Can your alliance partners tell your clients what makes you special? Do your alliance partners’ sales teams know what value you bring to the ecosystem? Are you sure you placed your strategic ecosystem bets on alliance partners that are well positioned for the next growth wave? Are your competitors gaining ground with your common alliance partners through sales programs, go-to-market motions and training that you are not doing?
 
Vendor consolidation and enterprise optimization of existing digital stacks have compelled IT services companies and consultancies as well as their ecosystem partners to think strategically about who to partner with and how to secure and expand their position within the ecosystem. As a result, aligning business priorities with alliance partners will allow IT services companies and consultancies to develop a more empathetic approach to technology-fatigued buyers. Additionally, understanding pricing and commercial structures backed by common knowledge management programs will elevate the value of joint services and appeal to enterprise buyers’ appreciation of a separation of labor, supported by greater transparency and accountability.

What is ecosystem intelligence for the B2B industry?

Ecosystem intelligence provides the framework and insights necessary for all parties involved to deliver value to the end customer. Establishing common governance models backed by self-accountability metrics helps guide vendors in executing against universally agreed-upon business objectives, thus maintaining ecosystem trust.
 
Ecosystem go-to-market strategies, which involve multiple vendors collaborating to deliver complex and comprehensive solutions, now drive more than half of total IT investment, and, critically, this revenue generated through ecosystem partnerships has been growing faster than the overall market, turning ecosystem intelligence-enabled insights into invaluable pillars supporting the next wave of vendors’ business model evolutions.
 
As IT budgets grow, a greater percentage of new funding will flow to companies collaborating to deliver value, in part because the complexity of solutions required by end customers necessitates a multifaceted approach involving various layers of infrastructure, software, services and networking.

Ecosystem intelligence will become a strategic advantage for B2B

In the last few years, ecosystem intelligence has eclipsed competitive intelligence as the use case most frequently leveraging TBR’s IT services, professional services, and digital transformation data and analysis, often in an effort to answer the questions above. That shift reflects three broader trends.

• First, enterprise buyers want to deal with fewer technology vendors, increase transparency around their IT spend and realize faster returns on technology investments.
• Second, portfolio and capability expansion — PwC has expanded into managed services, HCLTech into software, Amazon Web Services into professional services and Lenovo into consulting — has created a more fluid ecosystem, where partnering with competitors and competing against alliance partners has become the norm.
• Third, and perhaps seeming to run as a crosscurrent to the other two trends, the best performing companies have chosen to play primarily to their strengths, staying in their lane and partnering better, rather than building out capabilities and scale.

In 2025, IT services companies and consultancies will refine their alliances, winnowing lists of 100-plus technology partners to the handful that drive more than 90% of their business, articulate a clear joint value proposition, and align at both the leadership and sales force levels. Technology-agnostic was always a bit of a fiction and in the coming years will become a description of the past and not a strategy going forward. To make all that happen, IT services companies and consultancies will invest in ecosystem intelligence and elevate alliance management within their organizations.

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Infosys’ proven engagement and delivery strategies continue to pay off, evidenced by accelerated sales during 4Q24 and an increase in FY25 revenue guidance for the third consecutive quarter. The company’s approach of underpromising and overdelivering, rooted in the company’s humble culture, allows it maintain trust with ecosystem stakeholders while it continues to expand and enhance its portfolio in emerging areas such as agentic AI and industry-aligned small language models (SLMs).
 
Infosys remains well positioned to surpass India-centric peer Cognizant for the No. 2 spot in revenue size, despite the inorganic boost of over $800 million that Cognizant will receive over the next year from its purchase of Belcan. Its’ relentless execution, backed by investments in talent development and partner-enabled solutions, will continue to be the company’s key to success as it gradually increases its share of value-based selling efforts, which are also bolstering its profitability, making otherwise impatient shareholders happy.

Scaling GenAI use cases through the development of prebuilt, industry-specific SLMs, and relying on highly skilled talent and resource management

As noted in TBR’s 4Q24 Infosys Earnings Response report, developing a client-ready AI-first portfolio is not a strategy unique to Infosys, but keeping pace with the rapidly evolving generative AI (GenAI) market highlights the company’s appetite for innovation and helps it strengthen stakeholder trust. Over the past 24 months, a large portion of vendor-client discussions focused on experimenting with developing and running large language models (LLMs), often fed with either public or nonessential data. Growing adoption of the technology has introduced the need for developing SLMs that are either function or industry specific.
 
While cloud-deployed models have far fewer resource constraints, there are still significant drawbacks with an LLM approach. Additionally, LLMs’ massive size leads to downsides in efficiency, cost and customizability, presenting serious hurdles over the long term, especially as contextualization improves. Moreover, when looking at specific use cases, SLMs built to perform particular tasks can outperform broader LLMs. These SLMs can be pretrained on smaller datasets, enabling developers to be more selective with training data and opt only for high-quality data sources pertinent to the desired use case.
 

Ecosystem partners remain a critical component of Infosys’ GenAI strategy

Infosys and NVIDIA co-launched three NVIDIA-enabled GenAI solutions, which, according to Infosys’ press release, use “NVIDIA NIM inference microservices, NVIDIA NeMo Retriever embedding models, and NeMo Guardrails to customize and deploy generative AI telco domain-specific LLM models.” Infosys also launched NVIDIA-enabled SLMs for Infosys Topaz BankingSLM and Infosys Topaz ITOpsSLM, targeting clients through core industry and horizontal offerings and allowing them to use their own data on top of the prebuilt SLMs.
 
Further, Infosys launched the Finacle Data and AI Suite of solutions to support banking clients seeking to enhance IT systems and customer experience using AI. The solutions include Finacle Data Platform, Finacle AI Platform and Finacle Generative AI Offerings. We see these capabilities as a prerequisite to enhance the core Infosys Finacle platform and enable Infosys to remain a formidable competitor in the banking space.
 
Despite the modularity of these offerings, we do not expect the company to change its commercial model and continue to use the suite of offerings to drive services opportunities. Infosys’ SLM portfolio expansion strategy closely mimics the company’s build-out of industry cloud offerings that address client pain points with prebuilt models for specific functions. The difference is the added complexity around building and managing the prebuilt SLM models with their massive number of parameters.
 
Developing and supporting these prebuilt models will require the right-skilled bench and, more importantly, retention programs enabled by unique career paths for programmers who are involved in such tasks. Infosys’ Power Programmers group of engineers consists of highly skilled professionals who are responsible for developing products and ensuring that the intellectual property they create and use meets the cost-saving requirements Infosys pitches to clients. The Power Programmers group is much leaner than the traditional software developers pyramid and resembles the business models that many vendors, including Infosys, may aspire to implement in the future.

Enhancing its chip-to-cloud strategy via acquisitions can bolster cloud performance, but only if Infosys accounts for and aligns with OEM and cloud vendor priorities, including edge and 5G

With its cloud business reaching 30% of Infosys’ total sales and growing 25.1% year-to-year in 4Q24, Infosys continues to invest across its portfolio to expand its addressable market opportunities. For example, Infosys Engineering Services remains among the fastest-growing units within Infosys as the company strives to get closer to product development and minimize GenAI’s disruption of its content distribution and support position.
 
Since the 2020 purchase of Kaleidoscope, which provided a much-needed boost for Infosys to infuse new skills and the IP needed to appeal to the OT buyer, Infosys has enhanced its value proposition to also meet GenAI-infused demand. Infosys’ investments in recent acquisitions including in-tech and InSemi have expanded the company’s addressable market opportunities around product engineering and silicon design services, further strengthening its chip-to-cloud strategy.
 
We do not expect growth of Infosys’ cloud business, Infosys Cobalt, to slow down anytime soon, given the company’s market position for infrastructure migration and managed services as well as its well-run partner strategy with hyperscalers. Adding semiconductor design services bolsters that value proposition as buyers consider whether to use price-attractive CPUs or premium-priced GPU data centers. The latter currently dominates the marketplace, and we expect that trend will not change for at least the next 18 to 24 months. But having semiconductor engineers on its bench can help Infosys start supporting CPU-run models, appealing to more price-sensitive clients.
 
Additionally, expanding its product engineering services also enhances Infosys’ edge and 5G value proposition, which we believe are two of the next frontiers for AI-enabled growth.

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What are AI agents?

Over the past several quarters, OEMs have focused on incorporating local AI-powered features into their new PC releases, with initial neural processing unit (NPU)-enabled use cases leveraging AI to further enhance collaboration experiences and extend battery life. However, AI agents take the NPU’s functionality a step further, combining the capabilities of large language models (LLMs) with other resources to partially or fully automate a wide range of tasks, including responding to emails, booking hotel stays, or opening and closing IT help desk tickets.
 

LLM-based AI systems have traditionally been programmatic in nature, making them well suited for accomplishing a relatively narrow range of tasks quickly but with a varying degree of accuracy depending on the user’s specific query and how closely it aligns with how the LLM was trained. However, as AI has matured, an increasing number of organizations have invested in the development of compound AI systems, making way for the rise of agentic AI. Compound AI systems, which include AI agents, combine AI models with additional resources such as adjacent AI models, external data sets, web searching capabilities and other APIs to address some of the limitations of programmatic AI systems. This allows AI agents to carry out more complex tasks with a higher degree of accuracy compared to traditional programmatic AI systems, like ChatGPT.
 

As a general rule, as AI systems become more compound, speed is sacrificed. However, the compound nature of AI agents is what allows them to act on behalf of the user — a key differentiator and the primary value proposition behind agentic AI. Without any human intervention, an AI agent can create several subtasks where it brings in and analyzes data from several sources before determining the next step in the process.
 

It is worth noting that while AI PC agents typically leverage the NPU, most AI PC agents do not operate completely locally, leveraging cloud computing resources.

Proprietary AI agents will become increasingly prevalent in the AI PC space over the next several quarters

Maximizing AI PC appeal through software integration

For OEMs to attract customers to their AI PC offerings, the devices must have software that leverages the power of the NPU in a way that improves performance, productivity and/or security.
 

One of the most important software solutions underpinning the AI PC space is Microsoft Copilot+, which offers a series of generative AI (GenAI) features and experiences for Windows 11 machines leveraging several of Microsoft’s small language models. However, not all Copilot+ functions are run natively on the device, with certain queries going to the cloud, which may lead to security and privacy concerns for some users.
 

To differentiate its AI PC portfolio and bring more AI tasks onto the device itself, Lenovo has developed an agent known as AI Now, which has capabilities such as document management, meeting summarization, device control and content generation. Leveraging a local large language model built with significant collaboration from Meta, AI Now offers enhanced data privacy and enables GenAI features without internet connectivity by allowing users to interact in real time with the device’s personal knowledge base, rather than relying on cloud computing.
 

With the release of its first set of Next-Gen AI PCs in May, HP Inc. announced a similar application to Lenovo’s AI Now, named HP AI Companion. Available for download on any HP AI PC with a 40-60 TOPS (trillion operations per second) NPU, the application leverages OpenAI’s GPT-4 model to bring AI tasks such as performance optimization, document summarization and content generation onto the device.
 

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AI agents as differentiators in the AI PC market

We expect to see these offerings become increasingly central to the AI PC space over the next several months, with vendors tapping into buyers’ concerns about data privacy related to cloud computing in order to promote their own proprietary AI agents. Vendors will continue to position these agents as complements to Microsoft’s Copilot+, rather than replacements, as they will shy away both from attempting to compete with Copilot+ and other cloud-based offerings and from alienating Microsoft, a vital partner when it comes to AI.
 

Overall, these agents are currently being more heavily marketed toward commercial customers, as that subsegment of the market is generally more strategically valuable to OEMs because of commercial PCs’ higher average revenue per unit (ARPU) and attach rates for peripherals and services.
 

However, TBR expects these agents to gain traction in the consumer AI PC space as well, especially as they include features useful to all users, such as performance optimization and increased security, as well as those designed specifically for enhancing workplace productivity. Ultimately, TBR believes the extent to which vendors can educate users on when and how to use specific AI tools will determine the level of adoption of individual AI tools. The availability of multiple tools on the PC is likely to lead to confusion.
 

Similar to AI PC OEMs, smartphone vendors are becoming increasingly invested in baking AI into their devices to enhance the devices’ value and accelerate the refresh cycle. Many of these features revolve around photo and video editing software, such as Google’s Magic Editor and Photo Unblur, as well as notification and document summarization. Personal agents that allow the user to navigate their device through voice commands and natural-language text such as Apple’s Siri are also popular.
 

Smartphone vendors are also combining on-device and cloud-based AI processing when building out the functionality of these devices, with the recently released Apple Intelligence platform being the most prominent example. When possible, queries are processed on the device through the NPU built into Apple’s proprietary chips, while queries that are more complex are sent to the cloud through the company’s Private Cloud Compute system. TBR expects that this hybrid model will increase in popularity as devices vendors balance greater AI functionality with data privacy and security.

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Enterprise Migrations and Large-Scale M&A Are Influencing the IaaS and PaaS Market

Current State of the Infrastructure as a Service Market

Among benchmarked Infrastructure as a Service (IaaS) vendors, average revenue growth increased 21% year-to-year in 2Q24, marking the fourth consecutive quarter of acceleration. There are two primary factors at play: enterprise IT modernization activity, which is much stronger now than it was this time last year, and generative AI (GenAI).

Top hyperscalers Amazon Web Services (AWS) and Microsoft are capturing legacy Oracle and SAP workloads as customers continue to migrate to the cloud to not only outsource their IT operations but also drive lasting business value. Though the geopolitical outlook is increasingly uncertain, we expect customers will continue to prioritize more traditional “lift and shift” migrations, and steps vendors are taking to deliver more integrated solutions could help. For instance, by the end of 2024, Oracle’s database services will officially be available on AWS, Microsoft Azure and Google Cloud Platform (GCP), which could be a big growth tailwind for these vendors. For context, converting Oracle’s remaining database support install base to the cloud represents a roughly $18 billion incremental revenue opportunity for these hyperscalers, including Oracle itself.

Regarding GenAI, investments in AI compute and new data centers are translating into top-line growth. Most vendors report they have multibillion-dollar AI and GenAI businesses, though this is minuscule compared to the tens of billions of dollars these vendors are investing. Vendor capex guidance for 2025 suggests that the level of investment will only increase, although we do expect this is when GenAI fatigue will hit and many customers may begin to re-evaluate their IT priorities.

Current State of the Platform as a Service Market

The Platform as a Service (PaaS) market is similarly growing behind GenAI adoption, as many customers, who still have a fear-of-missing-out mentality, are spinning up new workloads natively in the cloud with services like Amazon Bedrock, Microsoft Azure OpenAI and Google Vertex AI.

The PaaS market will similarly be impacted by GenAI disillusionment, but we believe this trend will also cause customers to focus more on the data layer, prompting them to take a second look at strategies around governance, data quality and integration for long-term AI success.

Another key trend driving PaaS market growth is M&A. IT leaders are acquiring to enter new markets and access IP they can ultimately sell as part of an entire end-to-end suite of offerings, as customers continue to crave more simplified, integrated solutions. By far the best example is Cisco’s acquisition of Splunk, which added $960 million to Cisco’s top line in 2Q24 and is quickly making Cisco a rising force in PaaS with its observability portfolio. IBM’s proposed acquisition of HashiCorp, which is expected to close by the end of this year, would be another transformative deal that would put IBM squarely into the Terraform space and deliver synergies with Red Hat that will be attractive to unsatisfied VMware customers.

Cloud Infrastructure and Platform Revenue Leaders

Steps Microsoft Is Taking to Elevate Its Data Portfolio as Part of the Broader AI Strategy Will Fuel Azure Growth and Marginalize AWS’ Segment Lead

Amazon Web Services: AWS continues to ride a wave of accelerating revenue growth and will cross the $100 billion threshold in annual sales by the end of 2024. Making it as easy as possible for customers to build GenAI applications in the cloud with Amazon Bedrock’s unified API, and adjacent developer tools like App Studio and SageMaker, is integral to AWS’ strategy and ability to drive IaaS growth. At this point, there are probably well over 10,000 customers using Amazon Bedrock for a range of generic use cases like text generation and virtual assistants.

Microsoft: Though AI infrastructure constraints caused Azure revenue to dip 2 percentage points to 29% in 2Q24, Azure is growing faster than AWS despite becoming larger and closing in on AWS’ revenue volume. Steps Microsoft is taking to advance its PaaS strategy through solutions like Fabric will continue to fuel Azure growth and help protect Microsoft’s lead in the AI space. For context, the number of Azure AI customers also using Microsoft’s data and analytics tools grew nearly 50% year-to-year in 2Q24, while Microsoft Fabric has now reached 14,000 paid customers.

Google Cloud: Recognizing that GenAI leadership stems from the infrastructure foundation, Google Cloud has been heavily building out its infrastructure portfolio by supporting not only NVIDIA’s Blackwell chips, which are expected to be available on GCP in early 2025, but also its own hardware. This includes Axion, Google Cloud’s first Arm-based processor that will support a range of GCP services, including data services key for GenAI like Dataproc and Dataflow. In 2Q24 Google Cloud also announced its sixth-generation TPU (tensor processing unit).

Technology continues to threaten the nature of consulting engagements, requiring consultancies to showcase value and deliver on outcomes. Greater investment in talent frameworks, structure and skill will equip staff to lead client discussions and effectively leverage technology to assist workflows. Partnerships remain a core piece of the technology integration, bringing in new expertise and go-to-market opportunities that enable consultancies to meet a wider variety of client needs. Client retention remains a priority across consultancies but will require the firms to effectively deliver value through services.

Consultancies Will Experience a Shift in Traditional Consulting Services as Technology Is Further Embedded in the Market

Consultancies will manage talent more closely to reach higher quality standards

Consultancies refreshed their network of centers, including new operations with partners as well as those designed for internal use. As the consultancies look to bring both talent and clients in-office to work more collaboratively, improve communication and enhance the culture, the new centers serve as a path to facilitate interactions and engagement.

In a joint investment, Microsoft and KPMG opened an Operational Risk Skills Development Center in Quebec, followed by a national rollout of the training center supporting Canadian clients’ efforts to take advantage of generative AI (GenAI) responsibly. KPMG also recently announced the opening of a European Union (EU) AI Hub in Ireland. The AI hub is located inside one of the firm’s Innovation Hubs and is set to house 200 employees with skills in risk, regulatory services and cybersecurity. The AI hub will leverage KPMG’s Trusted AI framework and use technology from Microsoft and Cranium (an AI security startup that was spun out from KPMG Studio in 2023).

IBM Consulting has poured investment dollars into training and building a network of hybrid cloud and AI talent globally, including IBM’s launch of an AI Center of Excellence in Abu Dhabi, United Arab Emirates, in January 2023 in partnership with the Mohamed bin Zayed University of Artificial Intelligence.
 

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With a return to in-person discussions and conversations, PwC strengthened its center network to emphasize technology solutions. For example, PwC established a Cyber Managed Services Center in Cork, Ireland; added a GenAI business center to its Luxembourg experience center; and opened an AI excellence center in Saudia Arabia.

Accenture announced the openings of GenAI studios in Chicago, Houston, New York, San Francisco, Toronto and Washington, D.C. Accenture Federal Services opened a Cybersecurity Center of Excellence (CoE) in partnership with Google in Washington, D.C., highlighting Accenture’s balanced approach to pragmatism and innovation executed through a well-oiled command-and-control culture.

Capgemini announced it had signed a strategic agreement with Amazon Web Services (AWS) to accelerate the adoption of GenAI solutions across organizations. The agreement focuses on helping clients gain knowledge around and realize the value of GenAI in business processes. Together, the two companies will move clients from pilots to production by leveraging Capgemini’s network of AWS CoEs. The partners will fast-track the deployment of industry-specific solutions, assets and accelerators, and create functional use cases through Amazon Bedrock.

New leadership will facilitate the evolution of traditional consulting services

With the appointment in July of a new PwC global chairman, Mohamed Kande, who was formerly the company’s Global Advisory and U.S. Consulting Solutions leader, TBR expects sustained and possibly increased investment in advisory and consulting capabilities across the global network, even as the consulting market overall continues to stagnate. Combined with the announcement of new leadership teams in a number of major territories, including the U.S. and the U.K., a new PwC strategy — to update the firm’s 3-year-old The New Equation strategy — will likely re-emphasize the PwC brand and lean into the firm’s technology expertise.

Janet Truncale became EY global chair and CEO on July 1, and TBR expects her top priority will be strengthening the company’s talent base, in part by continuing the EY Badges program and leading with its “better working world” strategy.

In February McKinsey & Co. partners re-elected Bob Sternfels as the firm’s global managing partner after three voting rounds. Sternfels has provided some stability to McKinsey in the last few years and will likely continue prioritizing quality over quantity, slowing its hiring efforts and fine-tuning the firm’s existing expertise to meet new demands in a GenAI age.

Across all three firms, in TBR’s view, new leadership (or consistent leadership, in McKinsey’s case) has been welcomed at the senior level and seen as necessary in light of post-pandemic changes to the consulting and professional services market.

In APAC, management consultancies have seen some leadership changes as well. EY Australia recently announced four new appointments: the leads for consulting in Australia; supply chain for Oceania; Asia Pacific financial services; and private equity consulting. Notably, only two of the people appointed to those four positions have been with EY for more than a few years.

In May EY Australia announced Katherine Boiciuc as the firm’s new chief technology officer. Earlier in the year, Boston Consulting Group (BCG) in Australia and New Zealand announced a number of senior-level promotions, including Stephen Hosie (healthcare, private equity and public sector), Whitney Merchant (gas, including liquefied natural gas), Lachlan McDonald (mining, oil & gas, manufacturing, and construction), and James Argent (managing director and partner). BCG also appointed Kelly Newton to serve as comanaging partner in New Zealand. Rounding out the region, KPMG appointed David Rowlands as global head of AI, in addition to the promotion of Tim Robinson to lead the firm’s technology consulting practice in Australia.

Partnerships require additional differentiation to drive value for clients

Differentiation will be key for consultancies to prove value tied to partner technologies including AI, GenAI, digital and cloud. Leaning on centers and talent to communicate the value and possibility of their services will provide consultancies with a slight advantage, but the firms will also need to partner around core AI and GenAI capabilities in addition to offering implementation and management services.

Post-pandemic management consultancies, particularly the Big Four, have expanded the scope and composition of their partner ecosystem, focusing primarily on key technology vendors including Google Cloud, AWS, SAP and Microsoft, as well as niche providers. Consultancies have trained their own staff around partners’ capabilities, as well as accelerated the opening of dedicated centers to facilitate adoption and transformation rooted within different solutions.

• KPMG US runs a global Oracle operating model backed by a Global Oracle Center of Excellence, and the firm recently launched a Global Oracle EMEA Hub to capitalize on growth in that market. KPMG Delivery Network hubs, located across LATAM, EMEA and APAC, are supported by over 8,500 Oracle consultants, including more than 700 Oracle Cloud Infrastructure-certified consultants. KPMG also opened a CoE with Google Cloud to combine Google Cloud’s AI technologies with KPMG’s industry and functional knowledge.
• PwC also partnered with Google Cloud, but through a different avenue, focusing on tax compliance and analytics. The partnership also dovetails with PwC’s efforts to complement its existing strengths around tax, workforce transformation, customer experience and HR processes. In addition, PwC teamed with Microsoft to open an AI CoE in Saudi Arabia with the goal of developing AI skills and supporting recruitment. The center will host a recruiting program every two months, bringing in new talent to support portfolio expansion.

With partnerships among the consultancies and vendors pursuing similar goals and initiatives, differentiation from the consultancies will be key to their success in scaling new technology and remaining go-to partners for their clients. The CoEs and certified talent provide an avenue for consultancies to immerse clients within the culture and company values in addition to exposure to the services and solutions.