B2B Strategic Advantage: Ecosystem Intelligence

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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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KPMG Shifts Focus to Legal Services and AI-driven Strategy Consulting 

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KPMG is leaning toward legal services and AI-infused strategy consulting offerings to bolster sales as the firm navigates choppy market conditions within core deal advisory

Earlier in January news reports surfaced that a subsidiary of KPMG, KPMG Law US, had applied to operate in Arizona under a state program allowing nonlawyers to operate law firms and provide legal services in the state. This aligns with our Fall 2024 Management Consulting Benchmark Vendor Profile: KPMG, in which we discussed this topic.
 
KPMG’s revenue growth decelerated from 0.7% year-to-year in 1H23 to -0.6% year-to-year in 1H24 as the firm continued to face pressure in core markets such as deal advisory despite the uptick in signings — a trend we expect to continue into 2025 as we estimate management consulting sales to stay flat on an annual basis. Over the last six months, KPMG signed M&A advisory and restructuring deals, including those with Germany-based air-taxi manufacturer Lilium; Spain-based Santander Consumer Finance; and Romania-based retailer La Cocos. As KPMG seeks to diversify its portfolio and revenue opportunities, recent investments across its portfolio related to legal services suggest that demand across regions is choppy and that KPMG will be reviewing its positioning, one member firm at a time.
 
For example, in Australia, KPMG restructured its stand-alone legal services practice, folding KPMG Law’s Tax Controversy & Disputes practice under KPMG’s tax business. At the same time, in the U.S. KPMG is looking to invest heavily in AI to bolster its legal services offerings, creating a conduit for consulting business. Meanwhile, KPMG partnered with ContractPodAI to bolster its legal AI and contract lifecycle management capabilities as the firm seeks to expand its legal managed services opportunities targeting clients in the U.S., U.K. and Germany. We believe KPMG’s push in the legal services space can also help the firm gain access to the talent needed to enhance its governance, risk and compliance (GRC) value proposition, especially as more general counsels are getting involved in GenAI solution development.
 
Outside legal services and M&A advisory, we expect KPMG’s efforts to bolster its management consulting revenues will come from its investments in technology-centric capabilities, with AI and GenAI among the predominant topics impacting the firm’s strategy consulting sales. We believe the KPMG Lighthouse team will continue to provide a critical link enabling the firm to elevate conversations beyond the typical art-of-the-possible discussions and tying them to business outcomes with tangible solutions. While embedding AI and data science is not unique to KPMG, the firm has an opportunity to elevate the value of such offerings as the single most important technology the firm stands behind, especially as many of its competitors stretch their portfolios and messaging across multiple domains. While we understand this can be a tricky message to execute against, demonstrating depth and specialization will likely trump generalization moving forward as GenAI levels the knowledge field, helping KPMG stand out.
 
Legal services would only be part of KPMG’s story going forward, as we also discussed in the Fall 2024 Management Consulting Benchmark Vendor Profile: KPMG.
 

GenAI can help KPMG enhance its industry consulting expertise, provided the firm leans on partners to do the tech part and focuses on its business pain points

Healthcare was KPMG’s fastest-growing industry vertical at 6.4% year-to-year in 1H24, according to TBR estimates. As an outlier for KPMG’s growth, the vertical benefited from industry clients seeking to digitize health systems and improve the patient experience. KPMG is not alone in capturing high-growth opportunities in the healthcare sector as rivals Deloitte and Accenture have also captured robust sales expansions in the industry with both competitors enhancing value propositions through acquisitions including Gryphonic Scientific (biosafety and biosecurity) and Cognosante (federal health).
 
To counter competitive threats, KPMG leaned on organic means, announcing the opening of a Global Center of Excellence for healthcare based in Bermuda. While the center will bring in professionals from the Caribbean, Bermuda, the Crown Dependencies, and Mediterranean islands, it will also have access to KPMG’s broader network of 5,000 professionals across the firm’s service lines within the healthcare vertical, including 200 clinicians.
 
Outside healthcare, KPMG continued to rely on its industry consulting know-how to enhance portfolio capabilities around partner-enabled industry accelerators such as with Workday for Retail and Hospitality; with Meta using Meta’s open-source large language model (LLM) Llama to build solutions for internal audit and commercial loan processing, paving the way for opportunities within the financial services vertical; and with Salesforce around the use of Customer 360 solutions for healthcare, among other verticals.
 
TBR views these as important steps that are enabling KPMG to better compete with Big Four rival Deloitte, which has set its Industry Advantage program to drive long-term managed services and feed the Operate part of Deloitte’s business. In a recent conversation with KPMG’s Managed Services leadership, TBR got a chance to hear how KPMG is able to use the KPMG Powered part of its four-part framework — Connected, Powered, Trusted and Elevate — to drive conversations around industry pain points in verticals such as insurance and financial services that have helped generate managed services engagements. Additionally, leaning on strategic growth and delivery partners has helped KPMG demonstrate depth rather deviate from its core capabilities.
 
We expect KPMG’s next growth frontier to come from the firm’s ability to codevelop industry-specific small language models as clients look to take advantage of the power of GenAI without compromising security and privacy by using LLMs based on public data.
 
Graph: 2H24 Est. KPMG Management Consulting Revenue and Growth

The Stargate Project: A Manhattan Project for the AI era

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President Trump Announces Joint Venture with OpenAI, SoftBank and Oracle to Build $500B Worth of AI-dedicated Data Centers

On his second day in office, President Trump approved funding for the Stargate Project, a joint venture with OpenAI, SoftBank and Oracle to initially build a $100 billion data center in Texas. Over the next four years, the project aims to expand into additional large-scale data centers, with a total of $500 billion in funding, making it the largest centralized data center investment in history. The funding includes significant financial backing from the U.S. government  with contributions from SoftBank, a firm known for its long-term investment strategies. OpenAI, SoftBank, Oracle and MGX will be the initial equity investors, while Arm, Microsoft, NVIDIA and OpenAI have been named as technology partners and will have some involvement in Stargate.
 
The $500 billion expenditure is unprecedented. Most Tier 1 hyperscaler data center projects are valued in the single-digit billions, making Stargate’s Phase 1 cost more than 50 times higher than its closest comparable. This venture will rely heavily on U.S. government funding, as SoftBank’s Vision Fund, which manages assets worth less than $200 billion, cannot shoulder the full burden. This positions Stargate as a “Manhattan Project” for the AI era, as it represents one of the largest technological undertakings in modern times. The project is poised to reshape global dynamics if it can navigate the significant hurdles that lay ahead. Regardless, OpenAI, equipped with the world’s largest AI cluster, will pursue its goal of artificial general intelligence (AGI) while enjoying unparalleled access to the compute infrastructure needed to push parameter counts higher.

 

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What Does This Mean for Cloud Vendors and Model Developers?

OpenAI Gains a Powerful Competitive Advantage Over Other Model Developers

Being the largest single technology endeavor in recent history, the Stargate Project will have a notable influence on the budding AI market. In TBR’s opinion, no company stands to benefit more than OpenAI. The company’s access to dedicated compute resources will be unmatched in the model developer industry, enabling OpenAI to push parameter counts further and faster compared to peers and supporting the company’s objective of differentiating based on large language model (LLM) performance. OpenAI’s ultimate goal is to reach AGI, which the company defines as “highly autonomous systems that outperform humans at most economically valuable work.” While estimates about when OpenAI will reach this goal vary widely, the Stargate Project fulfills a critical requirement in the pursuit of AGI, making OpenAI a top contender to reach AGI before other firms.

Another Win for OCI

Oracle’s reentry into the already highly saturated IaaS market with Gen2 OCI (Oracle Cloud Infrastructure) has been widely successful. Though initially designed to drive stickiness with enterprises already rooted in the Oracle ecosystem, OCI appears to be gaining traction among digital natives and ISVs for AI use cases. In many ways, this is a testament to Oracle’s decision to cozy up to NVIDIA for GPUs early on in the emergence of generative AI (GenAI) by hosting the company’s DGX software in its data centers, helping NVIDIA position as a software company and avoid becoming another piece of commoditized hardware locked into the hyperscalers’ stacks. Now, riding a wave of over $70 billion in cloud backlog, OCI is Oracle’s fastest-growing business and will soon become its largest.
 
Aside from the GPUs, the other factor fueling OCI growth and granting Oracle its status as one of the largest data center operators in the world is the company’s ability to bring new data centers online extremely quickly. This is because Oracle has generally adopted a strategy of building more but smaller-scale (approximately 145-kW) data centers, with a focus on ensuring that, outside of scale, all Oracle data centers are identical.
 
This scale can vary significantly, though, and with the current AI wave, we have seen Oracle prioritize larger data centers, some spanning 800MWs for AI customers, including OpenAI. There was perhaps no greater testimonial for OCI as a cloud credible enough for AI applications than OpenAI’s mid-2024 decision to leverage OCI for AI training via Azure.
 
To be fair, the existing Azure-Oracle relationship influenced that decision, but OpenAI has made it clear that the company not only needs IaaS services to push the boundaries of its models but also needs them quickly, regardless of who provides them. The Stargate Project would only advance the OCI-OpenAI connection, bringing new workloads to OCI and sending a message to the market that OCI is also in the game with Amazon Web Services (AWS), Microsoft Azure and Google Cloud when it comes to AI workloads.

Oracle Sets Its Sights on Healthcare as the Company Pursues AI Opportunities for Cerner

Oracle CTO Larry Ellison’s remarks at the White House on Jan. 21 were brief but telling of where Stargate could go, with the Oracle co-founder highlighting AI’s role in modern electronic health record (EHR) management and healthcare transformation at large. Of course, Oracle entered the healthcare market over two years ago with its acquisition of Cerner and has since modernized Cerner Millenium on OCI in hopes of delivering a new cloud-based system that will challenge decades-old EHR systems. This includes an EHR system that can support disease-specific AI models that, importantly, are developed not by Oracle but by medical professionals with expertise in said diseases. The details and timeline around Stargate are still vague but stand to advance Oracle’s push in AI, including within the healthcare vertical, which perhaps has among the most to gain from AI’s potential.
 
When the Cerner deal closed, Ellison was very clear about plans to have a standardized database that unifies fragmented data so medical professionals can instantly access EHR data, regardless of what type of EHR system it is, within a single database. At the time, we wrote about the obvious roadblocks to overcome, including the security & compliance concerns and need to obtain legislative backing. Since Ellison’s initial remarks, we have not heard much of an update on this vision, but Stargate and what seems to be Oracle’s rising role in the new administration (stay tuned as we track any potential Oracle-TikTok developments) could help move this vision along.

While Microsoft Has Been a Close Ally of OpenAI, the Bond That Was Forged in the First Year of GenAI’s Time in the Spotlight Has Weakened

So, how did we get here? Rumors of the Stargate Project date back to March 2024, when OpenAI CEO Sam Altman outlined ambitions for a $100 billion data center in partnership with Microsoft. At the time, the partnership seemed logical, given the companies’ long-standing relationship and Microsoft’s significant equity stake in OpenAI. However, the dynamics have shifted. In October 2024 Altman publicly criticized Microsoft for its slow progress in building AI-dedicated infrastructure, an issue corroborated by reports of persistent infrastructure shortages from Microsoft management. OpenAI’s latest announcement reflects the outcome of this strained relationship, as Azure’s exclusivity agreement with OpenAI has been officially amended, granting OpenAI the right to seek alternative delivery agreements if Microsoft fails to meet its compute demands. Oracle is the first cloud provider OpenAI has turned to, leveraging Oracle’s substantial capacity for AI workloads and an increasingly strategic relationship with Microsoft.
 
OpenAI’s shift toward Oracle is a setback for Microsoft but does not entirely diminish the hyperscaler’s leadership in AI. OpenAI remains a close partner, and Microsoft is well positioned to grow its AI-related IaaS revenue as the company continues expanding its infrastructure. Furthermore, Microsoft’s SaaS portfolio serves as a key delivery mechanism for OpenAI’s models, and the company retains a significant equity stake in OpenAI.
 
These factors are likely to sustain the strategic partnership between the two entities for the foreseeable future. Although Microsoft is not a member of the Stargate joint venture, it is listed as a strategic technology partner, and TBR expects its platforms and software to play a role in the project.
 
Additionally, while Microsoft may have less influence over OpenAI’s hosting decisions, Oracle and Azure remain deeply interconnected. For instance, Oracle now uses Azure data centers to house its database hardware through the Oracle Database@Azure Service. This setup could theoretically integrate Azure OpenAI into AI development as customers bring enterprise data from Oracle into the Azure cloud.

Stargate’s First Phase Includes the Construction of a Massive $100B Data Center, the Largest GPU Cluster in the World

Why Build an AI Megacluster?

OpenAI’s primary motivation for increasing computational resources is to meet the exponential demands of training models with higher parameter counts. Scaling up these parameters allows models to process larger quantities of data, often referred to as context windows. As a context window expands, model outputs improve in quality and accuracy. The prevailing belief is that pushing parameter counts far enough will enable models to exhibit the capabilities defined in OpenAI’s vision of AGI. With full financial backing from the U.S. government, OpenAI’s pursuit of AGI appears more achievable. The result would likely be a versatile GenAI back-end architecture capable of transforming process automation in SaaS workflows. However, in the short term, OpenAI’s focus on parameter scaling keeps its AI strategy centered on general-purpose LLMs, rather than more specialized small language models (SLMs). This approach makes OpenAI’s models particularly suited for productivity tools and customer service applications, while specialized models may dominate in niche workflow tasks.

Possible Stargate Constraints

While unparalleled access to GPUs and compute infrastructure is a major advantage for OpenAI’s model training strategy, there are still several factors that need to be addressed alongside the data center construction. First, the Stargate Project initially intends to absorb Oracle’s privately funded, in-progress data center in Abilene, Texas, yet TBR believes this could heighten power supply challenges. While power transmission constraints are widespread, Texas’ power grid has had issues in the past, such as in the winter of 2021, due to the fact that Texas’ power grid, unlike the other 47 states in the continental U.S., does not connect to the two major national grids. This prevents access to backup power generated outside the state and poses a risk of a significant outage. To mitigate these power concerns, TBR believes developing alternative power sources, namely nuclear power, will be a priority early in the Stargate Project.
 
Second, having access to effective training data remains a persistent need within the model developer market. While OpenAI has been forthcoming in striking deals with internet platforms and media sources, some speculate that the corpus of data available to train LLMs and large multimodal models (LMMs) could soon be completely used up. The use of synthetic data has often been proposed to overcome this hurdle, yet this path brings separate issues like greater AI hallucinations and model drift. Altogether, while securing project financing is the first step, working around these constraints will challenge OpenAI as it pursues AGI, and the innovations created in the Stargate Project will need to reach beyond simply building the largest AI-dedicated data centers in the world.
 
Financing could also prove to be a risk. In response to Trump’s executive action, Elon Musk, a Trump insider and co-head of the new Department of Government Efficiency, publicly shared his belief that the U.S. government does not have enough money to fund the project. Of course, Musk has a bias as the founder of startup xAI, but nevertheless, the Stargate Project does have a staggering price tag. Still, with the Republican Party’s control of the legislative and executive branches, there will be fewer political barriers to financing the Stargate Project based on the assumption that AI supremacy is of greater strategic importance.

Conclusion

The Stargate Project marks a significant development in AI infrastructure, with OpenAI, SoftBank, Oracle and the U.S. government collaborating to create a network of AI-dedicated data centers. With a planned $500 billion investment, this initiative seeks to address the increasing computational demands of AI model development, positioning OpenAI to advance toward its goal of achieving AGI.
 
Oracle’s involvement, bolstered by partnerships with NVIDIA and its advancements in cloud infrastructure, highlights its growing role in the AI ecosystem and could advance Oracle’s Cerner ambitions. However, the project faces notable challenges, including substantial energy requirements and concerns over the availability of high-quality training data, which will require innovative solutions to address.
 
As one of the largest technology projects in recent history, Stargate reflects the evolving priorities in AI development and the broader strategic implications for technological leadership.

Infosys’ Future: Scaling GenAI and SLM Innovation to Drive Growth and Stakeholder Trust

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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.
 

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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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PwC India Harnesses Microsoft Copilot to Better Serve Clients in Cybersecurity

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In October 2024 TBR met with Sangram Gayal, PwC India’s Incident Response lead and Managed Services Strategy global lead, and Terence Gomes, PwC India’s Microsoft Alliance lead, for a discussion about PwC’s cybersecurity business in India and the firm’s alliance with Microsoft. The following reflects that discussion and TBR’s ongoing interactions with and research on PwC.

Building on solid base, PwC India and Microsoft expand cybersecurity alliance

Setting the stage for an India-centric discussion, TBR met with PwC India leaders for a discussion about the post-pandemic shift in perspectives on opportunities within the India market, based on India’s economic growth and the growth of international companies’ global captive centers. Increasingly, according to Gayal and Gomes, decision makers for global companies reside in India, which is influencing talent management, supply operations and growth opportunities.
 

In this emerging environment, PwC’s decade-old decision to shift its cybersecurity practice from purely consulting to a mix of advisory and managed services has positioned the firm well for transformation, implementation and operations engagements. While PwC India earns 35% to 40% of its cybersecurity revenues from multinational clients, the remaining 65% to 60% comes from India enterprises, primarily in banking and other highly regulated industries.
 

Additionally, PwC has gained ground providing cybersecurity managed services in the manufacturing and pharmaceuticals spaces. Gayal and Gomes confirmed that consulting accounts for roughly 70% of the firm’s cybersecurity revenues while managed services makes up the rest.
 

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Turning to PwC India’s summertime announcement regarding collaboration with Microsoft, Gayal and Gomes noted that PwC’s strategy led the firm to partner more closely on cybersecurity because of Microsoft’s scale, established PwC India-Microsoft relationships, and Microsoft’s focus on large enterprise clients (not SMBs), which aligns with PwC India’s target market.
 

Further, PwC India’s Microsoft practice is, according to Gomes, “holistic,” covering everything in cybersecurity and much of the full Microsoft stack, making PwC an attractive partner for Microsoft — attractive enough, according to Gayal and Gomes, that Microsoft is bringing PwC clients and co-conducting workshops around transformation, security operations center (SOC) modernization, and cloud migration. Not surprisingly, clients then award PwC the cyber managed services deals that flow from these workshops and consulting engagements.
 

One issue the PwC leaders raised centered on talent growth paths. While PwC mostly hires university graduates and puts them through a cybersecurity academy, the firm expects the smartest freshers to move beyond cyber managed services and onto a partner track. TBR notes that PwC has dealt with this talent management issue, particularly in cyber managed services, for decades, constantly refining the professional development paths and selection processes. Gayal and Gomes said the Microsoft incident response in India is “very lean” and supported by teams in Australia and Singapore with “good local and good global connectivity with PwC.” As a result, PwC is enhancing incident response overall in India, helping Microsoft leverage the capacity and helping extend capabilities within India. In TBR’s view, PwC’s recognition of Microsoft’s long-term cybersecurity talent and capabilities needs in India — beyond just Microsoft salespeople — reflects the strategic nature of PwC’s partnership with Microsoft and bodes well for sustained growth.

“You need to be good. AI helps. We’re replacing mindless work with intelligent work.”

Regarding Microsoft Copilot — ostensibly a catalyst to the July 2024 announcement mentioned above — Gayal said generative AI is “all about the promise of being able to do better queries and get better recommendations, not about the promise of cost cutting and not about reducing headcount.” Working with Microsoft Copilot enables PwC cybersecurity staff to make “better queries without exceptional coding and software skills,” leading to faster threat hunting and faster incident response.
 

Further, according to Gayal, Microsoft Copilot “enables recommendations not previously easy to formulate … [so PwC professionals] can be more creative and expansive in the how-to of running a SOC and … doing investigations.” When TBR asked about demonstrating these Microsoft Copilot-enabled capabilities to Indian clients, Gayal and Gomes noted that PwC conducts workshops at PwC SOCs, PwC Experience Centers, Microsoft offices or — most often — the client site.

A strategic growth hub for cybersecurity services

On multiple occasions over the last year, PwC leaders globally have asserted to TBR that India will become one of the most important markets for PwC services — clients based in India and served by PwC India. Gayal noted that India companies struggle to “hire the right skills right now,” even as these companies are “growing very fast and have growing cybersecurity needs.”
 

PwC’s global leadership attention and investment, combined with a market ready for PwC’s services and — critically — a strategic partnership with Microsoft, have created a level of enthusiasm for the opportunities in India.
 

Arguably, PwC brings another key element to bear: the firm is not new in India — it is not jumping onto the Indian economic bandwagon — but is, instead, a long-established brand with an intimate understanding of the Indian business climate and culture. Other IT services companies can emulate PwC’s cybersecurity offerings and capabilities but lack the firm’s deep knowledge of how Indian companies actually run their businesses beyond the IT shop.
 

As companies increasingly view cybersecurity as critical to running the business, cyber managed services players need to have a full understanding of their clients’ operations, financials and risks. Being part of the broader PwC firm gives PwC India’s cybersecurity team a clear advantage. TBR will be watching in 2025 to see what the team does with it.

What Spectrum Will 6G Use?

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The wireless technology ecosystem is rallying around FR3 bands for 6G

The wireless technology ecosystem has settled on the upper midbands, specifically the 7GHz-24GHz range (aka Frequency Range 3 [FR3]). Within FR3, 7GHz-15GHz is considered the golden range for 6G, as it has the best balance between coverage and capacity and 1600MHz of total bandwidth could be made available in the U.S.
 
However, one of the biggest issues with these “golden bands” is the need for communication service providers (CSPs) to coexist with incumbent users, such as government entities and satellite operators, which utilize some of these channels for various purposes and would need to either clear, refarm or share those channels with CSPs for use in cellular communications. The telecom industry already has some experience with shared spectrum through CBRS, which operates in the 3.5GHz band, so there is a pre-existing framework and mechanism in place (i.e., Spectrum Access System) from which to begin establishing a spectrum sharing system for these new bands.
 
Ultimately, TBR believes that 6G will end up leveraging a mix of spectrum tranches, with midband, upper midband and mmWave frequencies all in play. Carrier aggregation and other frequency-combining technologies, as well as advancements in beamforming and endpoint devices, make these spectrum bands perform better when working together. Additionally, FR3 spectrum is not good at penetrating walls. Given that around 80% of wireless traffic is generated indoors — a statistic that is unlikely to change materially in the 6G era — FR3 bands would need to be complemented with lower bands to penetrate walls and provide optimal coverage and capacity.
 

Learn the scope of government support for the telecom industry amid 6G market development.

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Limited CSP investment and increased government role expected to shape the next cellular era

The telecom industry continues to struggle with realizing new revenue and deriving ROI from 5G, even after five years of market development. TBR continues to see no solution to this persistent challenge, and with no catalyst on the horizon to change the situation, CSPs’ appetite for and scope of investment in 6G will likely be limited.
 
TBR expects CSP capex investment for 6G will be subdued compared with previous cellular network generations, and deployment of the technology will be more tactical in nature, which is a marked deviation from the multihundred-billion-dollar investments in spectrum and infrastructure associated with the nationwide deployments during each of the prior cellular eras.
 
In a longer-term effort to address this situation, TBR expects the level of government involvement in the cellular networks domain (via stimulus, R&D support, purchases of 6G solutions and other market-influencing mechanisms) to significantly increase and broaden, as 6G has been short-listed as a technology of national strategic importance.
 

Click the image below to watch this recent TBR Insights Live session, 6G: How Government Intervention Will Shape the Next Generation of Telecom

 
With that said, 6G will ultimately happen, and commercial deployment of 6G-branded networks will likely begin in the late 2020s (following the ratification of 3rd Generation Partnership Project [3GPP] Release 21 standards, which is tentatively slated to be complete in 2028). However, it remains to be seen whether 6G will be a brand only or a legitimate set of truly differentiated features and capabilities that bring broad and significant value to CSPs and the global economy.
 
Regardless, the scope of CSPs’ challenges is growing, and governments will need to get involved in a much bigger way to ensure their countries continue to innovate and adopt technologies that are deemed strategically important.
 
 

Learn more

Download 2025 Predictions special report: 6G’s Fate Depends on the Level of Government Intervention

Watch on demand: 6G: How Government Intervention Will Shape the Next Generation of Telecom

 

AI Agents: What Are They, and How Will They Impact the AI PC Space in 2025?

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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.
 

Find out what’s in store for AI PCs in 2025, including how built-in AI and neural processing units are shaping the next PC refresh cycle.

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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.
 

Click the image below to watch our latest devices TBR Insights Live session, AI PCs in 2025: Unlocking Mass Appeal and Overcoming Market Challenges

 

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.

 

Learn more

Download 2025 Predictions special report: AI PCs: Progress, Potential and Hurdles in Redefining the Market in 2025

Watch On-demand TBR Insights Live session: AI PCs in 2025: Unlocking Mass Appeal and Overcoming Market Challenges

Key Discussions on Strategic Alliance Management, the Emerging India Opportunity, Monetizing GenAI in Cloud and More Now Available On Demand

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Technology Business Research, Inc. (TBR) is pleased to announce on-demand availability of all of our 4Q24 TBR Insights Live webinars. 4Q24 topics included strategic alliance management, the U.S. telecom B2B market, the emerging India opportunity, monetizing generative AI (GenAI) in cloud, the evolving IT infrastructure landscape, the private cellular networks market, and the hyperscaler ecosystem landscape.

 

Click any of the linked titles below to watch the full videos today.

 

Strategic Alliance Management: Case Study of a TBR Use Case

Learn: How both services revenue and industry-vertical revenue can guide your firm’s alliance strategy; how quarterly ITO revenue can help your firm benchmark partner teams for QBRs with validated and independent data; and which global systems integrator may be the right partner for your firm, and why the biggest partner may not be the best

 

State of the U.S. Telecom B2B Market: Trends and Strategies Impacting the Competitive Landscape

Learn: B2B revenue comparison of leading U.S. operators; macroeconomic and telecom industry trends that are impacting B2B customer segments, including SMBs, large enterprises and the public sector; and the impact of recent and upcoming partnerships and mergers & acquisitions on the competitive landscape of the U.S. telecom B2B market

 

$130+ Billion Emerging India Opportunity – India-centric vs. Global IT Services Firms: Who Wins and Why

Learn: The strategies, investments and internal activities global management consultancies and global systems integrators have leveraged to address the local Indian market; the market minefields and systemic challenges that may slow growth in consulting and IT services; and the consultancies and IT services companies TBR believes will lead and lag in the market

 

Monetizing GenAI: Cloud Vendors’ Investment Strategies and 2025 Outlook

Learn: The investments cloud vendors are making in their infrastructure, partnerships and portfolios; the business models that enable vendors to best monetize GenAI technologies; and TBR’s projections for industry changes in 2025

 

Evolving IT Infrastructure Consumption Services: Expectations for 2025

Learn: How infrastructure consumption services are evolving to meet AI demand and the increasing role they are playing in sustainability

 

Private Cellular Networks: Growth Drivers, Challenges and Opportunities Expected Through 2028

Learn: Which verticals are leading and lagging in private cellular network adoption; which ecosystem players are positioned to capitalize on market trends; and key growth drivers and detractors expected through 2028

 

Hyperscalers Building Out Their Global Networks: What this Means for the Telecom Industry

Learn: Key insights from TBR’s latest Hyperscaler Digital Ecosystem Market Landscape and how hyperscaler-owned and -operated networks will impact the telecom industry

 

TBR Insights Live sessions are held typically on Thursdays at 1 p.m. ET and include a 15-minute Q&A session following the main presentation. A recording of the session is sent to all registrants the day after the live airing.

 

To find out what we are discussing in the upcoming months, visit the TBR Insights Live page of our website.

 

PwC Positions Trust and Cybersecurity as Pillars for Success in AI and Business Transformation

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Analyst Summit Boston: PwC positions trust and cybersecurity as pillars for success in AI and business transformation

PwC has unquestionably built a brand around trust, as reflected in the two main themes woven throughout the Boston PwC Analyst Summit: risk and cybersecurity. In TBR’s view, PwC’s fundamental value proposition around trust and client intimacy reflects the firm’s strong governance, risk and compliance (GRC), cybersecurity and technology capabilities. TBR views risk and cybersecurity offerings as natural enablers for client discussions around business model reinvention and — when complemented by credible customer zero use cases across multiple domains, including AI — an extension of trust throughout a client’s ecosystem.

 

Despite its traditionally risk-averse culture, PwC was relatively quick to roll out an internal version of ChatGPT to all employees, and TBR believes the firm likely uncovered substantial best practices in how to manage change and limit downside risk associated with generative AI (GenAI).

 

Recognizing that cyber risk is no longer solely a technology issue but also a businesswide concern with financial and reputational consequences, PwC leaders repeatedly stressed that governance, not technology, must take the lead in ensuring robust cybersecurity strategies, supported by an ecosystem of partners. During a managed services use-case discussion, a client noted that PwC brought specific technology expertise and experience working with other business customers on this client’s specific problem. PwC’s relevant experience offered the client distinct benefits around risk mitigation, as part of their larger managed services engagement.

Additional highlights from PwC’s Boston event:

  • An emphasis on data sustainability and GenAI is central to PwC’s long-term investment strategy, forming the foundation of every business line. PwC’s role as what TBR calls a “technology orchestrator” reflects the firm’s commitment to navigating the intersection of renewable energy, AI and other emerging technologies to help clients adapt and grow.
  • Geopolitical tensions, particularly between the U.S. and China, remain a critical concern, with bipartisan consensus in the U.S. about addressing these issues underscoring the urgency. Despite challenges with R&D expense rules and state-level regulatory complexities, PwC has been advising clients to embrace sustainability and prepare for scenario planning.
  • Mike Thiessen, PwC’s U.S. Chief Clients and Markets leader, noted that PwC’s approach to GenAI focuses on building bespoke workflows, integrating technical development with legal safeguards, and prioritizing user-driven curation. PwC recognizes that each GenAI project is unique, requiring tailored approaches and experience in addition to technical features. Under these conditions, PwC ensures AI implementation is secure and effective, aligning with the firm’s broader AI strategy.
  • C. Lapierre, one of PwC’s U.S. Sustainability leaders, noted that mandatory reporting on climate action can serve as a catalyst for enterprises to get their data and sustainability strategy in order. Many companies now understand the scope and depth of the work needed to meet net-zero commitments, which were often made before the necessary parties had a full understanding of the difficulties and opportunities involved.

Artificial intelligence: Big bets, massive change, and all comes back to trust

On artificial intelligence (AI), PwC leaders during the Boston event noted that AI is reshaping everything, from brand and market positioning to operational strategy. PwC committed to a $1.5 billion investment in AI, an increase from its original announcement of $1 billion, underscoring the technology’s importance to the firm’s future.

 

The vendor is also focused on delivery excellence, specifically enhancing systems like SBLC to make them more intelligent and efficient. PwC noted that the U.S. firm spends 17 million hours annually bringing ISV partners into the production stage of engagements, clearly an area ripe for AI-driven optimization. Additionally, PwC leaders said that new partnerships around developing language models are revolutionizing SBLC, creating a new foundation while refactoring older offerings. According to PwC, this shift reflects the broader evolution of AI from an emerging technology to a general-purpose one that is now central to business strategies.

 

PwC leaders elaborated on potential business model implications of wider AI adoption, including the erosion of scale as a differentiator as AI-driven agentic workflows allow small companies to simulate large-scale operations. In addition, faster adoption rates help businesses more quickly realize the efficiency AI brings to back-office operations.

 

In TBR’s view, trust continues to be the linchpin for AI’s success; absent trust, AI’s potential will remain unrealized. As noted above, in previous TBR reports, and by PwC leaders repeatedly during the Boston event, PwC’s brand is built around trust.

 

Demonstrating the criticality of AI to PwC, firm leaders noted nine high-stakes AI investments, each worth $50 million, aimed at driving either top-line growth or cost reduction. One of the standout initiatives is Elly, an AI-powered system with a digital worker equivalent (DWE) of 2,500 — with each DWE representing 2,000 hours of work. This demonstrates the firm’s bullish outlook on AI’s return on investment.

 

Further, PwC leaders believe AI’s impact extends to enterprise resource planning (ERP) systems. While earlier designs emphasized efficiency, the focus has now shifted to functionality and achieving the best outcomes. In building these systems, PwC is ensuring that both design and implementation align with the firm’s strategic objectives. TBR agrees with PwC’s assessment of the potential for AI to massively improve ERP systems, provided enterprises fully trust their AI platform to handle mission-critical and proprietary data. Again, the emphasis is on trust.

Analyst Summit London: PwC leaders highlight megatrends and business model reinvention in effort to navigate transformation

In London, PwC leaders shared the following megatrends and commentary from the firm’s perspective:

  • Climate change is negatively affecting social stability.
  • Increasing demand for silicon chips and power, combined with a limited supply of chips and GenAI, is compounding clients’ risk factors.
  • There is a global need to rethink power, global food supplies, demographics and migration, and industrial processes.
  • Increase for on-demand mobility is quickening the pace of change in the automotive and oil & gas verticals.

 

To address the megatrends and capture opportunities, PwC is investing in three key areas both globally and in EMEA: sustainability, trust and business model reinvention (BMR). BMR requires helping clients operate in new ecosystems to find future areas of growth and reconsider how products and services will change. According to PwC EMEA leaders, AI, data and technology cut across all three, and every enterprise must be able to operate and be successful in these areas.

 

Going deeper on BMR, PwC EMEA leaders noted that, according to PwC’s most recent Global CEO Survey, approximately 45% of CEOs do not believe their business will be viable in the next 10 years without reinvention, up from 39% of respondents in 2023. Not surprisingly, clients are asking for PwC’s advice on strategic planning and how to invest today to be successful tomorrow. PwC has a methodology to assist clients with their transformations, starting by sitting with clients and discussing their needs to gain a deep understanding of their design and implementation abilities and industry knowledge and co-creating an approach that is industry-led and industry-focused.

 

According to PwC EMEA leaders, the PwC BMR framework helps clients identify business growth areas, such as the development of new ecosystems and the creation of new products and services to pursue value and underpenetrated areas of revenue. For example, through a client session, PwC walked through a BMR transformation in which PwC helped create a new company from scratch following a sale of the business. Through the new business, the client sought to overcome rising cost pressures as well as crop and agricultural challenges that were disrupting its ability to deliver its products. Additionally, changing its primary delivery method to include a different product allowed the new company to focus on driving value and creating new revenue streams.

 

In a separate client example, PwC created a new platform to transform how a university engaged with prospective students. Through the platform, the university sought to advance its technology, position for the future, strengthen trust, and improve online engagement and opportunities. PwC used its BMR framework in both of these client examples, guiding the evolution of existing business environments to identify needs and pursue next steps to future-proof operations.

 

On a technology-specific note, PwC EMEA leaders highlighted the firm’s Industry Edge approach, explaining that PwC’s first step is building a differentiated way to enable transformation outcomes tailored for each industry. PwC applies data and tech assets, gathers use cases to understand the best way to make decisions, and establishes preconfigured solutions that support business transformation, all while leveraging technology alliances.

 

The key, according to PwC EMEA leaders, is that the firm provides not only a consulting approach but also all of PwC’s capabilities, including technology, regulatory, risk and even tax services. Critically, in TBR’s view, PwC is not going to clients and selling Industry Edge; instead, the firm is adapting elements of Industry Edge that are applicable to specific clients.

 

PwC EMEA leaders noted that “every day PwC follows two principles”: 1) emphasizing client centricity, which PwC and TBR both recognize sounds obvious and is not differentiating but, according to PwC, is a key to success; and 2) a one-firm approach: a global network of firms that come together to seamlessly deliver services to clients. Pursuing these initiatives enables PwC to deliver reinvention and transformation services through an industry play, leading with the right approach to drive value, cocreation and evolution services.

TBR’s expectations for PwC in 2025

In TBR’s view, PwC’s twin analyst events at the end of 2024 showed a firm shifting into a new gear, perhaps reflecting leadership changes or the changing environment for professional services as the GenAI age begins to mature and PwC’s strategic investments and its own business model reinvention begin to take shape.

 

PwC’s early epiphany around artificial intelligence centered on understanding both the necessity of accessing client data and the implication that if a client’s data were a mess, AI would be useless. The firm steadily invested in the expertise and capabilities needed to assist clients with their AI journeys, accelerating that investment when GenAI hit the market. Notably, PwC continued its deeply ingrained practice of investing substantially in its own people, bringing AI and then GenAI solutions to the firm’s professionals and leaning into the customer zero approach.

 

Now PwC is fine-tuning its own business model and looking to accelerate technology adoption, redefine (or at least continually improve) global operations and grow its Managed Services business. In TBR’s view, it is not a reinvention … yet. Critically, as PwC transforms itself the firm remains grounded in its core value to clients: trust.