology partners. The following reflects TBR’s observations from the event, informal conversations with Hitachi leaders and clients, and TBR’s ongoing analysis of the overall IT services and professional services space.

Hitachi Digital Services perfectly positioned to take advantage of IT-OT convergence and AI adoption

Two tectonic technology shifts happening now and opening massive revenue opportunities play straight into Hitachi’s strengths, positioning Hitachi Digital Services for significant growth over the next five years. With IT and OT convergence accelerating and enterprises increasingly adopting AI at scale, Hitachi Digital Services can rely on Hitachi’s engineering DNA, deep expertise in specific industries, and firsthand experience in manufacturing as the foundation for a build-integrate-operate value proposition. The analysts and advisers event highlighted how well Hitachi Digital Services brings the entire Hitachi company to its clients, remains rooted in Hitachi’s engineering approach to everything, and maintains its focus on strategic priorities, even as the market shifts all around them.

 

Although smaller than the typical IT and professional services firms covered by TBR, Hitachi Digital Services warrants close attention in the coming years. Its distinctive business model, strategic direction and performance — particularly its combination of IT, OT, AI and domain expertise — position Hitachi Digital Services as a potential outlier in the IT services landscape.

Hitachi’s broader capabilities and assets help Hitachi Digital Services deliver unique combination of IT, OT and AI

Though only a two-day event, Hitachi included an impressive breadth of client speakers and panel participants, all from Hitachi Digital Services’ core industries, while also bringing technology partners into the discussion, occasionally simultaneously. One major telecom player described their relationship with Hitachi Digital Services as a client and with Hitachi overall as a go-to-market technology partner. An automotive client praised Hitachi Digital Services’ ability to “make our problems their problems to solve” and called out Hitachi’s “asset knowledge,” which blended IT capabilities with OT experience.

 

During onstage presentations and informal discussions with TBR, clients noted the importance of Hitachi Digital Services’ ability to seamlessly tap into the larger Hitachi organization and bring deeply technical engineering expertise to bear. Not surprisingly, clients attending the event also noted their well-established relationships with Hitachi, reinforcing Hitachi Digital Services’ messages around sustained focus on clients’ evolving issues. TBR’s assessment of Hitachi Digital Services’ client service value proposition and technology partner alliance strategy could be best summed up by a comment from a cloud vendor on stage with Hitachi Digital Services: “showing up together with Hitachi, delivering results, day after day.”

 

On Day 1 of the summit, a senior Hitachi Digital Services executive said the company maintained an “R&D and engineering first, consulting second mindset,” a sentiment echoed throughout the event. Another executive noted that innovation “starts with Hitachi engineering R&D.” Discussions around IT-OT convergence and Industry 5.0 included elements of consulting but remained rooted in engineering. For example, when discussing IT and OT convergence, Hitachi leaders described the company’s state-of-the-art railcar manufacturing plant in Maryland, a real, physical, operational test bed for digital innovations and Hitachi Digital Services’ IT + OT + AI value proposition. For Industry 5.0, Hitachi executives discussed Hitachi Digital Services’ overall AI strategy and noted the confluence of human and AI collaboration aided by AI agents.

 

In TBR’s view, the consistent undercurrent of engineering and R&D separates Hitachi Digital Services from peers in the IT services and consulting space, in part because of the credibility behind Hitachi’s “engineering first” assertion. Any company can say it has engineering capabilities; Hitachi builds railcars.

Domain expertise and organizational intelligence needed for broader AI adoption and agentic AI

Regarding AI, leaders at Hitachi Digital Services emphasized that effective AI begins with deep knowledge. Hitachi brings a strong foundation in business, operations, design, manufacturing and maintenance — an extensive base of expertise that it leverages to power its AI initiatives. In short, Hitachi Digital Services professionals argued they have more robust intelligence to feed into AI models and algorithms than most peers. Hitachi leaders also highlighted the company’s focus on organizational intelligence and its long-standing capabilities around “capturing the intelligence of complex organizations.”

 

In TBR’s view, Hitachi’s only complex organization likely provides a useful starting point for understanding the applicability of AI in organizational intelligence. Regarding agentic AI, Hitachi Digital Services leaders said AI agents must be specific to a domain, such as industrial AI, engineering AI or cybersecurity AI — an assertion that plays to Hitachi’s strengths. They also expect agentic AI adoption will accelerate in 2026, particularly around process and application modernization. One Hitachi Digital Services leader anticipated a shift from “minimum viable product” to “minimum viable agent,” a neat turn of phrase that might indicate both a shift toward a more consulting-focused mindset and internal pressures to deploy more AI-enabled assets. TBR notes that every one of Hitachi Digital Services’ competitors is working through those same shifts.

Mission-critical IT + OT + AI

In TBR’s view, Hitachi Digital Services’ ability to lean on the broader Hitachi company’s engineering expertise and real-world physical assets provides Hitachi Digital Services with clear separation from peers in the IT services space. If Hitachi Digital Services can deliver results in mission-critical — and constantly moving — settings, such as railway operations, clients in less dynamic environments can be assured of its capabilities.

Hitachi leaders noted shifts in the broader IT and OT spaces, such as the greater attention being paid to cybersecurity risks in OT and CFOs being generally more aware of the costs of funding fully separate IT and OT systems, which TBR believes may accelerate IT-OT convergence. Complemented by AI and infused with domain expertise, Hitachi Digital Services, in TBR’s view, should maintain a clearly differentiated position within the digital transformation and IT services space.

 

As a potential partner for large ISVs and cloud hyperscalers, Hitachi Digital Services’ combination of IT, OT and AI capabilities provides easily understandable differentiation. For large enterprises in Hitachi Digital Services’ target industries, Hitachi’s track record in mission-critical environments and the company’s sustained R&D and innovation create a compelling value proposition.

 

TBR will be more closely tracking Hitachi Digital Services’ evolution, particularly as IT-OT convergence accelerates and Hitachi Digital Services’ role in the broader ecosystem grows.

 

Graph: Degree of Consideration for Expanding Alliance Relationships (Source: TBR 1H25)

Salesforce Fills Its Data Governance Gap, Assembling an End-to-end Platform to Power Agentic Workflows

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Informatica acquisition is big step in already robust platform strategy

As agentic AI begins to blur the lines between applications and platforms, Salesforce continues to demonstrate its intent to lead in embracing change. Ever since the company’s 2018 acquisition of MuleSoft, purchasing platform vendors has, on average, been an every-other-year occurrence — and Salesforce continued this pattern in May when it finally entered into a definitive agreement to acquire Informatica. This marked the culmination of a yearlong pursuit, as the two companies were unable to reach an agreement at a rumored $11 billion price point in April 2024.

 

Waiting paid off for Salesforce, which is now expected to close at a price point of $8 billion — $3 billion less than the previously rumored figure. While the acquisition cost decreased due to a decline in Informatica’s publicly traded stock price, the company’s IP only became more relevant to Salesforce’s data and AI strategy over the year. As Salesforce CEO Marc Benioff put it, the merger will result in “the most complete agent-ready data platform in the industry.” It is a bold statement, but there is merit to the claim — Salesforce’s cohesive platform portfolio aligns well with the company’s Agentforce ambitions.

 

Informatica is an important addition to this cohesive portfolio. Data governance and management was a lingering capability gap — one of growing importance due to the lack of standardized data formats across acquired IP and the third-party applications offered via AppExchange.

 

Connecting customers’ entire front-office estate to Agentforce will require these data formats to be standardized across these systems, compelling Salesforce to offer these capabilities natively. This will bring Salesforce a big step closer to delivering on its promise to offer customers a unified, end-to-end portfolio capable of supporting agentic workflows. Selling the story and delivering on customers’ ROI expectations will be the next step, requiring Salesforce to be an innovator in contextualized model development as the company looks to unlock new use cases.

Informatica and its place within Data Cloud

With Informatica, Salesforce will gain a data management and governance leader. TBR covers Informatica’s product development strategy in greater depth in the recent special report Data Quality & Governance Pillars, and Ecosystem-led Approach Mark Informatica’s Entry Into Agentic AI. To quickly reiterate some of the big takeaways:

  • Informatica has become more ambitious over the past year in its agentic AI pursuits. The company argues that agents that can reason and act across workflows require far more than large language models. They need clean data, reliable orchestration and deep context. Informatica views its metadata-rich foundation — anchored in CLAIRE (Cloud-scale AI-powered Real-time Intelligence Engine) — as a critical advantage in this emerging stack. With this foundation, the company will target the AI opportunity from two angles. As TBR describes in the special report linked above, the two approaches include “Informatica for GenAI, in which customers use IDMC’s [Intelligent Data Management Cloud] data management capabilities to enable enterprises’ GenAI use cases; and GenAI from Informatica, where customers leverage Informatica’s GenAI offerings.” CLAIRE Copilot entered general availability at the event, while CLAIRE GPT, which is already used by over 550 customers, continues to automate cataloging, data access and metadata queries. In addition, Informatica made its formal entry into the agentic AI space. Eight new CLAIRE Agents were announced — focused on core data management tasks like quality, ingestion, lineage and modernization — and are scheduled to enter preview in the second half of 2025.
  • Ecosystem development is a major priority for Informatica as well. The firm highlighted its expanding relationship with both Microsoft and Salesforce. Microsoft and Informatica continue to deepen their ties, most notably with the integration of Informatica Data Quality as a native application within Microsoft Fabric, while CLAIRE Copilot, built using Azure OpenAI, reinforces the alignment. Still, this development is occurring outside the Salesforce umbrella. Under Salesforce ownership, integrations between Informatica and Microsoft will likely be deprioritized. However, the impact of the acquisition on Informatica’s broader relationships with third-party SaaS vendors will depend on Salesforce’s commitment to maintaining its open ecosystem approach.

Meanwhile, the company’s standard platform assets are likely of greater relevance to Salesforce. Informatica’s IDMC will bring ingestion pipelines and ETL (Extract, Transform, Load) tooling purpose-built for hybrid environments — something Salesforce would otherwise need to build or buy elsewhere. And with Informatica’s governance and metadata engine (CLAIRE), Salesforce will gain explainability and policy controls that are critical for deploying AI in regulated environments.

 

In short, Informatica will equip Salesforce with the ingestion and governance layers Data Cloud is missing — layers that are now prerequisites for scaling AI credibly in the enterprise. Crucially, Informatica’s prebuilt integrations and policy automation tools lower the barriers to entry for enterprise teams experimenting with agents, accelerating time to value for Agentforce deployments.

Salesforce is looking for a way to accelerate top-line performance with an end-to-end portfolio capable of powering automated workflows

Informatica joins MuleSoft, Slack, Own and Tableau in the ranks of large IP purchases Salesforce has made in pursuit of its platform-meets-application layer vision. While AI is still a relatively new part of this conversation, building a platform backbone and centralizing workflow management around Slack is a concept that has been around since the business messaging application was acquired in 2020.

 

The emergence of agentic AI brings a powerful new technology to drive deeper automation, which aligns perfectly with this existing goal but also elevates the need for a robust, well-rounded data layer. Agentic outcomes are contingent upon access to quality, standardized data and metadata, and the ability to natively offer modern governance capabilities via Data Cloud will help Salesforce deliver the positive ROI it is chasing with Agentforce.

 

This moves Salesforce closer to realizing the CRM-plus-data-plus-AI vision that the company’s leadership has been championing. That said, execution remains to be seen. MuleSoft and Tableau are healthy growth drivers for Salesforce, but Data & AI makes up just $1 billion of the company’s $37.2 billion in annual recurring revenue (ARR) as of CY1Q25. Agentforce contributes only $100 million in ARR.

 

Despite Agentforce’s triple-digit year-to-year growth, this scale means the contribution is not enough to move the needle in terms of total top-line performance. TBR continues to believe this will come with time as the still-nascent platforms mature in the market, though this will require the company to sustain the platform’s triple-digit growth in the short term, followed by high-double-digit growth in the medium term.

 

Internally, Salesforce is hiring into its sales teams and setting a goal for each of its account executives to land an Agentforce deal within the year. Ecosystem development will complement this strategy as Salesforce works with IT services partners to sell Agentforce and accelerate time to value for early adopters. TBR’s conversations with ecosystem channel partners have led us to suspect that the platform’s growth will accelerate in the future, but Salesforce will need to execute in the days and months ahead.

Informatica purchase will be margin accretive in CY2026

To briefly touch on the economics of the transaction, Salesforce anticipates the acquisition will be accretive to operating margins and cash flows by the end of the second year post-integration, so TBR does not expect it to derail the progress the company has made in establishing a new margin floor.

 

Near-term impacts are expected but should roll off quickly, allowing Salesforce to continue enjoying the ample free cash flow it has earned through its disciplined approach to cost-cutting. This will provide the company with meaningful liquidity, positioning it to remain a strategic acquirer long-term, as evidenced by the less splashy Convergence acquisition, which was announced in May.

Long-term acquisition strategy

TBR expects Salesforce to focus on integrating Informatica before committing to other large purchases. That said, smaller IP- and talent-driven acquisitions in the AI space will likely ramp up, similar to the recently announced acquisition of Convergence, an AI startup focused on agentic AI research. These smaller acquisitions will play a role in Salesforce’s portfolio development strategy.

 

Moreover, the company’s operating efficiency plan more than doubled free cash flow between 2023 and 2025, providing Salesforce with the capital to fund an accelerated acquisition strategy. AI will be a primary target of these acquisitions, though vertical-specific front-office solutions could also be major considerations as the company broadens its portfolio to create new native applications to connect to Agentforce.

Salesforce’s acquisition of Informatica is not only additive but also connective

By bringing governance, metadata and ingestion capabilities in-house, Salesforce will fill critical platform gaps that limit the company’s ability to scale Agentforce and deliver on its broader AI vision. The pieces now fit: a unified stack spanning CRM, data and AI. Execution, of course, is the next hurdle.

 

Agentforce is still in the early days of development, and the company’s ability to drive meaningful ARR from the platform will depend on sustained growth, smart ecosystem plays and clear ROI for customers. But once Informatica is in place, Salesforce will be better equipped to turn its AI ambitions into enterprise outcomes — and to do so in a unified way.

PwC Japan: Trust, Unity and Focus

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On April 15 and 16, PwC Japan hosted over 20 analysts, a partner and PwC executives for a day and a half summit at the company’s Technology Laboratory in Tokyo. Chief Strategy Officer and Chief Innovation Officer Kenji Katsura set the tone when opening the meeting by explaining that over the course of the event attendees would be hearing from leaders across PwC’s businesses — including audit, tax, deals and consulting — highlighting the importance of PwC’s strategy to deliver the full range of the firm’s expertise to clients. While ensuring that PwC’s services remain highly relevant to clients in Japan, the firm’s GTM strategy is closely aligned with its global network. This alignment allows PwC Japan to leverage the best practices and innovations from across the network while also contributing homegrown insights and advancements that can benefit clients worldwide.

The event included demos, presentations and one-on-one breakouts that allowed analysts to gain firsthand knowledge of PwC Japan’s evolving strategy. Demonstrating culture and an understanding of local business dynamics still provides an important nuance that allows PwC to elevate the value of its services, especially in the current uncertain geopolitical environment, as having highly country-specific capabilities and dedicated staff may become a greater asset than more explicitly globalized organizations. The following write-up summarizes TBR’s takeaways from the event and provides a glimpse into what we believe will set the next chapter of PwC’s business.

 

As a node in PwC’s ever-expanding ecosystem, Technology Laboratory brings art and science together through physical assets

Starting with a hands-on demo led by Technology Laboratory lead Shinichiro Sanji, PwC’s Technology Laboratory team demonstrated the pivot the firm has begun making in its interactions with clients, where the outcome of workshops has evolved beyond the art of the possible and into tangible solutions backed by the use of physical assets. Responsible for PwC’s tech-driven go-to-market strategy, which builds a business pipeline through cross-industry collaboration, Technology Laboratory in Tokyo is a first of its kind and enables the firm to demonstrate how it can interlink buyers beyond the traditional IT and/or finance functions into operational technology.

 

The cocreation of assets with commercial and public clients as well as academia will also help PwC demonstrate understanding and connectivity of physical AI and revamp industries where industrialized robotics are heavily in use. The Experience Center also remains an integral part of the Technology Laboratory’s success as creating future scenarios based on market and industry trends necessitates market insights delivered through multidisciplinary skills teams. With the Technology Laboratory and Experience Center housed adjacent to each other, it streamlines collaboration and interaction between teams when needed, while maintaining enough separation to enhance the unique value each team contributes during client workshops.

 

Meanwhile, as PwC strengthens its local relationships, it also continues to build nodes across its member firms that demonstrate an appetite for innovation and support client needs. For example, the firm recently announced the opening of the OT Cyber Lab in Dubai, United Arab Emirates (UAE) and the expansion of PwC’s Reinvention Lab in Australia, where it added hands-on capabilities for clients to test out advanced technologies.

We see PwC’s Business Experience Technology (BXT) and Business Model Reinvention (BMR) frameworks as the connecting glue between the various labs across PwC member firms, especially as the BXT raised the bar high for the firm’s consultants to drive outcomes. Now BMR provides a structured approach for the labs to have guided conversations with clients around their functional technology needs.

Maintaining continuity in executing against strategic priorities brings PwC closer, one member firm at a time

Following the Technology Laboratory demo, Masataka Kubota, Chair and Territory Senior Partner, PwC Japan Group CEO, kicked off the event by setting a high-level agenda centered on five megatrends: Climate Change, Tech Disruption, Demographic Shift, Fracturing World and Social Instability. These themes guided PwC’s presentations across its Assurance, Tax, Advisory and Consulting practices, with each area exploring or delving deeper into these trends.

 

PwC executives’ emphasis on reinforcing the alignment of PwC Japan and PwC Global strategies around BMR, trust, sustainability, and AI and data closely resonated with what TBR heard in a pair of similar events in the fall of 2024 in EMEA and the U.S. Kubota further amplified PwC member firms’ efforts around unity. PwC Japan’s regional customization and diversity remain vital to the firm’s success, especially as local clients lean on the company’s expertise and guidance to navigate choppy international market conditions.

 

Masaki Yasui, PwC Japan Group’s Consulting leader, continued the discussion, providing an update and insights into the firm’s line of business. Doubling in size in terms of people since late 2018, PwC Japan’s Consulting practice now houses 5,130 of the firm’s more than 12,700 employees in Japan and has grown at a double-digit rate for around 10 years — a pace that is expected to be sustained through 2030, according to Yasui. This will be an impressive achievement for PwC Japan’s consulting business, given the macroeconomic headwinds and impact on discretionary spending and consequently on consulting opportunities.

 

According to TBR’s management consulting research, consulting revenue experienced a deceleration in 2024 of 3.1% year-to-year, down from 8.1% in 2023, a trend we expect to continue throughout 2025.

Deploying tech-enabled arbitrage model will test PwC’s readiness to transform its professional services model, with consulting being most ripe for it

Leaning on the firm’s ongoing success rooted in its client-centric approach, focus on priority accounts, portfolio expansion and investment in growth areas provided a strong foundation for PwC Japan’s consulting growth. While these efforts are not unique to PwC, we believe what has helped the firm thus far is its collaborative culture across lines of business, making it appealing for partners to be part of. Growth will likely come from PwC Japan investing in new services to meet demand with BMR, strengthening its digital core, and front-office transformation serving as the lead in parts of the clients’ discussions.

 

Meanwhile, focusing on multinational clients while tapping into the power of PwC Japan’s Business Network will help the firm bridge opportunities with global clients in and outside Japan, further amplifying the need for better member firm collaboration. PwC Japan recognizes the evolving professional service market dynamics and has built out a new three-layer model for sustainable growth, with the key separation between the first and second layers being less human-dependent. Executing on the second and third layers, which are largely focused on accounting for changes in staffing and commercial models enabled through data intelligence and data monetization, will once again test PwC Japan’s collaborative culture, as often such initiatives are more challenging to be sold and managed internally than to bring externally with clients.

 

Many professional services companies grapple with similar challenges largely because of the time and materials (T&M) commercial model that consulting companies typically employ for such services. Developing data monetization and a fee-for-service type of model essentially requires companies like PwC to depart from the T&M model. We believe PwC Japan is one step ahead of many of its competitors in that regard as its consulting business has largely been driven by fixed-price engagements, making it easier to bridge into the fee-for-service setup it is looking to pursue as part of its layers two and three strategies.

 

The challenge for PwC Japan will be to educate other member firms on how to approach the opportunities, as elsewhere T&M remains the predominant commercial model. Further, PwC Japan, just like other member firms, sees managed services as part of its ability to continue to grow its business. While it is still a small portion of the current revenue composition (about 4% to 6% at the global level, according to TBR estimates), the firm continues to explore avenues to augment that gap, with leaning on its tax and cyber practice capabilities, delivery partners, and acquisitions among its top choices.

PwC’s Industrial Structural Transformation framework: A road map to the firm’s ability to execute through integrated scale and packaged services

Here lies the opportunity for PwC: developing a framework that demonstrates unity and focus while relying on its core success around trust. During the event, PwC unveiled an Industrial Structural Transformation (IST) framework, which we believe provides the necessary road map to execute against the firm’s aspiration of what the next chapter of the firm might look like. Bringing together all parts of the business — Assurance, Tax, Advisory and Consulting — and replicating them across industries while using data intelligence and a fee-for-service commercial model can help PwC build a foundation that resonates across all member firms.

 

Starting with use cases in Japan across segments like mobility provides a glimpse into how the framework can be applied as the evolution of AI extends into the physical world, and how the architecture of the entire industry can be transformed beyond the use of the software to include the business and social rules. Developing the backbone of going to market through integrated scale is the first step. Executing against it, especially bringing use cases outside of Japan to other member firms, which often deal with their local client issues, can prove to be a rewarding challenge.

Three key areas which PwC Japan discussed at length during the event — sustainability, risk management and tax — brought to light the closer collaboration and applicability of the framework at scale between the various parts of PwC’s portfolio. Sustainability and risk management bring together assurance and consulting while tax provides a conduit for closer collaboration with consulting.

 

Developing solutions that are function-specific provides the necessary horizontal connection across these areas while relying on the firm’s industry knowledge to demonstrate value and deliver outcomes. We believe a large portion of PwC’s success will come from including its technology partners at every step of development, deployment and management of its IST framework as partner feedback and knowledge management have become as critical as ever to understand how professional services companies go to market.

Application of technology solutions beyond the marketing hype elevates PwC Japan’s soberness and readiness to support the global network in handling macro disruptors

Virtually no market discussions today exclude data and AI. Takuya Fujikawa, PwC Japan Group Chief AI Officer, Data and AI Leader, took the opportunity to provide an update on the firm’s data and AI practice at the onset of the second day of the event. One important nuance struck TBR about PwC Japan’s portfolio: its applicability of AI across multiple domain areas, rather than simply drilling down on generative AI or agentic AI, which have been the predominant focus in similar settings. Adhering to open data principles while relying on its industry and functional expertise provides a strong foundation for the firm’s data and AI portfolio with examples around threat intelligence, intelligent business analytics or power market analytics highlighting various use cases.

 

With PwC US recently launching the Agentic Operating System, we expect PwC Japan to lean on these experiences and capabilities and follow suit with agentic AI solutions that meet local client needs for driving efficient operations. We expect the rollout to be bidirectional and other member firms to look to collaborate with PwC Japan on emulating its portfolio offerings. Scaling the use of such solutions will fit nicely and support PwC Japan consulting’s three-layer growth model, especially around the data intelligence and data monetization opportunities and the tech-enabled arbitrage model.

Additionally, discussions throughout the second day provided deeper insights into other strategic domains of PwC Japan’s portfolio, such as sustainability and trust, including cybersecurity. Common themes across value creation enabled through technology amplified the need for better alignment among practice areas within PwC Japan, especially as buyers’ focus in each area has shifted toward translating respective market challenges to business implications.

 

Within sustainability, PwC remains focused on creating customer value by emphasizing cross-business themes, including decarbonization and biodiversity, with most of the opportunities centered on government reporting mandates, further demonstrating the need for collaboration between audit and consulting services.

 

Withing trust, leadership highlighted cybersecurity and cyber intelligence services – both important elements of PwC Japan’s strategy – including its collaboration with delivery partners, such as with TIS Inc. for use of remote monitoring, alert responses and emergency interventions, among other security services.

Enabled by a humble and gracious culture, PwC Japan sets the bar high for what’s next in the firm’s strategy evolution

Just as technologies arm PwC consultants with tools to solve complex business challenges, the Technology Laboratory provides the enabling environment for all presentations, as regardless if executives spoke about audit and assurance, tax, advisory or consulting, they all leaned on a piece of technology that helped them connect the dots between art of the possible and the answer through the tangible.

 

As macroeconomic uncertainty persists, PwC has realized that instead of trying to fix issues outside its control, it is better to focus on its own transformation to prepare for addressing client challenges. We recognize there is still an opportunity for the firm to strengthen relationships with both internal and external stakeholders, including its alliance partners. Building a strong, common foundation for member firms is a crucial first step for integrated scaling. This involves connecting the Technology Laboratory and Experience Centers to deploy BXT and BMR at scale. Leveraging their experience with fixed-price contracts, they can then pivot toward fee-for-service models, providing the necessary frameworks for collaboration.

 

PwC Japan Group and its leadership set the bar high for its member firm counterparts in what it would take for the firms to work together more closely. Starting with better service line collaboration and portfolio offerings rollouts to establishing common KPIs and shared services are some of the prerequisites, and PwC Japan seems to have the ingredients to make it work all together. And while clients are less worried about how a firm operates and are more focused on solving their business and technology problems, working with a vendor that has its own house in order certainly makes it an easier partnership.

EY Reimagines Global Mobility: Human-centric, Tech-enabled and Business-critical

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EY Global Mobility Reimagined 2025, Barcelona: Over two days in Barcelona, EY hosted more than 150 clients and a few industry analysts for its first in-person EY Global Mobility Reimagined conference since 2019. During the event, TBR spoke with EY leaders, EY technologists and EY clients from a diverse set of countries and industries. Nearly all the client attendees serve within their enterprise’s talent, mobility or human resources organizations, and a common vibe throughout the event was the changing challenges facing HR professionals. The following reflects both TBR’s observations and interactions at the event and our ongoing research and analysis of EY. Three themes emerged over the two days of the conference, both from the presentations and in discussions with EY leaders and EY clients. First, rapidly changing technology, particularly AI, permeates every aspect of mobility, but the EY leaders and conference attendees returned repeatedly to the need to keep humans at the core. Second, EY did not emphasize or sell what EY can do but rather kept the focus on clients’ problems. A Tech Connect showcase featured cool new EY software and solutions, but the conference plenaries and breakout sessions never veered into a sales pitch for EY’s solutions. Third, in discussions with EY leaders, TBR heard a clear strategy for continued rapid growth and evolving technology alliances, underpinned by a commitment to managed services.

Humans remain central to mobility, although technology can help

Mobility — moving talent around the world on short- and long-term assignments — is inherently stressful for the employee and risk-inducing for the employer, so while technologies can improve the processes and mitigate risks, the experience remains a human one. Even with generative AI (GenAI) and agentic AI, everyone strives to keep humans fully at the center. Three moments during the conference highlighted this theme.

 

During a breakout session focused on emerging technologies, EY noted that nearly all current mobility-focused technologies and platforms have been designed around corporate requirements and policies. In the near future, technologies will be designed around the employee experience. EY’s new Microsoft Teams app for mobility, described below, provides an example of that shift. Second, during a panel discussion about the ethical concerns around AI adoption, one EY leader noted that even if agentic AI and other tools replace many of mobility professionals’ day-to-day tasks, nothing can replace the human touch, especially during a stressful time like an international relocation. Once again, the technology must enhance the employee experience. Lastly, EY professionals noted during a breakout panel on immigration that employers have had a mindset shift with respect to permanent residency.

 

Previously, employees tried to shift their residency status in a foreign country without assistance from their employer, reflecting employers’ concerns that once established in a country, those employees would be inclined to stay, perhaps necessitating a split with the employer. In some countries — Saudi Arabia was cited as a prime example — annual visa and work permit renewals are both expensive and stressful. Over a long-term assignment, paying for an employee to gain permanent residency could be cost effective and, by demonstrating support and bringing corporate resources to bear, could increase employee retention. Happy employees who stay longer and build better relationships with clients lead to better returns for the company on its investment in talent and mobility.

The event offered a forum for clients to discuss challenges and how they are coping

EY sold without selling. Every session included EY partners describing the firm’s views of the challenges facing mobility professionals and HR teams overall, but, with the exception of the Tech Connect showcase, EY’s capabilities were not front and center. In the majority of sessions, EY’s capabilities and the firm’s ability to help address those challenges simply did not come up. The EY partners focused on setting the overall parameters of the discussion, providing context around the challenges clients face, and then allowing those clients to engage with EY and with other clients about how they are coping.

 

In TBR’s view, this approach separates EY from peers while also reflecting the ethos TBR has observed at other EY events, such as the Strategic Growth Forum. EY provides clients a comfortable space to talk about issues and commiserate, without a hard EY sell. One attendee told TBR the conference made him feel better because his problems were not nearly as dire as the other professionals he spoke with during the event.

 

Navigating GenAI: Insights, Strategies and Opportunities for 2025 — Watch “2025 Predictions for GenAI” on demand now

Mobility practice serves as the glue across EY globally

In sidebar discussions with TBR, EY leaders’ comments reinforced two trends about Mobility — and the firm’s People Advisory Services – overall. First, People Advisory Services is growing ahead of the overall firm. The practice has been investing in managed services capabilities and scale, with an appreciation that noncommoditized managed services will be a significant component of People Advisory Services revenues. Second, Mobility remains an essential part of the glue that keeps EY operating as a global firm serving global clients.

 

In addition, during the event TBR noted a clear emphasis on Microsoft as a strategic partner, but EY noted expectations that other technology alliance partners, including ServiceNow, will become increasingly strategic to Mobility. Regarding the third point, Mobility services have challenged other Big Four firms, in part because — as practiced by EY — the burdens include forced cross-border coordination by and shared resources from separate member firms, managing a plethora of niche providers and technology partners, and deploying a software business model.

 

Countering those burdens, Mobility can serve as a centripetal force, helping align EY’s Tax, Audit and Advisory practices and giving additional weight to the firm’s global capabilities (and leadership, notably). As a complementary service to consulting or tax, Mobility advances EY’s client retention strategies, particularly with its largest clients. Internal benefits and external rewards. Win- win.

Emerging technologies begin to permeate HR

AI could not be ignored, in part because the notion of agentic AI-related disruption was an underlying current throughout the event. While not diminishing the challenges of adopting emerging technologies, EY professionals repeatedly stressed the need to adopt soon, smartly and with a long-term plan in place. In a breakout session, EY professionals used a now/next framework to describe a few trends in emerging technologies (including the corporate requirements and employee experience described above).

 

Currently, HR professionals and employees must wrangle with multiple technologies and platforms to execute on mobility challenges; in the near term, everyone will enjoy streamlined technologies with cohesive data-sharing strategies. Today, HR professionals rely on dashboards to provide analytics on mobility and other People Advisory Services issues, but soon predictive AI-driven analytics will provide insights and quicker decision making, with fewer (or perhaps no) dashboards.

 

Notably, when surveyed during the breakout session, the majority of HR professionals in attendance opted for “streamlined technologies” as their top priority. In a separate session, client attendees said their greatest expectation from AI would be data analytics and enhanced reporting.

A few other technology-centric comments and observations from the event:

  • EY partners said Mobility professionals did not need to wait for the next GenAI update or release — the technology needed is here and can be applied now.
  • Previous notions about data complexity may be outdated as the technology exists now to handle that complexity — HR professionals should focus on what they want to accomplish, not whether their data is perfect. (Side note: in the same discussion, EY partners observed that the biggest roadblock to adoption remains the availability of quality data.)
  • The ethics around GenAI remain … murky. EY partners noted the environmental impact of energy-hungry data centers and suggested a gap exists between innovation and accountability, eventually cautioning for a go-slower approach to AI adoption.

Overall, technology played across every aspect of Mobility with the common theme around enhancing the employee experience and measuring how EY’s Mobility practice can benefit a company’s strategy and employee retention, and even improve relationships with clients. In short: use technology wisely, with help from EY.

EY integrates mobility management into Microsoft Teams

The Tech Connect showcase included nine solutions, most notably EY Mobility Pathway, a corporate mobility management tool; EY Mobility Carbon Tracker, a customizable tool for scenario planning and carbon footprint measuring; and new Microsoft Teams app for mobility, a seat-based SaaS offering deployed as an application on Microsoft Teams. The last one stole the show. Employees do not need to log on to another platform, remember another password or navigate an unfamiliar app, but rather add the new Microsoft Teams app for mobility app to their Teams experience. The software can be configured to clients’ specific mobility needs, such as shipping dates, travel, housing, tax and other elements of the international relocation journey.

 

The new Microsoft Teams app for mobility looks and feels like a Teams app, has all the employer data, and seamlessly — as the employee experiences it — pulls in data and information from the third-party providers the employer uses, such as shipping companies or short-term housing agents. EY partners explained that new Microsoft Teams app for mobility is currently live with a few clients, and will go live soon across more of EY.

 

In TBR’s view, EY made a significant strategic decision in embedding new Microsoft Teams app for mobility into Microsoft Teams and not creating a separate employee-centric dashboard. This keeps employees in an environment they are already comfortable working in and avoids additional stress during a difficult time. EY’s commercial model for new Microsoft Teams app for mobility requires the firm to invest in software support and maintenance capabilities, but feeds into the firm’s overall managed services play.

Immigration rises to C-level topic

An immigration session resonated with TBR, in part because the TBR principal analyst in attendance once stamped visas at a U.S. embassy, but also because of the political issues that were openly discussed. EY partners noted that 2024 was a “super year” for elections globally, and immigration issues featured prominently in election politics in many countries. Extrapolating to global enterprises, EY partners made a convincing case that immigration has become a boardroom issue. EY’s Batia Stein and Chris Gordon noted that chief human resources officers (CHROs) and other executives surveyed by EY said the top option for solving talent gaps is moving talent where it is needed, no matter where on the globe — so, mobility.

 

As described above, assisting with permanent residency can alleviate some employee stress and enhance client and employee retention. In addition, using technology to enhance the employee mobility experience is not simply the right thing to do for employees; EY also believes the Mobility practice can be a business driver. And at a time when compliance issues have become more frequent and fraught, exacerbated by immigration raids and joint immigration and tax audits, Mobility can be a business driver for EY, too.

People Advisory Services global infinity loop reflects EY’s approach to clients’ issues

EY has a visual of its People Advisory Services Tax practice that features an infinity loop with People Advisory Services on one side and People Managed Services on the other, with all the related offerings creating an endless cycle of services, surrounded by EY’s other practices and offerings, such as Strategy & Transactions and Sustainability. The infinity loop helps understand EY’s positioning of its services and, perhaps more importantly, reflects EY’s understanding of its clients’ needs and challenges.

 

Companies keep recruiting, hiring, paying, rewarding, moving, repatriating, retiring and hiring in an endless loop, and EY has capabilities — including consulting, tax and software — that can accelerate movement around that endless loop. EY did not need to say that at the Global Mobility Reimagined conference, as clients understood it already. EY also has a stated ambition to grow People Advisory Services to more than $3 billion by 2031. Absent the worst possible global political and economic scenarios, including a drastic curtailment of global mobility, TBR believes that ambition is perhaps a bit too modest.

Data Quality & Governance Pillars, and Ecosystem-led Approach Mark Informatica’s Entry Into Agentic AI

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Building on last year’s theme of modernization, where Informatica highlighted innovations to fast-track migrations from legacy PowerCenter and Master Data Management (MDM) to Informatica Data Management Cloud (IDMC) in the cloud — accounting for over half of Informatica’s business — Informatica World 2025 in Las Vegas was all about agentic AI, and the crucial, yet still sometimes overlooked, role of data. With its ability to apply reasoning to handle more complex, multipart workflows, agentic AI has rapidly emerged as AI’s next frontier. Although agentic AI promises increased productivity, AI agents require a few key elements, including orchestration, a vast knowledge base and governance. With the wealth of metadata in CLAIRE, the AI engine powering IDMC, it was only a matter of time until Informatica used some of its core differentiators to push into the agentic AI space to not only craft a future for more autonomous data management but also to give customers the tools needed to build and orchestrate their own agents.

 

Informatica enters agentic AI race

Informatica employs two strategies relative to generative AI (GenAI): Informatica for GenAI, in which customers use IDMC’s data management capabilities to enable enterprises’ GenAI use cases; and GenAI from Informatica, where customers leverage Informatica’s GenAI offerings. Those products include CLAIRE Copilot, which entered general availability at the event, and CLAIRE GPT, which is used by over 550 clients to streamline tasks within IDMC such as pulling datasets and interacting with catalogs. On the annual conference’s 25th anniversary, Informatica formally entered the agentic AI space with a similar approach, giving customers the ability to consume AI agents within IDMC for more autonomous data management and a tool for letting customers build, manage and orchestrate their own AI agents.

  • CLAIRE Agents: As part of the GenAI from Informatica strategy, Informatica introduced eight new agents to support tasks across the data life cycle. The agents, which are expected to begin preview in 2H25, are Data Quality, Data Discovery, Data Lineage, Data Ingestion, ETL [Extract, Transform Load], Modernization, Product Experience and Data Exploration. Architecturally speaking, these agents will round out the IDMC platform, sitting above the metadata system of intelligence, with CLAIRE Copilot and GPT acting as user experience (UX) overlays, where customers can interact with these agents.

Nearly every facet of IT has emerged as a prominent use case for GenAI, including data management, and customers are looking for ways to streamline more system-level tasks. Provided customers are prepared to move from manual — or even predictive and conversational AI engineering — to agentic AI, these new data management agents can help absorb a lot of back-end data management tasks, including developing the data pipelines and reducing some of the burden on the user, whose primary focus now becomes managing the agents.

 

  • AI Agent Engineering: In agentic AI, the hyperscalers and SaaS vendors are racing to position as the AI control tower. As more vendors push into the PaaS space and the resulting AI agents convolute the applications layer, the question becomes, “Which set of vendors are positioned to abstract that complexity in a governed way?” At the event, Informatica entered the space with the introduction of AI Agent Engineering, a new tool to help users build their own agents using the popular low-code/no-code drag-and-drop experience. Additionally, AI Agent Hub, which acts as a marketplace within AI Agent Engineering, helps users find, manage and connect these agents, including not just Informatica’s CLAIRE agents but also the tools customers are already using to build agents, such as Amazon Bedrock, Azure OpenAI, Google Vertex and Salesforce’s Agentforce. When it comes to building and orchestrating AI agents, customers have a range of options, but one of the compelling things about Informatica entering this space is its ability to provide the federated governance and access controls around these agents without disrupting existing workflows. Governance remains one of the leading barriers to GenAI adoption, and while some overlap will always exist between the hyperscalers and data ISVs, the hyperscalers recognize Informatica’s reputation for helping customers build trust in their data and ability to apply that trust in a vendor-agnostic way.

 

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Ecosystem developments

As we often discuss, Informatica maintains a high degree of neutrality and can effectively work across a range of technology partners without introducing significant overlap. Maintaining its commitment to working within the technology ecosystem, Informatica announced new product integrations across its technology partners, including the following highlights.

  • Microsoft: Microsoft’s play at the PaaS layer (e.g., Synapse, Power Platform) and ability to extend the Dynamics 365 data model to enable Customer 360 analytics make it an invaluable, somewhat unique partner to Informatica. Reaffirming Informatica’s commitment to Microsoft, CLAIRE Copilot was built using the Azure OpenAI Service. The launch of Microsoft Fabric last year seemed to mark a turning point in the alliance, as Informatica was granted status as an early design partner for Fabric, which has amassed 21,000 paid customers in the span of 18 months. Essentially, this status allows Informatica to make its Data Quality tool available as a native service, so customers can profile and assess data using Informatica as it gets ingested into Microsoft Fabric via the OneLake repository in real time. At the event, Informatica made Data Quality available (in public preview) as its own Fabric application. In addition, as part of its commitment to staying relevant within the Microsoft Fabric ecosystem, Informatica will start supporting Apache Iceberg in Microsoft Fabric, which is important as Microsoft looks to cement its commitment to open standards. These developments come as part of a new strategic agreement between Informatica and Microsoft, which implies not just a focus on R&D but also investment in the joint go-to-market approach. Having Informatica exist as a first-class citizen within the Microsoft stack could make the case for customers to explore other components of IDMC, creating deeper synergies with services partners like KPMG that use Informatica and Microsoft Fabric, both internally and externally for data modernization and transformation.
  • Salesforce*: Though Informatica and Salesforce technically had a preexisting alliance, the partnership was formalized at Informatica World 2025 with the announcement that IDMC will be integrated with Salesforce’s Agentforce. Specifically, Informatica plans to deliver MDM SaaS with Agentforce, effectively putting the 360-degree wrapper around agents that customers build in Salesforce’s platform. As previously mentioned, customers will also be able consume Agentforce via Informatica AI Agent Engineering upon availability later this year. Salesforce sees Informatica as a key player in the market and is looking to strengthen its play in data management and governance in accordance with Agentforce, so this partnership is a win for Salesforce. In turn, Informatica seems to recognize the role Agentforce will play in the AI ecosystem for sales and service use cases, and it will be interesting to see how this partnership progresses and if Salesforce ends up joining Informatica’s seven other, more established technology partners.

On the services side, Informatica continues to cement its value across nine core global systems integrator (GSI) partners, which collectively staff 30,000 Informatica professionals. In 2024, Informatica earned 15,000 certifications, up over 20% year-to-year. Vendor sentiment and our own conversations with enterprise IT decision makers suggest that for AI to effectively scale, data needs to be in the cloud. As such, modernization will continue to be a big focus for Informatica and its partners through 2025. This includes AI-powered modernization and potentially using the new CLAIRE Agents, specifically Modernization, to help migrate on-premises data to IDMC. When it comes to agentic AI, Informatica’s new innovations should open new doors for services partners to not only modernize data management tasks ahead of GenAI deployments but also help clients create new custom agents (using AI Agent Engineering), including those tailored to certain industries, and make them relevant within existing workflows.

 

Between the technology partners and GSIs, Informatica works with a robust ecosystem of partners in a triparty approach, where resources from a hyperscaler, GSI and Informatica are brought together to help customers modernize their data faster and, by default, hasten AI’s time to value. When we survey and speak to alliance decision makers at IT services firms, data management comes up as one of the top areas for partner-led growth, signaling to the ecosystem that they will continue to invest in resources to guide conversations with customers with the technology maturity to address the data foundations ahead of GenAI.

Conclusion

Agentic AI has a lot of promise but also some challenges. The proliferation of AI agents will create more best-of-breed complexity — which we know customers are trying to move away from — and heighten concerns around data privacy and governance. Informatica’s move into the agentic AI space with both CLAIRE Agents and AI Agent Engineering is certainly in step with the market; we all know AI agents do not exist in silos, so Informatica’s ability to work within its ecosystem of tech partners and connect agents in a vendor-neutral way is particularly compelling. Meanwhile, Informatica’s robust engineering relationships with the hyperscalers, as evidenced by Informatica’s Data Quality integration with Microsoft Fabric, will continue to elevate its standing with the big GSIs and foster a compelling triparty alliance approach focused on helping customers get their data ready for AI.

*After Informatica World, on May 27, Informatica entered into an agreement to be acquired by Salesforce. Informatica will continue to operate as a stand-alone entity until the acquisition closes, likely in Salesforce’s FY27. Please see TBR’s Salesforce coverage for further insights.