Governance Becomes a Prerequisite for Success with AI 

/by

Governance was a recurring theme across content sessions and executive meetings at Mobile World Congress 2026. As telecom operators move from experimentation to operational in AI, creating a corporatewide, centralized framework for data management, model oversight and regulatory compliance is becoming essential. Without clear governance, AI initiatives often remain fragmented across business units, leading to inconsistent outcomes, duplicated efforts and limited enterprise impact.
 
The challenge is that most telecom operators still lack a horizontal governance model for both AI and data. Data ownership is often siloed, policies vary by department and there is limited visibility into how models are trained, deployed and monitored. This fragmentation makes it difficult to scale AI beyond isolated pilots and increases operational, regulatory and reputational risk.
 

 
Telecom operators with strong C-suite sponsorship are best positioned to overcome these challenges. Executive backing helps enforce common standards, prioritize enterprisewide data initiatives and ensure AI programs are aligned with broader digital transformation objectives. Without this level of leadership support, governance efforts often stall as organizational silos resist change.
 
Leading telcos are beginning to formalize governance by creating centralized data offices and appointing chief data officers responsible for enterprisewide data strategy and governance. In practice, robust governance is quickly becoming a prerequisite for AI. Organizations that establish clear frameworks for data quality, access, security and accountability will be far better positioned to operationalize AI at scale and consistently generate business value.

More from Mobile World Congress 2026

MWC26 made clear that the telecom industry is entering a new phase shaped by the convergence of AI, geopolitics and digital infrastructure. While AI dominated the conversation, the broader narrative that emerged centered on control, resilience and trust in an increasingly complex digital environment.
 
Click here to read our lead telecom analyst’s full recap of Mobile World Congress 2026.

New Growth in Consulting Is Emerging from an Unexpected Place: Managed Services

/by

Managed services teams embedded at clients are quietly evolving into the front line for strategy and advisory opportunities

This spring, TBR will mark 15 years of publishing the semiannual Management Consulting Benchmark, and the basic structure remains essentially the same. Although this consistency is remarkable, consulting seems to be the only business model left undisrupted. Sure, technology now permeates everything, the talent pyramid faces structural change, and a good large language model might be capable of replacing an entry-level consultant, but the biggest firms continue to grow and provide answers to “tell me what to do and how to do it.” Consulting went through a rough patch from 2023 to 2025, but now we’re looking at a resurgence. Even as some industry experts see the Big Four dying alongside SaaS and private equity cutting the fat from strategy consultancy, TBR sees a few reasons to be more than bullish on management consulting in 2026 and 2027. Let’s start with where those consulting opportunities increasingly come from.
 
For the last couple of years, TBR has heard more and more consultancies and IT services companies describe a gradual shift in managed services, with professionals on-site at clients uncovering new management consulting opportunities and becoming, in a sense, the tip of the spear — a role traditionally played by strategy consulting. This is a significant change. If the trend accelerates and reaches scale, business models will change. For now, managed services as an entrée to management consulting remains a tactic for some and an aspiration for others. Years of use cases, experience and results lead TBR to believe managed services will contribute significantly to the growth of management consulting going forward.

Management services will positively impact consulting engagements — just not for everyone

OK, so managed services brings new opportunities, but for which consultancies? A better question: Will managed services enable traditional IT services companies to finally break through meaningfully into management consulting? Yes, massive IT services companies that have flirted with McKinsey-like consulting capabilities over the last couple of decades will be able to uncover and deliver on consulting opportunities based on their deep understanding of clients’ IT environments and business challenges. And accelerated AI adoption at enterprise scale will increase transparency and uncover opportunities for every IT services company and consultancy.
 
A scaled managed services practice trained in spotting consulting opportunities and armed with AI-enabled solutions will unquestionably win some management consulting market share. More significantly, from TBR’s objective view, is whether the Big Four firms can manage their staffing, brand promise and technology alliances to take advantage of the managed services practices they’ve already built and use those opportunities to return to robust management consulting growth. Maybe, but probably not all four. The next two years will be telling, and TBR expects the existing differences between the Big Four will become even more pronounced.
 
All of that just to say: Managed services will increasingly lead to consulting engagements, growing the overall consulting pie — just not for everyone.
 
As we continue into 2026 and look ahead to 2027, we see the three main management consulting groups pursuing similar yet different strategies and three main trends influencing how they execute those strategies. The Big Four firms (Deloitte, EY, KPMG, and PwC) continue to invest in and emphasize their industry expertise as differentiators, particularly in management consulting. McKinsey & Co., Boston Consulting Group (BCG) and Bain have all increased their technology capabilities and stressed to their clients and alliance partners (yes, they now have technology alliance partners!) that they’re deeply versed in emerging technologies, including AI.
 
And the IT services-centric consultancies, such as Accenture, Capgemini and IBM, continue to expand and contract their consulting practices, always returning to the same “end-to-end” set of offerings. (Yes, those are generalities. For specific analysis of each company, see TBR’s semiannual Management Consulting Benchmark.) Across the entire management consulting space, TBR sees increasing client demand for outcomes-based pricing, particularly as AI enables greater transparency across every aspect of an enterprise; talent management (within consultancies) emerging as a strategic lever for consultancies’ own business model reinvention; and AI permeatingeverything.
 
Looking beyond 2026, TBR sees three reasons to bet on growing demand for management consulting. First, AI-related confusion, FOMO (fear of missing out) and adoption will create massive, seemingly relentless opportunities for consulting. If you doubt that, consider how well your own company has adopted AI and how much AI has changed just since January 2025. Second, the managed-services-to-management-consulting pivot described above, combined with AI, will enable more competitors to stand up capable and scaled management consulting practices. Does that mean more competition? Yes, but it also means more opportunities for the firms that have established permission and people and can continue investing in capabilities without balancing those dollars (and margins) against other core businesses. Third, and a continuation of the previous point, the management consulting space will fracture into more highly specialized consulting firms, better-staffed IT services companies, and technology providers adding strategy consulting to their arsenal.

Explore deeper data and analysis

Over the last 15 years, technology has permeated every aspect of management consulting. This trend has been so persistent and significant that TBR has been increasingly asked if our taxonomy, which includes Strategy Consulting, Operations Consulting, Organization and Change Consulting, and Technology Consulting, still holds up. Indeed it does. Because while every consulting engagement includes technology, business model reinvention remains rooted in business: business strategy and operations and organization. And woe to the business that thinks AI doesn’t mean change management. Answering those core questions — what do I do and how should I do it — will provide opportunities for … let’s be ambitious and say millennia to come.
 
And we have the data.

2025 Estimated Management Consulting Revenue, Operating Margin and Year-to-year Growth by Company (Source: TBR)

 

Pricing Structure Utilized for DT Services Engagement (Source: TBR 2H25)


 
With TBR Insight Center’s interactive data visualization tool, your team can quickly adapt thousands of IT services and consulting data points for tailored competitive analysis, go-to-market strategy and executive briefings. The tool enables you to curate relevant quantitative insights by company, business unit and/or market segment, creating a report specific to your needs and ensuring consistent frameworks across projects.
 
Click here to explore Insight Center’s data visualization tool, or start your free trial today to access this one-of-a-kind digital-first intelligence platform.
 

Skills Shortage Will Challenge the Scaling of Sovereign AI in 2026

/by

AI-related skills will remain scarce across both buyers and ecosystem partners as the rapid pace of innovation and the technical complexity required to enable sovereign AI continue to hinder adoption. These challenges, combined with a lack of clearly defined and compliant use cases among sovereign customers, gaps in sovereign cloud infrastructure availability and steep AI learning curve faced by ecosystem partners, will constrain meaningful investment and implementation of sovereign AI throughout 2026.

Sovereign AI momentum will build through partnerships in 2026, but meaningful financial impact remains a longer-term prospect

Sovereign AI will undoubtedly mature more quickly than the sovereign cloud market, but it is still too early to expect a noticeable financial impact from those capabilities in 2026. While Sovereign cloud did not develop until more than a decade after the general cloud trend was underway, it remains very nascent from an adoption and market development perspective. Widespread adoption of sovereign AI depends on deliverable sovereign cloud capabilities, among other requirements. Further complicating adoption is the advent of agentic AI, which introduces new risks by leveraging data that can be sovereign and sensitive and by taking action on the intelligence produced.
 

Despite the challenges to widespread adoption of sovereign AI in 2026, we expect vendors across the spectrum of business models to aggressively partner and invest to capitalize on the opportunity in this emerging segment. Partnership activities will center on the strongest sovereign AI providers and the most well-established sovereign cloud regions, as would be expected. Amazon Web Services (AWS) and Microsoft are the clear leaders in sovereign cloud delivery capabilities, and their geographic focus will remain the U.S. and Europe, particularly Germany. The U.K. should also see concentrated investment and lead in early adoption.
 

Watch now: 2026 Predictions for Cloud & Software, featuring Senior Analyst Alex Demeule

 

In some ways, the development of sovereign AI will look much like the Industrial Revolution, which disproportionately benefited the developed countries that had access to resources and oil to fund the new economic model. Microsoft and AWS have already announced specialty partner programs for sovereign AI and big-name alliances with the likes of Accenture and SAP. We expect those alliances and ecosystems to become more AI-focused in 2026, providing tighter integration between cloud providers, model providers, SIs and ISVs that will form the foundation for sovereign AI growth in 2027 and beyond.
Explore more SaaS predictions for 2026 in our special report Will AI be the Death of SaaS in 2026?

PaaS Revenue Will Outpace SaaS Revenue for Cloud Software Vendors

/by

Enterprise customers are prioritizing the modernization of their existing SaaS estates rather than adding new applications, driven by market saturation, accumulated technical debt, and a growing imperative to become AI-ready. As IT buyers shift their focus toward modern platforms, traditional SaaS leaders should expect their PaaS segments to continue significantly outperforming their core SaaS businesses in revenue growth.

A clear inflection in SaaS momentum emerges

SAP’s trajectory is tied to Business Technology Platform (BTP) becoming the architectural anchor of RISE programs. BTP is no longer an optional add-on but rather the control plane for process mining, metadata management and event-driven extensions. Attach rates above 80% in RISE cycles reflect SAP’s ability to position BTP as mandatory for modernization rather than discretionary middleware. The addition of Signavio and LeanIX broadened the portfolio, giving SAP a modern platform that starts with process intelligence and ends in a coherent data and extension strategy.
 

Salesforce is following a data-first path. Data Cloud has become the centerpiece of modernization discussions as the company works to consolidate fragmented CRM data models and unify cross-cloud metadata.
 

MuleSoft remains critical in stitching legacy systems into Salesforce’s AI-ready architecture, and early Data Cloud wins indicate customers view it as the foundation for copilots, agentic workflows and future small language model integration.
 

Both vendors benefit from a status as a highly trusted incumbent and deep process ownership, enabling them to sell platform capabilities not as adjacent tools but as prerequisites for becoming AI-ready.
 

SAP & Salesforce PaaS Revenue (Source: TBR)


 

Explore more SaaS predictions for 2026 in our special report Will AI be the Death of SaaS in 2026?

Alliances Will Extend Beyond Core Offerings as AI-driven Sales and Marketing Reshape Ecosystems

/by

Traditional one-plus-one alliances are evolving into multiparty alliances, unlocking new growth opportunities across the technology ecosystem. This shift is being accelerated by AI adoption — particularly in sales and marketing — which lowers the cost of expanding alliances, introducing new portfolio offerings and reaching new clients. As a result, tighter alignment among ecosystem participants is raising client expectations for more seamless integrations and more favorable commercial terms.

IT services firms will push beyond traditional alliances in 2026

Early adopters of generative AI (GenAI) frequently cited sales and marketing efficiency improvements as relatively easy use cases for proving the technology’s value and ROI. As those AI-enabled solutions matured, IT services companies sought to leverage productivity savings into expanded offerings, reflecting both the success of their customer-zero use cases and the opportunities to serve as data and AI orchestrators.
 

Qualities of a Successful Alliance (Source: TBR)


 

But IT services companies have their limits, and clients have preferred technology vendors, leading IT services companies to look to alliances to drive new growth. We have seen this pattern before, but in 2026 we will see IT services companies extend those alliances into devices, connectivity and even silicon, requiring a multiparty alliance approach that will strain commercial models, sales strategies and alliance leaders across the ecosystem.
 

In 2025, TBR’s ecosystem intelligence research repeatedly showed that companies across the technology ecosystem that developed multiparty go-to-market strategies and sought to leverage alliance partners beyond their traditional pairings experienced steadier revenue growth. One roadblock stood out: IT services companies rarely partnered with OEMs, primarily due to misalignment around sales, client base and brand.
 

TBR expects a substantial shift in 2026 as IT services companies more readily embrace partnerships with chip, edge, connectivity hardware and OT providers to extend IT services companies’ reach into clients’ technology environments and to fully exploit AI’s possibilities.
 

A partner at a leading consultancy with a substantial IT services practice once told TBR that even if an OEM gave him a gold brick, he would not try to sell it to his customers, in part to protect his brand from being associated with selling a physical product. This sentiment will not last through 2026.
 

Explore more 2026 predictions for alliances and partnerships by downloading our special report 2026 Will be a Pivotal Year as AI Momentum Drives Deeper Ecosystem Alliances.

Consulting Will Rebound in 2026

/by

After a period of relative softness, consulting revenues are expected to rebound to high-single- or low-double-digit growth as pervasive uncertainty pushes enterprises to seek external guidance. Demand will be particularly strong around risk mitigation, strategic planning and AI adoption, positioning forward-deployed engineers (FDEs), supply chain management (SCM) and people advisory services as leading revenue drivers in 2026.

Managed services shifts from delivery model to growth engine

AI-driven complexity will accelerate demand for consulting, particularly around data modernization, transparency, and helping enterprises understand the organizational impact of new software and AI capabilities. Popularized by Palantir, the FDE model will continue to permeate across IT services companies and consultancies in 2026, primarily as a marketing term but also backed by actual organizational changes, new hires, and adjusted ways of delivering value to clients.
 

AI integration work is increasingly performed by FDEs — engineers positioned close to clients who translate AI systems into business outcomes. Demand for FDEs is exploding, and hyperscalers and GSIs are building these roles, with Infosys viewed as an early leader and McKinsey & Co., Boston Consulting Group (BCG) and KPMG expected to position FDEs as premium integration talent. FDEs will likely follow the pattern of data scientists and other specialized roles within IT services companies and consultancies, responding to market demand and providing companies and firms with a new way to describe their AI-enabled offerings and solutions.
 

Listen now: 2026 Predictions for Managed Services, featuring Principal Analyst Bozhidar Hristov

 

Higher consulting demand will also come in an increasingly unstable geopolitical and economic world. Although uncertainty fueled by immigration issues, tariffs, fluctuating interest rates, and political instability dampened IT services and consulting growth in 2025, TBR expects an upturn in consulting revenues in 2026 even as those underlying conditions worsen. Navigating stormy seas demands a proven crew and trusted advisers; anyone can sail a ship in calm waters. TBR has seen a steady rise in investments into supply chain consulting, including increasing capabilities around the underlying technologies, such as blockchain and analytics. Combined with increasing investments in cybersecurity, TBR anticipates the three fastest-growing areas in consulting in 2026 will be risk mitigation (SCM and cyber, especially), strategy, and AI adoption.
 

But keep an eye on human capital management consulting. The IT services companies and consultancies will spend the next few years sorting out their own staffing models, adjusting the traditional apprentice-model pyramids to reflect AI-enabled roles and responsibilities changes (here come the obelisks). And these companies and firms will bring their lessons learned to enterprise clients, particularly around building highly functioning human-plus-robot teams, adjusting promotion and compensation packages, and budgeting for the expected higher costs of adopting AI at scale.
 

In all this consulting growth, TBR expects the leaders will be those IT services companies and consultancies that have refined and scaled their managed services offerings. This may come as a surprise to the longtime strategy consultants in leadership positions at many of these firms, but TBR’s research indicates revenue and growth at leading IT services companies and consultancies have been increasingly tapping into consulting opportunities identified through ongoing managed services engagements. Who knows more about underlying problems than the people working day-to-day with the client in their environment? TBR anticipates greater investment in managed services offerings and increased leadership attention paid to how those engagements underpin sustained consulting revenue growth. Managed services is no longer your mess for less but a Trojan horse for higher-margin consulting.
 

Explore more 2026 predictions for managed services in our special report In 2026, Managed Services Shifts from Delivery Model to Growth Engine.

Bad Debt Expenses Will Rise for CSPs in 2026

/by

The telecom industry will adapt to a K-shaped economy in 2026

In a K-shaped economy that increasingly separates financial winners from losers, the majority of households and businesses on the lower arm of the “K” are under mounting financial strain and are finding it more difficult to pay their bills. As these economic pressures persist, communications service providers (CSPs) should expect bad debt expenses to continue rising, with the potential to meet, or even exceed, levels experienced during the Great Recession.
 

CSPs’ expenses related to bad debt have been steadily increasing since plunging to record lows during the height of the COVID-19 pandemic in 2021, when an unprecedented amount of government stimulus provided a financial windfall to households and businesses across the U.S. (and in many other countries through their respective stimulus programs), enabling many to improve their debt situations.
CSPs’ bad debts have now exceeded the mean of pre-pandemic, normal levels and are likely to reach levels unseen since the Great Recession. A key leading indicator of bad debt expense is what some operators report and refer to as “provision for credit losses,” which is the amount of money owed to CSPs that they expect to write off.
 

Provision for Credit Losses as a Percentage of Total Revenue_TBR

Several headwinds are occurring concurrently, which will push bad debt expenses higher for CSPs

  • The resumption of student loan payments as of June 2025, which has made it more difficult for households to manage their finances, evident in the stark increase in subprime car loan delinquencies and a spike in home foreclosures
  • Inflation increasing costs of basic life necessities and business needs
  • Tariffs impacting consumers and businesses, feeding inflation and forcing tough financial decisions
  • Job losses and a generally anemic job market (directly and indirectly, due to AI and general business restructurings and bankruptcies)
  • Immigration policy changes — deportations and voluntary emigrations lead to unpaid bills, including phone and internet bills
  • Interest rates remain high relative to the post-Great Recession new-normal level, making it more challenging to pay back interest-bearing loans
  • Paring back of social safety nets — SNAP, WIC and other food security benefits, and government-provided or subsidized healthcare programs
  • Bankruptcies surging across the business spectrum; bankruptcies can lead to restructured debt loads or partial or full nonpayment if the entity liquidates

Overall, most households and SMBs are increasingly struggling to pay their bills, as evidenced by essential expenses like car and mortgage payments becoming harder to manage. Because cars, homes, phones and internet service are essentials, bad debt expense is likely to continue rising through 2026, and telecom providers will feel the impact.
 

Explore additional predictions for the telecom industry in 2026 in our special report The Telecom Industry Will Aapt to a K-shaped Economy in 2026.

How Will Advanced AI Impact Pricing, Labor Practices and Client Expectations?

/by

TBR FourCast is a quarterly blog series examining and comparing the performance, strategies and industry standing of four IT services companies. The series also highlights standouts and laggards, according to TBR’s quarterly revenue projections and geography estimates. This quarter, we look at Infosys, Tata Consultancy Services, HCLTech and Accenture and compare how their advanced AI and labor strategies position them for revenue growth.

 
Advanced AI may be front and center in IT services strategy, but execution challenges remain a familiar story. Despite ongoing hype around unlocking new efficiencies and nonlinear growth, IT services firms continue to grapple with the reality of needing labor arbitrage in the short term and meeting client expectations. The distance between strategic intent and operational reality is less about reluctance to adopt AI and more about IT services companies’ timing, risk management, and the need to protect revenue streams today while betting on the future potential of advanced AI.

AI-first in strategy, labor-arbitrage in practice

Although all IT services companies aim to leverage advanced AI to improve margins and propel revenue growth, in the short term some are still relying on headcount growth to execute on deals. For example, even though advanced AI remains core to HCLTech’s delivery strategy and in February the company announced a goal to double revenue with half the number of employees, HCLTech has added a total of 10,032 freshers over the past three quarters.
 
Similarly, Infosys has increased headcount in preparation for executing on large deals, as evidenced by its announcement of hiring a total of 12,000 freshers over 2Q25 and 3Q25. In contrast, Tata Consultancy Services (TCS) and Accenture experienced headcount declines in 4Q25, marking the first drop for Accenture since 2010. Yet the quarterly decrease for both companies may reflect the worsening macroeconomic conditions rather than decisions to downsize headcount. If anything, companies are preparing for ongoing demand fluctuations as clients remain cost-conscious.
 
According to TBR’s 3Q25 IT Services Vendor Benchmark, offshore and nearshore headcount continues to grow among the 30 covered vendors, increasing 1.2% in 3Q25 as opposed to a 1% decline in onshore headcount in the same period, indicating the labor arbitrage model is alive and well, at least for now. Accenture, HCLTech, Infosys and TCS are all expanding their reliance on global delivery centers, including for in-demand skills such as AI, causing increased demand for highly skilled workers. Most companies have reported some AI training numbers, such as TCS stating that 159,000 of its more than 580,000 employees have been trained on AI. However, the reported numbers reflect a significant portion of companies’ employee base, raising questions about the depth of knowledge. TBR believes the training is just deep enough to lend credibility to the marketing.

BPO companies are the first to face a transformative wave of AI delivery implications: Can they impress clients while keeping them happy?

The four covered IT services companies are all top contenders in the business process outsourcing (BPO) space, making advanced AI essential for these companies right now. CEO of HCLTech C Vijaykumar stated on the company’s CY3Q25 earnings call, “As mentioned on Investor Day, the biggest impact will be in the BPO business, where productivity gains could reach 40 to 50%.” According to TBR’s estimates (see Figure 1), Accenture has the largest BPO segment, followed by TCS, HCLTech, and Infosys. With BPO having the most initial risk of cannibalization to traditional revenue, these companies will be the first to test how to adapt their commercial models. Although delivery remains largely time-and-materials-based, IT services companies such as Accenture are moving to a fixed-price model, a potential bridge to outcome-based pricing.
 
Yet cost-conscious clients are beginning to demand lower pricing due to the use of AI and automation, forcing IT services companies to compete on price even as they look to improve margins. This is creating pressure to realize ROI internally while appeasing clients on price and service quality. According to TBR’s 4Q25 Infosys Earnings Response, Infosys views its agentic AI “as a productivity and monetization lever rather than a growth engine that fundamentally reshapes the revenue mix.” Persistent macroeconomic uncertainties remain both a blessing and a curse for vendors. On the one hand, clients are becoming more curious about the benefits of advanced AI adoption, particularly agentic AI, providing more sales for IT services companies. On the other hand, clients are demanding a growing share of the resulting cost savings as price discounts, negatively impacting vendors’ margins.
 

2025 BPO Revenue Graph

Figure 1: 2025 BPO Revenue for Accenture, HCLTech, Infosys and TCS (Source: Company Data and TBR Estimates)


 
So, what approach should companies take to maximize potential growth, protect margins and ROI, and manage client expectations? Although companies are racing to keep pace with the competition in offering hyperscaler-enabled agentic capabilities as well as large language model-enabled solutions with companies such as Anthropic and OpenAI, establishing proprietary solutions will be important to differentiate and demonstrate advanced AI proficiency. Companies may have difficulty finding a healthy balance between focusing on proprietary solutions that set themselves apart and delivering key partner-enabled solutions that clients have come to expect and trust.
 
Perhaps more importantly, IT services companies will need a well-thought-out strategy to deepen client relationships while keeping AI top of mind as a value-add rather than a purely cost-conscious tool. Slimming headcount, for example, is undoubtedly an end goal for Accenture, HCLTech, Infosys and TCS, but maintaining the right strategic onshore locations to keep a human touch and not cutting headcount too quickly will be essential to retain employees and institutional knowledge. This will help uphold the company’s service quality, but if IT services companies can leverage AI to augment service delivery rather than market solely as one-size-fits-all stand-alone solutions, this could generate more demand. Further, protecting the value of services will strengthen companies’ contract negotiating power.

Conclusion

HCLTech is among the few IT services companies that have reported advanced AI revenue. In 3Q25 HCLTech announced it received $100 million in advanced AI revenue. On Accenture’s 4Q25 earnings call, the company reported advanced AI revenue of $1.1 billion, but leadership later noted that this metric will no longer be reported because advanced AI has become integrated across much of the company’s operations. This also implies concerns of revenue cannibalization — especially if Accenture cannot introduce fixed pricing fast enough. TBR believes companies need to have a well-planned pricing strategy in addition to a holistic approach to ensure a healthy long-term trajectory.
 
HCLTech follows this approach in part through its industry- or task-specific solutions that focus on solving a problem. Product launches throughout 2025 reflected this point, including HCLTech Insight, an agentic AI solution built with Google Cloud to support manufacturers with data analytics, and Physical AI with SAP, which enables optimization across warehouse operations, fleet management and 3D reality capture. TBR believes this strategy, although not entirely unique, has contributed to HCLTech’s consistent financial performance and strong bookings.
 
TCS takes the opposite approach in some ways, using AI to augment existing platforms rather than releasing stand-alone AI solutions. Although this may help TCS navigate revenue disruption in the short term as its client-facing solutions retain their names and functions, over time TCS may need to define its AI strategy better and market a more compelling story about how it can help clients solve problems with innovative solutions. Nevertheless, TCS’ IP-driven AI strategy will undoubtedly be a strength. Infosys may have a better narrative around AI aligning as it shifts its strategy to focus on outcomes.
 
Additionally, similarly to TCS, according to TBR’s 3Q25 Infosys report, “Successful positioning and usage of industry- and function-aligned proprietary and partner-enabled agents could help Infosys stay grounded, which could strengthen trust with clients and partners and help drive sales rather than entering uncharted territory in a GenAI [generative AI] market that is in a hypergrowth phase.” Importantly, TCS and Infosys have not reported AI revenue numbers. TBR believes the two companies may be withholding this data because it may be less than HCLTech’s and Accenture’s figures. With Accenture no longer reporting the metric, TCS and Infosys may be less likely to provide the information.
 

IT Services Revenue Forecast for Accenture, HCLTech, Infosys and TCS Graph

Figure 2: IT Services Revenue Forecast: Accenture, HCLTech, Infosys and TCS (Source: TBR)


 
How will the three India-centric vendors fare against Accenture, which has vigorously invested in AI IP, particularly in industry-specific solutions such as the AI agents in AI Refinery? Although India-centrics’ clients may not have the same expectation as Accenture’s clients, the vendors will need to make sure they are prioritizing client outcomes and creating a meaningful narrative. Leaning into this approach will be particularly important as Accenture’s undeniable size in BPO provides it with an ideal testing ground for agentic AI. TBR could see Accenture making a similar acquisition as Capgemini did with WNS, such as by acquiring Genpact or EXL, which would sharpen its competitive edge. Ultimately, future success will depend on how effectively IT services companies translate AI adoption into differentiated, outcome-driven offerings without eroding client trust or margins. Those that balance proprietary innovation with partner ecosystems while resetting commercial expectations will be best positioned as AI reshapes cost structures and value creation.

AI Alliances Will Increasingly Target OT

/by

New and expanding partnerships are increasingly targeting the convergence of IT and OT, as system integrators (SIs) align with OEMs, manufacturing ISVs and silicon providers. This momentum is driven by the strong growth potential in high-tech manufacturing, where solutions that improve accuracy, efficiency and safety can be deployed on-site without reliance on rack-scale compute systems in neoclouds or Tier 1 clouds. As a result, while AI has long operated at the edge, these partnerships will accelerate both the sophistication of AI-driven use cases and the pace of solution framework development.

A host of use cases are ripe for disruption in OT

NVIDIA AI platforms, including NIM Agent Blueprints and NVIDIA Omniverse, lay a foundation on which partners can build. Partnerships representing a blend of IT and OT capabilities — including NVIDIA, SIs, manufacturing-centric ISVs and OEMs — will bring together new capabilities.
 

SIs are a key piece of the puzzle to bridge IT and OT. Although NVIDIA provides a platform, the complexity exceeds what most IT teams can manage. The SI also must act as a bridge between IT and OT technologies, skill sets and cultures. Expanding partnerships with industrial automation leaders such as Siemens is central to this.
 

As constraints around the ability to quickly build out AI factories become clearer, edge workloads will be an AI opportunity relatively unencumbered by these restrictions.
 

High-tech manufacturing represents a strong opportunity for AI adoption globally. Within the U.S., edge AI will be positioned as a focal point for the era of modern manufacturing.
 

In addition to the GPU-enabled edge servers available in the market, NVIDIA’s upcoming launches of RTX AI server and IGX Thor edge computer, which do not require liquid cooling, will accelerate interest in AI use cases on premises and at the edge.
 

Other silicon providers, namely Qualcomm, will launch products designed for manufacturing and robotics in 2026. However, a strong software platform from which SI partners can build on is a necessity for success.
 

TBR expects other industry verticals, including pharma and biotech, will replicate these partnership approaches.
 

Enterprise Edge Spending Forecast by Segment (Source: TBR)


 

Explore more 2026 predictions for alliances and partnerships by downloading our special report 2026 Will be a Pivotal Year as AI Momentum Drives Deeper Ecosystem Alliances.

Agentic AI Adoption Is Pressuring Security Architectures to Converge

/by

Microsoft distribution edge and AWS and Google integration moves are reshaping competitive dynamics

The emerging pattern of multicloud security consolidation has direct implications for both Amazon Web Services (AWS) and Microsoft, as enterprises reassess detection pipelines, governance models and operating frameworks heading into 2026. Although AWS remains well positioned in analytics-heavy workloads, the company needs to reevaluate its long-established “building block” approach, especially as peers deliver more integrated platforms. For Microsoft, its strengths will continue to be with organizations where Microsoft 365 already anchors their identity and collaboration strategies.

Interoperability in agentic systems calls for greater interoperability in security

Security has been a top concern among enterprises for years, and that history of investment has often translated into sprawling security estates, posing a challenge for AI adoption. If agentic AI systems are going to work across platforms, security needs to work across platforms as well.
 
At Ignite 2025, Microsoft outlined a path intended to pull customers toward a more unified operating model. Tighter integrations across the company’s Defender, Sentinel and Purview offerings as well as the new Agent 365 control plane were a major development. However, announcements stating Security Copilot capacity will be bundled with both Microsoft 365 E5 and expanded Sentinel connectors for AWS really caught TBR’s attention. Sentinel’s updated AWS integration now uses an S3- and SQS-based model that ingests CloudTrail, GuardDuty, VPC Flow Logs and selected CloudWatch exports through an AWS Identity and Access Management role, allowing those signals to be correlated with Microsoft-native alerts in a unified analytics and response workflow. Creating more streamlined cross-cloud security signals Microsoft’s clear expectation that customers centralize analytics, automate more of the SOC and apply enterprise-level governance to AI agents rather than allow fragmented, team-level management.
 
AWS and Google are also responding to cross-cloud telemetry challenges. AWS has broadened Security Lake into a hub that can ingest and normalize signals from a wide ecosystem, including tools such as CrowdStrike, Palo Alto Networks Prisma Cloud, Wiz, Lacework, SentinelOne, Zscaler, Okta, Cisco Secure Firewall, ExtraHop, Vectra AI, Splunk, IBM QRadar, Datadog and Sumo Logic. Security Lake standardizes these feeds via OCSF (open cybersecurity scheme framework) and allows downstream analytics through OpenSearch Service or partner SIEMs (security information and event management).
 
Google Security Operations has taken a different path, building a SIEM and SOAR (security orchestration, automation and response) platform with a large connector catalog spanning GuardDuty, Security Hub, CloudTrail, Azure Active Directory, Carbon Black, network-security vendors, CSPM (cloud security posture management) tools and a wide set of SaaS and identity integrations. These connectors feed normalized telemetry directly into SecOps’ analytics and playbook engine, enabling orchestration and automated response across heterogeneous environments. The strength of Google’s approach lies in its broad ingestion and automation capabilities, though its native alignment remains strongest where organizations standardize on Google Workspace and Cloud Identity.
 
With each vendor pursuing new security integrations, Microsoft’s greatest point of differentiation is its distribution advantage. The company’s security capabilities sit on top of the widespread Microsoft 365 and Entra ID install base, giving Microsoft direct access to identity, endpoint and collaboration signals without requiring separate platform deployment. Moreover, partners can attach services to an installed base rather than drive net-new platform adoption, enabling faster scale and lower friction. AWS and Google can compete on analytics, automation or integration, though arguably both lack the access to enterprise control points that Microsoft derives from its productivity stack.

Explore deeper data and analysis

Although the cloud ecosystems market is complex, it is the backbone of the broader digital transformation (DT) opportunity. As a result, studying the relationship between services vendors and technology vendors provides a glimpse into some of the key issues many participants face as they work toward the same outcome: winning both market share and mindshare. As it leverages insights across all of TBR’s practices, the Cloud Ecosystem Report can help you better understand the nuanced trends and forces at play within cloud, professional services and other IT markets.
 
With TBR Insight Center’s interactive data visualization feature, your team can quickly adapt thousands of data points for their competitive analysis, go-to-market strategy, and executive briefings. The tool enables users to curate relevant quantitative insights by company, business unit and/or market segment, creating a report specific to your needs and ensuring consistent frameworks across projects.
 
Explore Insight Center’s data visualization tool with the video below, and start your free trial today to access this one-of-a-kind tool.
 

TBR Insight Center™ Data Visualization Tool