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Key IT Services Takeaways

Federal systems integrators (FSIs) are under mounting pressure to bring to market a broad portfolio of cloud offerings underpinned by a robust network of commercially centric cloud partners

TBR estimates the total available market in federal cloud was roughly $17 billion in FFY24, and we believe this figure is set to rise to between $20 billion and $21 billion in FFY25. We anticipate total federal cloud spending will expand by between $13 billion and $15 billion to surpass $30 billion by FFY28. Modernizing legacy IT infrastructures remains a paramount, strategic objective for civilian, defense and intelligence agencies that are actively migrating IT systems to the cloud and/or replacing outdated and monolithic IT networks with cloud-native technologies. The advent of AI, generative AI (GenAI) and agentic AI, and the mandatory adoption of zero-trust security infrastructures are also accelerating cloud adoption. The Pentagon maintains a robust pace of cloud implementation, and the next iteration of the $9 billion Joint Warfighting Cloud Capability (JWCC) is in development. DOGE’s actions will upend civilian IT spending patterns through the remainder of FFY25, with disruption likely extending into the first half of FFY26. Federal IT vendors have struggled with budget cuts, headcount reductions, and delayed procurement and project delivery cycles at many civilian agencies since DOGE began reviewing budgets in January 2025. In the long run, TBR believes DOGE will prompt a resurgence in demand for cloud-based solutions as civil agencies and departments are vigorously pushed to outsource increasingly larger shares of IT functions (particularly tasks once provided by now dismissed government employees), migrate to multicloud and hybrid cloud environments, secure their IT networks with zero-trust architectures, and digitally enable mission-critical systems.

Key Cloud Takeaways

Leading vendors look for ways to extend commercial products and go-to-market motions to the U.S. federal space as cloud opportunities increase

The JWCC contract continues to represent the single biggest opportunity for the cloud market’s leading players within the U.S. federal government: Amazon Web Services (AWS), Microsoft, Google Cloud and Oracle. As of 1Q25, roughly $2 billion in task orders have been allocated to these four vendors, with Oracle securing the biggest award to date, after the U.S. Army — with support from Accenture Federal Services (AFS) — migrated its legacy PeopleSoft deployment to Oracle’s Government Cloud. This win highlights the advantages of being rooted in legacy software and partnering with commercial SIs like Accenture that have experience modernizing business applications. JWCC is still in its early days — and an extended contract dubbed JWCC Next is under development — but Google’s recent IL6 (Impact Level) accreditation for Google Distributed Cloud (GDC), available as an air-gapped solution, should be a big step forward for not only Google but also JWCC, as all participating vendors can now deliver at the highest accreditation levels. That said, as the Department of Defense (DOD) starts to more actively leverage infrastructure from distinct cloud providers, it raises the question of interoperability; buying cloud services from multiple providers and leveraging multicloud environments are two different things. It will be interesting to see how agencies work to overcome integration challenges, which could include enlisting more PaaS vendors as part of JWCC Next, and if the four hyperscalers can deliver joint solutions that work with each other. Civilian spend remains strong, with the impacts of DOGE seemingly starting to fade, though defense spending will outpace civilian in the near term. AI opportunities within the sector are also increasing, namely for agencies that already have their infrastructure and applications in the cloud and are best positioned to take advantage of AI.

Cloud technologies are the foundation for digital transformation across the federal market; overall demand and opportunities for IT modernization remain prevalent

How do IT services vendors view the cloud opportunity?

Despite the growth in cloud spending outlined earlier in this report, large swaths of the federal government’s IT infrastructure remain in dire need of updating to cloud to accommodate the implementation of various AI technologies, advanced zero-trust security solutions, and other emerging technologies (e.g., quantum computing). DOGE disrupted federal IT spending in 1H25, but federal IT vendors remain undeterred in their pursuit of cloud-based digital modernization opportunities. Vendors and their federal customers are collaborating closely to map out future cloud migration and consolidation programs that will increasingly leverage commercially sourced cloud technologies, such as shifting federal data centers to cloud-based architectures to enhance data accessibility.

What do vendors need to develop or deploy to tackle the cloud opportunity?

The Trump administration is prioritizing enhancing data security, availability and cost-effectiveness via cloud technologies as a cornerstone of its federal IT strategy, and vendors are pivoting to align with the administration’s IT vision. FSIs must showcase their successful deployments of mission-enhancing cloud infrastructures that improve agencies’ operating efficiencies while crafting strategies for agencies to reinvest savings from DOGE-driven budget cuts and for the eventual implementation of next-generation technologies to support future missions. FSIs are adjusting marketing messaging to emphasize their ability to deliver innovation at speed within outcome-based cloud deployment engagements. Possessing the scale to deploy cloud infrastructures across agencies is still important for vendors. Equally critical are offering customers the broadest possible suite of partner-enhanced cloud solutions and having a vendor-agnostic approach to migrating federal IT workloads to cloud environments. Agency IT decision makers prefer not to be restricted to using products or services from a single vendor or a small cadre of IT providers. FSIs believe federal agencies will continue leveraging the cloud as the principal destination for legacy systems and for modernizing those systems and fully expect to accelerate adoption of SaaS and PaaS solutions, as reflected by federal IT contractors’ M&A, alliance and joint venture-related activities in 2024 and 2025.

Microsoft’s and Oracle’s hold on the U.S. government is unwavering, but AWS’ early IaaS lead and defense ties are elevating its standing in JWCC and the broader market

Unsurprisingly, Microsoft and Oracle are driving the bulk of prime awards, with the overwhelming majority stemming from traditional license and support contracts. Prime award value for Microsoft dipped in 2024, as large support renewals from the Department of Justice (DOJ) and Department of State that occurred in 2023 and have since expired. Meanwhile, Oracle’s jump in 2024 almost entirely reflects Cerner-related services for the Department of Veterans Affairs (VA). Though AWS does not have the legacy software ties that Microsoft and Oracle do, the company is very competitive in the market. In 2024 AWS saw a big jump in defense-related wins, including those associated with the Defense Information Systems Agency (DISA) and the JWCC contract. Other notable prime awards for AWS during this time include the National Nuclear Security Administration, within the Department of Energy, which is leveraging S3 and other IaaS services.

 

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Attributes related to vendors’ ability to execute on DT promises reflect changing buyer priorities from a year ago and send a strong message that vendors should not take relationships for granted

Main criteria for selecting digital transformation (DT) services vendors

Working knowledge of buyers’ IT infrastructure, digital-related security and privacy issues, and specific line of business or domain ranked as the top three attributes for vendor selection. The ranking was a major reshuffling from 2023, when industry knowledge, value-to-price, and complete line of professional services ranked as the top attributes. The change highlights buyers’ evolving priorities. While a year ago the attributes were oriented toward convincing stakeholders to spend on DT programs, this year it appears as though buyers are looking for vendors that can execute on the programs, aligning with the increase in overall DT spend. Existing vendor relationship remained the least critical attribute for vendor selection, underscoring that no single vendor’s position is guaranteed and that vendors must account for evolving stakeholder expectations.

Addressing common gaps such as technical expertise could help vendors build a foundation around scale and quality as GenAI adds another layer of complexity that has to be tied to business outcomes

Customer recommendations for DT services vendors by region

Improving technical expertise remained among the top recommendations across regions for vendors to consider, which reflects the IT fluency of DT buyers and illustrates portfolio and skills gaps vendors struggle with despite ongoing investments. Other common recommendations, such as GenAI knowledge tied to business operations, also underscore the need for vendors to find a way to balance their technology-led discussions with business process knowledge, especially as the majority of buyers’ budgets are shifting back to business and tech advisory services. Supporting and taking responsibility for enterprises’ IT environments cannot be done in a vacuum, and vendors need to account for the impact of broader stakeholder ecosystems, especially as the adoption of emerging technologies increases the level of complexity. This is particularly the case among EMEA buyers, who ranked vendors’ expertise in ecosystem management within the top five recommended improvements, highlighting the importance of collaborating with regional vendors as a critical link in otherwise fragmented European-sourced opportunities. In comparison, APAC and North American buyers see a gap in vendors’ ability help them understand the impact of AI on the business, creating an opportunity for providers with strong consulting skills that can also demonstrate business outcomes through proven use cases.

ESIs and acquisitions — strategies that work

Successful M&A strategies follow one of two cadences in TBR’s research: constant or infrequent. In-between approaches or inconsistent cadences fail to deliver expected returns on investment and do not support sustained revenue growth.
Most ESIs that have doubled their revenues post-pandemic have acquired at an Accenture-like pace, adding complementary capabilities and/or expanding into new geographies (e.g., Persistent and Stefanini). In contrast, some ESIs have maintained high revenue-per-employee results in part by eschewing frequent acquisitions in favor of more organic growth (e.g., Ensono and Protiviti).

Why are these two opposite approaches successful? Evaluating, financing, acquiring, absorbing and bringing to market new assets requires experience that builds muscle memory. Do it often and get good at it or do it rarely so you are not wasting time and money. Inconsistency leads to uncertainty and inefficiencies.

Increasingly, according to TBR’s research, an approach favored by some global systems integrators (GSIs) and consultancies appears appealing to ESIs: invest, do not buy. Most ESIs cannot match GSIs’ dollars invested in corporate venture capital funds or startup incubators, but ESIs can emulate the business model. Investing in niche technology or complementary services providers demonstrates differentiation in a crowded field and potentially provides additional revenue streams.

Increasingly, ESIs will invest in startups and boutiques, expanding their portfolios without the costs of acquisitions and realizing new revenue streams.

ESIs and technology partners — ESI perspective

In TBR’s research, successful SI partnerships with technology vendors require the SI to understand and align with the technology vendor’s sales team. Clear incentive and compensation structures lead to smoothly functioning go-to-market initiatives.

ESIs, by their nature, can be more flexible than GSIs and can benefit from being named the best SI partner in their particular country or for their particular skills. GSIs can compete for global accolades while ESIs show their technology partners the benefits of more local recognition.

Of cloud and software respondents, 33% said, “We use niche providers for small and midsize clients as they offer better pricing flexibility and domain expertise.” 
“I want to work with all the major technology companies, but I work with smaller niche companies too. So, when we were rationalizing who to work with and who not to work with, ultimately, it comes down to the TAM [total addressable market]. I want some revenue potential behind any new partners, and any new go-to-market offerings. So that’s what kind of the think tank is deciding behind the scenes.” — Senior Manager of Global Channels and Alliances, Cloud—TBR’s Summer 2025 Voice of the Partner Ecosystem Report

ESIs face core challenges similar to GSI, namely how to differentiate and get technology partners to recommend and even sell an ESI’s services. Without expecting technology partners’ sales teams to be fluent in an ESI’s offerings and value propositions, ESIs can sell themselves in three ways:

• Offer flexible and responsive commercial models that play to tech partners’ metrics and compensation models
• Provide access to personas and buyers that tech partners cannot reach, such as enterprise business line leaders or wholly new logos
• Augment with highly specialized and responsive talent when tech partners’ own professional services teams are stretched too thin

TBR Spotlight Reports represent an excerpt of TBR’s full subscription research. Full reports and the complete data sets that underpin benchmarks, market forecasts and ecosystem reports are available as part of TBR’s subscription service. Click here to receive all new Spotlight Reports in your inbox.

 

AI data needs raise expectations about how services vendors and hyperscalers should be thinking about their relationships, with region-specific guardrails further testing joint GTM durability

Key trends
Hyperscalers’ dispersion across the globe requires these vendors, along with their services partners, to carve out new operating models that prioritize both go-to-market success and adherence to local requirements. This balance translates into a case-by-case — or rather, country-by-country — approach with local partnerships being the common thread. This is especially true for hyperscalers competing for local market share — particularly in the European Union (EU) — to the extent of relinquishing operational control (e.g., Microsoft Bleu), creating a direct opportunity for regional system integrators (SIs) and local infrastructure operators. While global SIs (GSIs) are also in contention, they must account for these vendors as they build out local presence, along with their commercial, staffing and partner models. Meanwhile, regional legislation is pushing hyperscalers to commit to investment pledges to ensure business continuity, with implications for services partners and buyers, further testing the limits of their relationships.

Go-to-market strategy
Enterprise buyers are becoming increasingly conflicted in their expectations of how vendors can best support their technology needs. When it comes to interoperability, many customers look to leverage third-party vendors, and a smaller percentage expect their cloud vendors to address these concerns directly. At the same time, buyers continue to identify technology expertise as a key skills gap in vendors’ value proposition across regions. These dynamics are further amplified in vendors’ regional go-to-market strategies, especially when it comes to accounting for the role of AI and niche vendors that bring specialized knowledge. In a nutshell, vendors cannot rely on a one-size-fits-all AI ecosystem strategy across regions. Success will require region-specific approaches: IP-led initiatives in APAC, orchestration frameworks in Europe, and startup-centric marketplaces in the Americas. All must be underpinned by interoperable APIs and strong governance to help IT services providers capture and monetize local demand. Executing against such expectations while continuing to rely on a traditional labor-arbitrage model will test professional services firms’ readiness to transform their own operations while maintaining trust with hyperscalers, which continue to explore the opportunity to drive professional services revenue by simplifying the sales process and marketplace through the use of agentic AI.

Vendors
In addition to launching bespoke operating models and investing in local infrastructure, hyperscalers are investing at the infrastructure layer to support workload portability and management capabilities that help customers adhere to sovereignty regulations. Google Distributed Cloud is probably the most sovereignty-forward example, but similar comparisons can be made for both Microsoft and Amazon Web Services (AWS). Security is another critical area hyperscalers are investing in, whether it is Microsoft’s new deputy chief information security officer (CISO) role for Europe or Google’s continued effort to expand Mandiant’s assets to prevent breaches. Orchestrating these evolving offerings into a cohesive IT estate will be an opportunity for services vendors, especially when deciding how to configure them in a way that is suitable for country-specific needs. Services — including migration, implementation, consulting and advising — all play a role in navigating the increasingly complex regulatory and security environment, requiring broad hiring in the EU, where the opportunities are the greatest.

Data location will remain a leading barrier to cloud adoption, but interoperability and breaking down data barriers across platforms will present the bigger opportunity for services vendors

As highlighted in TBR’s 2H24 Cloud Infrastructure & Platforms Customer Research, data location ranked as the second-highest cloud pain point after security, with 40% of respondents expecting their cloud vendors to directly address these concerns — largely due to vendors doing a better job of making customers aware of the various data center hosting and encryption options. Conversely, when it comes to interoperability, many customers will leverage third-party vendors, and a smaller percentage expect their cloud vendors to address these concerns directly. This speaks to both the skills that services-led firms have amassed across multiple technology platforms and the high degree of lock-in the hyperscalers still create across their infrastructure. That said, from a technology perspective, vendors are doing a better job of integrating their offerings, particularly in the area of agentic AI, which necessitates more robust data sharing. As more open frameworks, including Google’s A2A (Agent2Agent), mature and become enterprise-ready, they could create a needed level of standardization that GSIs can leverage to build new agents alongside their ISV partners. Deloitte’s partnership with Google Cloud to build ServiceNow-specific agents on A2A is a good example.

“It [sovereign cloud] helps, significantly helps. A completely separated, air-gapped environment different from the regular public cloud itself. And Switzerland, by the way, is a great example. AWS put up two regions in Switzerland. It’s a tiny country. But even then, they had two regions to satisfy this condition of resilience, etc.” — Managing Director (Firmwide) & Chief Data Architect, Financial Services

Cloud vendor insights excerpt

Microsoft’s Cloud Services & Ecosystem Strategy

 

TBR Spotlight Reports represent an excerpt of TBR’s full subscription research. Full reports and the complete data sets that underpin benchmarks, market forecasts and ecosystem reports are available as part of TBR’s subscription service. Click here to receive all new Spotlight Reports in your inbox.

 

CSPs have an opportunity to capture meaningful value from AI, but realizing this opportunity requires action and investment

Most CSPs look for quick-hit ROI from GenAI; there is still hesitancy to commit to larger-scope AI initiatives that require significant upfront investment

Leading CSPs are all dabbling with GenAI, with some use cases already commercially scaling, especially in customer care and BSS.

CFOs at some leading CSPs are getting directly involved in AI programs to give visibility to these initiatives and ensure they are paying off, looking for quick ROI.

So far, CSP managers like what they are seeing and are hopeful about the prospects of AI delivering significant outcomes, but this hope has yet to translate to large-scale investments tied to broad transformations. Rather, CSPs are focused on more tactical, smaller-scope solutions that address specific pain points or that promise fast ROI.

TBR believes it will take some time for most CSPs to evolve this investment behavior, but some other considerations also need to be factored into the equation, such as uncertainty about governance, regulation and data efficacy. For example, AI’s effectiveness correlates closely with the volume and quality of the data input into the model. The reality is that data inside CSP organizations are usually highly disaggregated in silos and on legacy systems, which poses a major challenge to undergoing large-scale AI transformations.

Realizing the $170 billion total opportunity TBR estimates AI presents the telecom industry by 2030 requires CSPs to act differently

AI presents a once-in-a-generation opportunity for the telecom industry to achieve two key objectives: generate new revenue and reduce costs.

However, there is real risk that most CSPs globally will miss out on the AI opportunity due to cultural (behavioral) and regulatory encumbrances, such as long decision cycles, an unwillingness to invest what it takes to win and general risk aversion. These encumbrances, which are endemic to the telecom industry, have resulted in CSPs largely missing out on every major opportunity in the last two decades (e.g., cloud computing opportunity, video streaming opportunity, digital advertising opportunity), many of which were won by the hyperscalers that were willing and able to take these risks.

Though leading CSPs have been investing in AI, TBR notes that most of these investments seem to be myopically focused on quick-hit wins, which is acceptable in the short term, but true opportunity capture will be contingent on broader-scope initiatives, coupled with upfront investment.

CSPs cannot afford to miss out on another opportunity, especially one that has such transformational qualities as AI. Getting AI right should be of paramount concern to CSPs, as competitors that transform with AI may obtain unapproachable differentiation compared to CSPs that do not invest in AI. Said differently, CSPs that do not get AI right may not be competitive anymore, leading to longer-term questions about their viability.

CFOs need to evangelize AI across their organizations to seize this critical opportunity. True digital transformation with AI will require significant upfront investment, and the payoff of some investments take a longer time to realize than others. CFOs need to balance investment levels with outcomes, but more support is needed from the top to approach AI in a broader manner.

TBR notes that of the $170 billion CSP AI opportunity by 2030, an estimated 50% is likely to be realized in APAC, where there are many CSPs aiming to take a leadership role in the AI market. The lack of domestic hyperscalers (outside of the U.S. and China) and government desire to have sovereignty over technologies of national importance gives CSPs an opportunity to fill in the gaps in the market. China-based CSPs are already diving headfirst into the AI opportunity, and they are likely to generate billions of dollars in new revenue and save billions of dollars in costs from AI by 2030.

Telcos have a data usability problem, which could slow the pace of AI adoption in their businesses; addressing this issue requires significant additional investment

CSPs have a data preparedness problem, which is an underestimated issue and will be costly to rectify

The efficacy of and value provided by AI are contingent on the quality, type and volume of data the AI model is trained on. It is therefore imperative that CSPs ensure their data is ready for AI and that the data is managed and governed in a sustainable way. This is especially pertinent now that GenAI can train on a broad range of structured and unstructured data.

The reality is that CSPs’ data does not reside in one data lake. Rather, it is highly disaggregated and siloed across the organization and, in some cases, may be incomplete. There are also restrictions (e.g., regulatory, privacy) and security considerations around certain types of data, which hinder the utility and accessibility of the data, creating another major challenge that companies will have to address before they can appropriately leverage AI.

Individual CSPs have access to petabytes of data, but most of this data resides in legacy systems and/or is subject to other restrictions, creating challenges around pooling and preparing the data to be leveraged for AI.

To rectify this issue, CSPs will need to clean up their technical debt and assemble their data in a single, unified platform. This horizontal data layer will be required to run and realize AI-driven outcomes at scale. Most CSPs will likely need assistance with this task, opening up opportunities for the vendor community.

Addressing this issue will also require significant investment and human resources, and TBR believes CSPs that are in the initial stages of their GenAI initiatives have underestimated or overlooked the problem.

TBR believes this issue could extend CSPs’ timelines for AI commercialization. Vendors and hyperscalers will try to mitigate the data issue by training AI models on their own datasets, which could also be fed by partners’ data, but there is a risk that this will not be sufficient and that AI models will need to be tuned to a specific CSP’s needs to realize desired outcomes. TBR also believes it will be common for stakeholders in the telecom ecosystem to be protectionist regarding their data, not wanting to (or being able to) share their data for fear of regulatory reprisals and a nullification of competitive advantages.

Sovereign cloud requirements have the potential to be a meaningful revenue driver for CSPs in select regions and countries

Countries (e.g., China, Saudi Arabia, Qatar, United Arab Emirates, South Korea) and alliance entities (e.g., NATO) that are more impacted by geopolitics and/or have strong data privacy rules and regulations (e.g., European Union [EU] member countries) are looking into establishing national AI infrastructure (e.g., data centers), also referred to as sovereign cloud.

Sovereign clouds would theoretically be set up and managed by domestic players for national security reasons and could be an area of opportunity for CSPs that reside in those countries or regions, whereby the CSP might host the cloud and provide some value-added services to manage those environments on behalf of the government and related entities.

However, TBR ultimately believes it is more likely that U.S. hyperscalers will participate in some way in the AI value chain for most countries given the broad scope of their involvement and dominance in the global AI ecosystem, despite intentions for national sovereignty. This includes CSPs partnering with hyperscalers to jointly develop, operate and manage cloud resources in-country, as evidenced by Orange’s use of Microsoft’s cloud and AI technology for its sovereign cloud joint venture with Capgemini (called Bleu) in France.

TBR estimates the potential annual AI-related opportunity for CSPs will reach $170B by 2030, approximately 53% of which is new revenue and 47% is cost efficiencies

CSPs have been largely sidelined from the new revenue opportunity presented by AI since the emergence of GenAI in 4Q22, but this is starting to change, evidenced by significant deals won by Lumen and Zayo to provide transport between data centers for AI workloads. There are also some green shoots of demand for hyperscalers to leverage CSPs’ network facilities (e.g., wire centers and central offices) and other real estate assets to colocate AI infrastructure closer to end users, as evidenced by efforts being made by Verizon and AT&T.

All CSPs that are investing in AI currently expect to reap cost efficiencies from the technology. The new revenue opportunity is more nuanced and is CSP- and market- specific in nature. APAC-based CSPs are likely to be the largest beneficiaries of new revenue from AI due to government protections, stimulus and cultural orientations toward early adoption of emerging technologies.