Cloud Components Benchmark

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Behind healthy server backlog and new software IP, hardware vendors drive the cloud components market, particularly as software pure plays prioritize entirely public cloud migrations

Hardware-centric vendors continue to make their move into software

Over the past several years, the cloud software components market has shifted. Microsoft and Oracle are no longer dominating the market as they prioritize their native tool sets and encourage customers to migrate to public cloud infrastructure. Driven largely by weaker-than-expected purchasing around Microsoft Windows Server 2025, aggregate revenue growth for these two software-centric vendors was down 3% year-to-year in 3Q24. Over the same compare, total software components revenue for the benchmarked vendors was up 14% and total cloud components revenue was up 8%. In some ways, this dynamic has made room for hardware-centric vendors such as Cisco and Hewlett Packard Enterprise (HPE) to move deeper into the software space, particularly as they buy IP associated with better managing orchestration infrastructure in a private and/or hybrid environment.

Backlog-to-revenue conversion for AI servers fuels market growth

Though revenue mixes are increasingly shifting in favor of software, driven in part by acquisitions (e.g., Cisco’s purchase of Splunk), hardware continues to dominate the market, accounting for 80% of benchmarked vendor revenue in 3Q24. Industry standard servers being sold to cloud and GPU “as a Service” providers are overwhelmingly fueling market growth, more than offsetting unfavorable cyclical demand weakness in the storage and networking markets. This growth is largely driven by the translation of backlog into revenue, but vendors are still bringing new orders into the pipeline, which speaks to ample demand from both AI model builders and cloud providers. However, large enterprises are increasingly adopting AI infrastructure as part of a private cloud environment to control costs and make use of their existing data.

Graph: Cloud Revenues by Segment for 3Q23-3Q24 (Source: TBR)

Cloud Revenues by Segment for 3Q23-3Q24 (Source: TBR)

 

Ample scale and strong demand from both CSPs and enterprises extend Dell’s lead in the cloud components market

Cloud components vendor spotlights

Dell Technologies [Dell]

From a revenue perspective, HPE and Cisco once threatened Dell’s cloud components leadership, but the company has been able to distance itself from its nearest competitors. This is largely due to Dell’s performance over the past year, with strong server demand, particularly from Tier 2 cloud service providers (CSPs), propelling the company’s corporate and cloud components revenue growth rate to the double digits. Meanwhile, in 3Q24 Dell shipped $2.9 billion worth of AI servers while backlog reached $4.5 billion, reflecting 181% year-to-year growth during the quarter and indicating strong future revenue performance.

Hewlett Packard Enterprise

Like its peers, HPE is benefiting from AI-related server demand, and in 3Q24 the company reported $1.5 billion in total AI systems revenue. HPE continues to benefit from its ongoing efforts to shift the sales mix in favor of software and services via GreenLake. In 3Q24 HPE completed its acquisition of Morpheus Data, officially equipping HPE with a suite of infrastructure software that allows customers to take core hypervisors, such as KVM and VMware, and use them to build complete private cloud stacks.

Cisco

With its acquisition of Splunk, Cisco has emerged as the leader of the software components market, even surpassing Microsoft in related revenue. But networking still accounts for the bulk of Cisco’s components business, and, as evidenced by a 32% year-to-year decline in total hardware revenue for 3Q24, Cisco is facing headwinds in the core networking business. That said, the company is actively taking steps to build out its portfolio, particularly by integrating more security components into the networking layer, which is where most cyberattacks originate, to boost its long-term competitiveness in the market.

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Infrastructure agnosticism and flexible cloud-enabled delivery are core attributes of the service delivery market, cementing IBM’s leadership

Dedicated orchestration tools continue to have their place in the market, both in on-premises and cloud environments, but growth is largely driven by application lifecycle management and orchestration tools that span multiple environments. IBM has a rich history in this space and remains a revenue leader. Cisco used to have a foothold in the market but no longer sells its CloudCenter suite.

Vendor spotlight: IBM

After taking steps to bring watsonx into Maximo in 2Q24 for greater process automation, IBM strengthened its commitment to the asset performance management space with the acquisition of Prescinto. Prescinto offers AI tools and accelerators designed for asset owners and operators with a focus on renewable energy and operators. This deal is designed to support IBM’s play in certain verticals, particularly energy and utilities.

Graph: Service Delivery and Orchestration Revenue Growth vs Cloud Software Components Revenue Growth for 3Q24 (Source: TBR)

Service Delivery and Orchestration Revenue Growth vs Cloud Software Components Revenue Growth for 3Q24 (Source: TBR)

 

AI PC and AI Server Market Landscape

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Despite hyperscalers’ increasing investments in custom AI ASICs, TBR expects demand for GPGPUs to remain robust over the next 5 years, driven largely by the ongoing success of NVIDIA DGX Cloud

The world’s largest CSPs, including Amazon, Google and Microsoft, remain some of NVIDIA’s biggest customers, using the company’s general-purpose graphics processing units (GPGPUs) to support internal workloads while also hosting NVIDIA’s DGX Cloud service on DGX systems residing in the companies’ own data centers.
 
However, while Amazon, Google and Microsoft have historically employed some of the most active groups of CUDA developers globally, all three companies have been actively investing in the development and deployment of their own custom AI accelerators to reduce their reliance on NVIDIA. Additionally, Meta has invested in the development of custom AI accelerators to help train its Llama family of models, and Apple has developed servers based on its M-Series chips to power Apple Intelligence’s cloud capabilities.
 
However, even as fabless semiconductor companies such as Broadcom and Marvell increasingly invest in offering custom AI silicon design services, only the largest companies in the world have the capital to make these kinds of investments. Further, only a subset of these large technology companies engage in the type of operations at scale that would yield measurable returns on investments and total cost of ownership savings. As such, even as investments rapidly rise in the development of customer AI ASICs, the vast majority of customers continue to choose NVIDIA’s GPGPUs due to not only their programming flexibility but also the rich developer resources and robust prebuilt applications comprising the hardware-adjacent side of NVIDIA’s comprehensive AI stack.
 

Graph: Data Center GPGPU Market Forecast for 2024-2029 (Source: TBR)

Data Center GPGPU Market Forecast for 2024-2029 (Source: TBR)


 

Companies across a variety of industry verticals want to take a piece of NVIDIA’s AI cake

Scenario Discussion: NVIDIA faces increasing threats from both industry peers and partners

NVIDIA GPGPUs are the accelerator of choice in today’s AI servers. However, the AI server and GPGPU market incumbent’s dominance is increasingly under threat by both internal and external factors that are largely related. Internally, as Wall Street’s darling and a driving force behind the Nasdaq’s near 29% annual return in 2024, NVIDIA’s business decisions and quarterly results are increasingly scrutinized by investors, forcing the company to carefully navigate its moves to maximize profitability and shareholder returns. Externally, while NVIDIA positions itself largely as a partner-centric AI ecosystem enabler, the number of the company’s competitors and frenemies is on the rise.
 
Despite NVIDIA’s sequentially eroding operating profitability, investor scrutiny has not had a clear impact on the company’s opex investments — evidenced by a 48.9% year-to-year increase in R&D spend during 2024. However, it may well be a contributing factor to the company’s aggressive pricing tactics and rising coopetition with certain partners. While pricing power is one of the luxuries of having a first-mover advantage and a near monopoly of the GPGPU market, high margins attract competitors and high pricing drives customers’ exploration of alternatives.
 
Additionally, the fear of vendor lock-in among customers is something that comes with being the only name in town, and while there is not much most organizations can do to counteract this, NVIDIA’s customers include some of the largest, most capital-rich and technologically capable companies in the world.
 
To reduce their reliance on NVIDIA GPUs, hyperscalers and model builders alike have increasingly invested in the development of their own custom silicon, including AI accelerators, leveraging acquisitions of chip designers and partnerships with custom ASIC developers such as Broadcom and Marvell to support their ambitions. For example, Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP) and Meta have their own custom AI accelerators, and OpenAI is reportedly working with Broadcom to develop an AI ASIC of its own. However, what these custom AI accelerators have in common is their purpose-built design to support company-specific workloads, and in the case of AWS, Azure and GCP, while customers can access custom AI accelerators through the companies’ respective cloud platforms, the chips are not physically sold to external organizations.
 
In the GPGPU space, AMD and, to a lesser extent, Intel are NVIDIA’s direct competitors. While AMD’s Instinct line of GPGPUs has become increasingly powerful, rivaling the performance of NVIDIA GPGPUs in certain benchmarks, the company has failed to gain share from the market leader due largely to NVIDIA CUDA’s first-mover advantage. However, the rise of AI has driven growing investments in alternative programming models, such as AMD ROCm and Intel oneAPI — both of which are open source in contrast to CUDA — and programming languages like OpenAI Triton. Despite these developments, TBR believes NVIDIA will retain its majority share of the GPGPU market for at least the next decade due to the momentum behind NVIDIA’s closed-source software and hardware optimized integrated stack.
 

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Microsoft Copilot+ PCs represent a brand-new category and opportunity for Windows PC OEMs industrywide

PC OEMs expected the post-pandemic PC refresh cycle to begin in 2023, but over the past 18 months, their expectations have continually been delayed, with current estimates indicating the next major refresh cycle will ramp sometime in 2025. While the expected timing of the refresh cycle has changed, the drivers have remained the same, with PC OEMs expecting that the aging PC installed base, the upcoming end of Windows 10 support — slated for October 2025 — and the introduction of new AI PCs will coalesce, driving meaningful rebounds in the year-to-year revenue growth of both the commercial and consumer segments of the PC market.
 
As organizations graduate from Windows 10 devices to Windows 11 devices, TBR expects many customers will opt for AI PCs to future-proof their investments, understanding that the overall commercial PC market will be dominated by devices powered by Windows AI PC SoCs in a few years’ time. However, while TBR expects the Windows AI PC market to grow at a 44.3% CAGR over the next five years, the driver of this robust growth centers on the small revenue base of Windows AI PCs today.
 
While Apple dominated the AI PC market in 2024 due to the company’s earlier transition to its own silicon platform — the M Series, which features onboard NPUs — TBR estimates indicate that among the big three Windows OEMs, HP Inc.’s AI PC share was greatest in 2024, followed closely by Lenovo and then Dell Technologies. Without an infrastructure business, HP Inc. relies heavily on its PC segment to generate revenue, and as such, TBR believes that relative to its peers — and Dell Technologies in particular — HP Inc. is more willing to trade promotions and lower margins for greater number of sales, which is a key factor in the current increasingly price-competitive PC market. TBR estimates Lenovo’s second-place positioning is tied to the company’s growing traction in the China AI PC market, where the company first launched AI PCs leveraging a proprietary AI agent in a region where Microsoft Copilot has no presence.
 

Graph: Windows AI PC Market Forecast for 2024-2029 (Source: TBR)

Windows AI PC Market Forecast for 2024-2029 (Source: TBR)

The PC ecosystem increases its investments in developer resources to unleash the power of the NPU

 
Currently available AI PC-specific applications, such as Microsoft Copilot and PC OEMs’ proprietary agents, are focused primarily on improving productivity, which drives more value on the commercial side of the market compared to the consumer side. However, it is likely more AI PC-specific applications will be developed that harness the power of the neural processing unit (NPU), especially as AI PC SoCs continue to permeate the market.
 
Companies across the PC ecosystem, including silicon vendors, OS providers and OEMs, are investing in expanding the number of resources available to developers to support AI application development and ultimately drive the adoption of AI PCs. For example, AMD Ryzen AI Software and Intel OpenVINO are similar bundles of resources that allow developers to create and optimize applications to leverage the companies’ respective PC SoC platforms and heterogenous computing capabilities, with both tool kits supporting the NPU, in addition to the central processing unit (CPU) and GPU.
 
However, as it relates to AI PCs, TBR believes the NPU will be leveraged primarily for its ability to improve the energy efficiency of certain application processes, rather than enabling the creation of net-new AI applications. While the performance of PC SoC-integrated GPUs pales in comparison to that of discrete PC GPUs purpose-built for gaming, professional visualization and data science, the TOPS performance of SoC-integrated GPUs typically far exceeds that of SoC-integrated NPUs, due in part to the fact that the processing units are intended to serve different purposes.
 
The GPU is best suited for the most demanding parallel processing functions, requiring the highest levels of precision, while the NPU is best suited for functions that prioritize power efficiency and require lower levels of precision, including things like noise suppression and video blurring. As such, TBR sees the primary value of the NPU being extended battery life — an extremely important factor for all mobile devices. This is the key reason why TBR believes that AI PC SoCs will gradually replace all non-AI PC SoCs, eventually being integrated into nearly all consumer and commercial client devices.
 
One of the reasons PC OEMs are so excited about the opportunity presented by AI PCs is that AI PCs command higher prices, supporting OEMs’ longtime focus on premiumization. Commercial customers, especially large enterprises in technology-driven sectors like finance, typically buy more premium machines, while consumers generally opt for less expensive devices, and TBR believes this will be another significant driver of AI PC adoption rising in the commercial segment of the market before the consumer segment.

DOGE Federal IT Vendor Impact Series: General Dynamics Technologies

The Trump administration and its Department of Government Efficiency (DOGE) have generated massive upheaval across the board in federal operations, including in the federal IT segment. As of March 2025, thousands of contracts described by DOGE as “non-mission critical” have been canceled, including some across the federal IT and professional services landscape. TBR’s DOGE Federal IT Vendor Impact Series explores vendor-specific DOGE-related developments and impacts on earnings performance. Click here to receive upcoming series blogs in your inbox as soon as they’ve published.

 

Demand for digital accelerators grows despite federal IT market uncertainty

Although the Department of Government Efficiency (DOGE) claims to have canceled at least six of General Dynamics’ contracts during 1Q25 and the U.S. General Services Administration (GSA) has instructed agencies to scrutinize their work with General Dynamics Information Technology (GDIT) to determine whether it is truly essential, General Dynamics Technologies (GDT) posted better numbers than expected. When General Dynamics released its 1Q25 fiscal results on April 23, it revealed that GDT’s quarterly revenue was $3.4 billion, up 6.8% year-to-year and 5.9% sequentially.
 
GDIT drove this expansion, with its revenue of $2.36 billion surging 9.2% year-to-year and 7.2% sequentially. While the acquisition of Iron EagleX in 3Q24 provided mild inorganic revenue contributions, demand increased rapidly for its growing portfolio of digital accelerators: Comet 5G, Coral Software Factory, Cove AI Operations, Eclipse Defensive Cyber, Ember Digital Engineering, Everest Zero Trust, Hive Hybrid Multicloud, Luna AI and Tidal Post-Quantum Cryptography.
 
GDT’s operating margin also benefited from this uptick in volume for GDIT as well as General Dynamics Mission Systems offerings, improving 40 basis points year-to-year to 9.6% in 1Q25. However, GDT’s operating margin declined 20 basis points on a sequential basis as IT services are becoming a more prominent component of its portfolio mix, rather than high-margin defense electronics, as Mission Systems continues to reshuffle its portfolio mix.
 
While General Dynamics’ backlog decreased on a sequential and year-to-year basis, GDT’s backlog of $14.4 billion was actually up 6.7% year-to-year and 1.8% sequentially. GDT’s bookings were notably robust, with the segment achieving a book-to-bill ratio of 1.1:1, indicating that disruptions to its $120 billion pipeline of opportunities have been minimal despite the new headwinds. While GDT flagged its win and captures rate as being in the 80% range, its leadership highlighted that the solicitation, proposal and award process have been slowing down across the market as the Trump administration refines its long-term goals.

How GDT will navigate 2025

Since GDIT secured two wins in the federal health market worth approximately $3 billion in the second half of 2023, the segment has continued to ramp up its efforts to diversify its non-DOD (Department of Defense) revenue base. For example, GDIT secured a contract worth up to $286 million in 4Q24 to keep enhancing the Centers for Medicare & Medicaid Services’ (CMS) Benefits Coordination & Recovery Center by weaving in emerging technologies like AI to streamline the center’s operations.
 
GDIT formally established a Federal Health practice toward the end of 2024, signaling its intent to create deeper ties to agencies within the Department of Health and Human Services (HHS). Although GDT’s non-DOD revenue growth has gained momentum, expanding 8.8% year-to-year in 4Q24 and 5.3% year-to-year in 1Q25, DOGE’s actions may complicate things, given that the bulk of GDT’s canceled contracts thus far have been tied to HHS.
 
Additionally, GDIT’s consulting services have drawn the ire of the GSA. GDIT is one of the 10 vendors the GSA has identified as being set to receive more than $65 billion in 2025 and beyond. The GSA has requested that agencies go through their contracts with these vendors and outline which are mission critical and why. GDIT has been actively working with clients to identify ways to reduce costs and enable efficiencies through technology. Although consulting offers a lucrative avenue for GDIT to expand its margins and build upon its existing relationships with clients, the vendor still prioritizes delivering solutions and IT services in its go-to-market strategy.
 
GDT is not going to give up on the federal health market or on consulting, but TBR anticipates the vendor will increasingly prioritize defense opportunities in the interim, such as a recently awarded contract worth up to $5.6 billion to manage the DOD’s Mission Partner Environment. The DOD has historically been GDT’s largest client and was responsible for more than 58% of its revenue in 1Q25.
 
While the Trump administration is asking for a 23% reduction in nondefense discretionary funding in its FFY26 budget proposal, it wants to keep the DOD’s discretionary spending roughly on par with the $892.5 billion stopgap for FFY25. GDIT is well positioned to capitalize on the DOD becoming increasingly interested in emerging technologies, given its experience with fixed-price and outcome-based contracting. Additionally, GDIT can offer defense and intelligence clients its array of digital accelerators to help offset the disruptions in the federal civilian market.
 
These digital accelerators were responsible for more than $2 billion of the total contracts that GDIT won during 2023. In 2024 GDIT continued to build out its array of digital accelerators and generated nearly $7.5 billion in awards from them. GDIT’s go-to-market strategy is reliant on these digital accelerators.
 
To continue gaining traction with defense as well as civilian clients, GDIT will need to keep leveraging its partners to enhance these solutions and make inroads in these markets. GDIT suddenly began ramping up its alliance activity during 2H24 and has continued to do so. For example, GDIT is augmenting its Cove AI Ops Digital Accelerator with ServiceNow’s AI and machine learning platform to make agencies’ systems more efficient.

TBR’s outlook for GDT

At the end of 4Q24, GDT tendered full-year revenue guidance for 2025 sales of $13.5 billion, implying growth of approximately 2.8% over 2024 sales of $13.1 billion. As is tradition, General Dynamics did not update its guidance for GDT this early in the fiscal year.
 
TBR remains skeptical of GDT’s guidance, given the lack of synergy between GDIT and MS. The latter will continue to transition its portfolio mix from legacy programs to newer initiatives after starting this arduous process in 2024, and GDIT is tasked with driving revenue expansion during this process.
 
Although GDIT is leveraging the demand for AI and other emerging technologies, the uncertainty in the federal IT market and the segment’s own small-scale portfolio transition could impede the growth needed to offset Mission Systems’ performance. The impact of the Trump administration’s sudden and aggressive adoption of tariffs also increases the likelihood of supply chain bottlenecks and significant program delays.
 
For these reasons, TBR believes that GDT’s guidance for an operating margin of 9.2% could be too lofty, and we anticipate its operating margin could decline from 9.6% in 2024 to 8.9% in 2025. TBR conservatively believes that GDT’s revenue will expand approximately 2% over 2024 sales of $13.1 billion in 2025.

 

TBR’s DOGE Federal IT Impact Series will include analysis of Accenture Federal Services, General Dynamics Technologies, CACI, IBM, CGI, Leidos, IFC International, Maximus, Booz Allen Hamilton and SAIC. Click here to download a preview of our federal IT research and receive upcoming series blogs in your inbox as soon as they’ve published.

 

DOGE Federal IT Vendor Impact Series: IBM Federal

The Trump administration and its Department of Government Efficiency (DOGE) have generated massive upheaval across the board in federal operations, including in the federal IT segment. As of March 2025, thousands of contracts described by DOGE as “non-mission critical” have been canceled, including some across the federal IT and professional services landscape. TBR’s DOGE Federal IT Vendor Impact Series explores vendor-specific DOGE-related developments and impacts on earnings performance. Click here to receive upcoming series blogs in your inbox as soon as they’ve published.

 

DOGE’s aggressive cost-cutting activities impacted IBM-Fed* in 1Q25

IBM tendered its 1Q25 earnings on April 23, and while the company does not disclose fiscal data about the federal operations of IBM Consulting, IBM’s executives did provide useful color on IBM-Fed and the impact of DOGE. Not surprisingly, IBM-Fed’s contracts with the U.S. Agency for International Development (USAID), much maligned by the Trump administration, suffered cancellations and drawdowns.
 
According to the DOGE-Terminated Contracts Tracker on the GX2 website, which tracks developments in federal contracting, IBM-Fed has had a total of $40.1 million in contracts terminated by DOGE as of the publication of this blog. Cancellations included awards with the Department of the Treasury ($17.5 million in TCV), the Department of Health & Human Services ($3.4 million in TCV), the Commerce Department ($1.3 million in TCV), and the Department of Education ($18 million in TCV). Without disclosing specific revenue data for IBM-Fed, IBM noted that its federal business accounts for less than 5% of IBM’s total corporate revenue and less than 10% of IBM Consulting sales, or, according to TBR estimates, about $490 million in 1Q25, up 3% year-to-year.
 
We note that none of the USAID awards terminated or scaled back by DOGE were listed on the GX2 website. IBM CFO Jim Kavanaugh indicated during the 1Q25 earnings call that IBM-Fed had a “handful of contracts” canceled by DOGE, affecting about $100 million worth of contracts in IBM Consulting’s $30 billion (on an annualized basis) backlog.

The advisory business within IBM-Fed bore the brunt of DOGE-based pressures; the company’s core technology operations may have largely been spared

IBM indicated during the earnings call that 40% of IBM-Fed’s revenue stems from technology-focused work described as “high-value annuitized revenue under contract” and, by implication, is so far unscathed by DOGE. IBM-Fed blends its hybrid cloud, AI and security technologies to offer federal agencies a suite of transformative solutions that are very technology-centric and mission-enabling by nature. Conversely, 60% of IBM-Fed’s sales derive from advisory-based work, which company executives noted during the earnings call would be “more susceptible to discretionary efficiency-type programs.”
 
Based on data about IBM-Fed’s canceled contracts on the GX2 website, we believe the advisory work affected by DOGE included cloud transition and support services, data standards testing and implementation, data quality support services, the acquisition and implementation of integrated workplace management system licenses, and “data at rest” support services (i.e., data that is stored and not being actively used or transmitted). Other contracts were “terminated for convenience,” according to the GX2 website, which did not provide a specific description of the canceled services.
 
IBM-Fed, according to IBM CEO Arvind Krishna, processes claims for veterans, provides procurement services to the General Services Administration (GSA), and has implemented and is currently operating payroll systems for several federal agencies. Krishna acknowledged that “some areas around the edges” of this work “could be viewed as discretionary” by DOGE, but that the bulk of IBM-Fed’s services are mission critical and technology focused.

IBM-Fed will double down on its core cloud, security and AI capabilities to successfully traverse the DOGE-disrupted federal IT space in 2025

According to TBR’s 1Q25 IBM Consulting Earnings Response, “IBM Consulting could experience variability in revenue growth in 2025, and IBM is cautious about the revenue contribution from the business to total corporate revenue due to possible further tightening of discretionary spending driven by macroeconomic uncertainty and the U.S. Department of Government Efficiency’s (DOGE) activities.
 
However, IBM Consulting will continue to gain ground in areas such as generative AI (GenAI) due to IBM’s early advances in the segment, diversifying revenues through new areas of expansion.” To buffer its 2025 sales growth against DOGE’s cost-rationalization efforts and offset revenue losses from the cancellation of advisory work deemed discretionary (and thus expendable) by DOGE, IBM-Fed must play to its strengths in AI- and security-infused hybrid cloud solutions and emphasize how well its offerings align with DOGE’s efficiency agenda.
 
IBM-Fed won large-scale programs with civilian and defense agencies in 2024, thanks to the additional delivery and offerings scale in digital transformation it obtained by acquiring Octo Consulting in late 2022, another advantage and a key selling point for IBM-Fed when advising or coaching the DOGE advisory board. While Octo’s pure play advisory capabilities expose IBM-Fed to DOGE’s federal spending cuts in traditional consulting services, Octo’s oLabs center of excellence showcases IBM-Fed’s acquisition-enhanced cloud, security, data science and DevSecOps capabilities that sync well with the IT priorities of the Trump administration.

IBM-Fed must accelerate its expansion within the DOD and among national security agencies, particularly by emphasizing its strengths in cloud

Octo’s oLabs also serves national security and defense agencies. The Trump administration has indicated national security will be an overarching budget priority during its term and has hinted at a federal fiscal year 2026 (FFY26) defense budget surpassing $1 trillion for the first time, underscoring the urgency for IBM-Fed to accelerate its expansion with the Pentagon, where it has been gaining traction since acquiring Octo.
 
According to TBR’s 1H25 IBM Federal Vendor Profile, “Some federal IT industry observers believe the Trump administration’s DOGE will accelerate cloud investment as federal agencies may be forced to outsource more operations deemed outside ‘Inherently Governmental Functions (IGF).’ Cloud adoption in the Department of Defense (DOD) continues to far exceed civilian cloud investment, which the GSA’s Federal IT Dashboard (FITD) estimated to be $8.2 billion in FFY24, up from $5.5 billion in FFY23.”
 
IBM-Fed could leverage IBM’s 1Q25 $6.4 billion acquisition of HashiCorp to accelerate DOD-based expansion, as HashiCorp has helped the DOD migrate more than 3,000 applications to the cloud with its Terraform (Infrastructure as Code software) and Vault (identity-based security) tools designed to facilitate migrations to multicloud architectures. The DOD has clearly indicated it favors a multicloud approach for implementing cloud-based edge computing solutions.
 
*TBR refers to IBM Consulting’s federal IT operations as IBM-Fed. IBM-Fed is not an official business line title used by IBM or IBM Consulting. The business defined by TBR as IBM-Fed resides within IBM Consulting’s U.S. Public and Federal Market group.

 

TBR’s DOGE Federal IT Impact Series will include analysis of Accenture Federal Services, General Dynamics Technologies, CACI, IBM, CGI, Leidos, IFC International, Maximus, Booz Allen Hamilton and SAIC. Click here to download a preview of our federal IT research and receive upcoming series blogs in your inbox as soon as they’ve published.

 

DOGE Federal IT Vendor Impact Series: CACI

The Trump administration and its Department of Government Efficiency (DOGE) have generated massive upheaval across the board in federal operations, including in the federal IT segment. As of March 2025, thousands of contracts described by DOGE as “non-mission critical” have been canceled, including some across the federal IT and professional services landscape. TBR’s DOGE Federal IT Vendor Impact Series explores vendor-specific DOGE-related developments and impacts on earnings performance. Click here to receive upcoming series blogs in your inbox as soon as they’ve published.

 

CACI spared from major DOGE disruptions: Growth and profitability on track for FY25 goals

CACI tendered its 1Q25 earnings on April 23, and TBR did not discern any material impact from DOGE on the company’s business during the quarter, the third fiscal quarter of CACI’s FY25 (ending June 30). The company posted sales of $2.17 billion in 1Q25, up 11.8% year-to-year on a statutory basis and up 5.6% on an organic basis. CACI’s gross margin of 33.8% in 1Q25 was up sequentially from 33.2% in 4Q24, while its operating margin of 9.1% in 1Q25 was up 50 basis points sequentially from 8.6% in 4Q24. The company’s adjusted EBITDA margin was 11.7% in 1Q25, up from 11.1% in 4Q24.
 
CACI believes demand will remain strong through the remainder of its FY25 and into its FY26 for technologies and capabilities at the core of the company’s portfolio: AI-enhanced and commercially honed software-defined solutions delivered with Agile development methodologies; signals intelligence (SIGINT) and electronic warfare (EW) technologies for warfighters, defense vehicles and platforms, and IC applications; and AI-infused financial management offerings.
 
Uninterrupted sales growth and consistent margin performance indicate CACI’s offerings remain well aligned to the Trump administration’s IT investment priorities, particularly as the new administration prepares to expand investment in cybersecurity, national security and national defense, and advanced space-based communications systems for defense, intelligence and civil applications. CACI executives also noted that the federal budget environment is slowly becoming more constructive and more transparent, a positive harbinger for CACI and its fellow federal IT contractors.

CACI’s order book was essentially immune to DOGE-related turmoil in the federal IT market

TBR did not observe any impact from DOGE activities on CACI’s book of business. CACI’s backlog fell 1.3% sequentially, from $31.8 billion to $31.4 billion in 1Q25, but his kind of decline is typical in the company’s third fiscal quarter. CACI’s trailing 12-month (TTM) book-to-bill ratio was 1.5 in 1Q25, down from 1.7 in 4Q24. However, a sequential decline from the second to third fiscal quarter is not unusual for the company. In 1Q25, both the TTM book-to-bill ratio of 1.5 and the quarterly ratio of 1.2 were consistent with figures from the same period last year.
 
Furthermore, CACI’s bookings of $2.2 billion in 4Q23 and $3.5 billion in 1Q24 came during a period of exceptionally robust Department of Defense and Intelligence Community-related award activity. CACI’s bookings were $2.75 billion in 1Q25, up from $1.2 billion in 4Q24, consistent with the seasonal, historical pattern of sequential bookings expansion in the company’s third and second fiscal quarters. CACI noted in its 1Q25 earnings discussion that DOGE examined seven contracts in the company’s order book, including one that had already been completed. The aggregate revenue impact of these awards being eliminated by DOGE would only be $3 million in TCV, though DOGE has only notified CACI that $1 million worth of this ongoing work is likely to be canceled.
 
The company acknowledged that its business development teams have experienced some deceleration in certain aspects of the sales cycle, such as invoice and funding approvals. CACI CFO Jeffrey MacLauchlan said during the earnings call that “things that used to take two or three days are taking four or five days.” CACI’s leadership expects the disruption, which according to the company has been “very manageable” to date, to wane during the second half of federal fiscal year 2025 (FFY25). If sales motions are being impeded by DOGE, TBR would expect to see this reflected in lower-than-expected margin performance by CACI, but we did not observe any DOGE-related margin erosion in CACI’s P&L in 1Q25.

Undeterred by the DOGE-disrupted environment, CACI elevates several elements of its FY25 guidance

CACI raised the low end of its FY25 sales guidance range in 1Q25 and is now calling for top-line revenue of between $8.55 billion and $8.65 billion, implying a growth range of between 11.6% and 12.9% over FY24 revenue of $7.66 billion. In 4Q24 the company forecasted $8.45 billion in revenue at the low end of its projected FY25 sales range, implying growth of 10.3% at the bottom of the range.
 
CACI also raised the low end of its guidance for FY25 adjusted net income* in 1Q25 and now expects at least $543 million in FY25, up from $537 million forecasted in 4Q24.
 
CACI elevated its outlook for non-GAAP adjusted diluted earnings per share (ADEPS) in 1Q25, and as of 1Q25 is projecting a range of between $24.24 and $24.87 per share for FY25, up from a previous ADEPS range of between $23.24 and $24.13 per share. Free cash flow guidance was also elevated from $450 million tendered in 4Q24 to $465 million in 1Q25.
 
TBR notes that CACI has twice raised guidance for FY25 sales, adjusted net income, ADEPS and free cash flow since initially tendering its FY25 outlook in 2Q24. CACI is still guiding for a FY25 EBITDA margin in the low 11% range, implying a potential improvement of 100 basis points over FY24’s EBITDA margin of 10.4%, but also suggesting CACI does not expect any DOGE-related margin headwinds through the remainder of FY25.

CACI will remain vigilant and maintain a constant dialogue with customers

During CACI’s 1Q25 earnings call, CEO John Mengucci described DOGE’s objectives as “peace through strength, secure borders, increased efficiency and technology modernization.” Mengucci and his executive team remain confident that CACI’s strategy and portfolio are and will remain in sync with DOGE’s goals and with the IT strategy of the Trump administration, a contention supported by the company’s 1Q25 fiscal results and its more optimistic FY25 outlook.
 
Irrespective, CACI recognizes that federal executives are under pressure to accelerate IT modernization, quickly achieve IT-driven operational efficiencies and curb spending according to DOGE directives. Procurement teams at federal agencies are struggling to keep bid review processes and proposal adjudications on schedule as the Trump administration executes large-scale furloughs across the federal workforce. As such, CACI will keep its executives, business line leaders and business development teams as close as possible to IT decision makers and procurement counterparts in federal agencies for as long as DOGE’s efficiency agenda is in effect.
 
*Adjusted net income: GAAP-compliant net income excluding intangible amortization expense and the related tax impact

 

TBR’s DOGE Federal IT Impact Series will include analysis of Accenture Federal Services, General Dynamics Technologies, CACI, IBM, CGI, Leidos, IFC International, Maximus, Booz Allen Hamilton and SAIC. Click here to download a preview of our federal IT research and receive upcoming series blogs in your inbox as soon as they’ve published.

 

Fujitsu Expands AI Strategy in Europe, Emphasizing Collaboration, Compliance and Customization

‘AI can be a knowledge management accelerator, but only if well-fed by an enterprise’s own data’

In February TBR met with two AI leaders in Fujitsu’s European Platform Business to better understand the company’s approach to the AI market, its evolving AI capabilities and offerings, and what we can expect as 2025 unfolds. Maria Levina, AI Business analyst, and Karl Hausdorf, head of AI Business, gave a detailed presentation focused primarily on the European market. The following reflects both that briefing and TBR’s ongoing research and analysis of Fujitsu, the company’s partners and peers, and the overall AI landscape.
 
One highlight that illustrates many facets of Fujitsu’s approach to AI was Levina and Hausdorf’s description of Fujitsu’s customers’ choices between “bring your own data” and “bring your own AI.” The first allows more AI-mature customers to bring their data into a Fujitsu-provided on-premises solution with full support for scaling, maintaining hardware and software, and updating, as needed.
 
The second allows customers to run their own AI stack on a Fujitsu “validated and optimized” platform, developed and maintained by Fujitsu and select technology partners. Critical, in TBR’s view, is Fujitsu’s positioning of these options as responsive to clients’ needs, as determined by all AI stakeholders within an enterprise, including IT, AI and business leaders.
 
Levina and Hausdorf explained, “Together, with our ecosystem of partners, we’re committed to unlock the potential of generative AI for our clients” through “on-premises data sovereign, sustainable private GPT and AI solutions,” focused on “rapid ROI.” Fujitsu is not approaching clients with a technology solution, but rather with options on how to address and solve business problems. As the Fujitsu team said, “Understand the why, know the what, and co-create the how.” The Fujitsu team also noted that the company’s industry expertise resides in the processes and workflows unique and/or critical to an industry.
 

‘Maintaining control of data means owning your AI in the future’

Before diving into Fujitsu’s AI offerings, the Fujitsu team laid out their understanding of the European market, sharing data the company collected around AI adoption, use of AI platforms, and barriers to growth (in Fujitsu’s phrasing, “progress-limiting factors,” which is perhaps a more positive spin on the usual list of barriers and challenges). Fujitsu surveyed or spoke with 400 data and IT professionals across six European countries, and the results indicated that overcoming legacy mindsets continues to be a major impediment to adopting and harnessing the value of AI.
 
TBR’s November 2024 Voice of the Customer Research similarly noted challenges in Europe with “the lack of engagement from employees who are being asked to change.” The Fujitsu team noted that change management, therefore, had to involve all AI stakeholders, including “IT people, business people and AI people” within an enterprise.
 
In TBR’s experience, IT services companies and consultancies continue to find new constituents for change management at their clients as the promise — and disruption — of AI becomes more widespread, reinforcing Fujitsu’s strategy of bringing change management to all AI stakeholders. Lastly, the Fujitsu team noted that within European clients, expectations around AI have heightened, especially as AI initiatives have launched across multiple business units. Again, Fujitsu’s research and TBR’s Voice of the Customer Research align around ROI expectations as AI matures.
 
The Fujitsu team introduced their AI platform by delineating the key performance indicators they believe a successful platform must have: scaling, performance and speed, simplicity, energy efficiency, AI services in data centers, and GPUs.
 
Although TBR is not in a position to evaluate the technological strengths, completeness or complexity of Fujitsu’s platform, the expansive KPIs indicate Fujitsu has considered not only the IT needs behind an AI deployment but also the larger business factors, particularly the financial impacts. Levina and Hausdorf then dove into the details, including the two customer options described above (bring your own data and bring your own AI). They discussed how Fujitsu offers consulting around the technical and business implications of AI platforms and solutions, including an “AI Test Drive,” which allows clients to test AI solutions before investing in new technologies, large language models (LLMs) or other AI components.
 
Notably for TBR, Fujitsu’s presentation extensively highlighted the company’s AI alliance partners, including Intel, NVIDIA, AMD and NetApp, as well as a slew of LLM providers, demonstrating an appreciation for the collaborative and ecosystem-dependent nature of AI at the enterprise level. The Fujitsu team also stressed the European nature of its AI strategy and platform.
 
European clients, Fujitsu noted, had specific requirements related to the European Union’s (EU) General Data Protection Regulation and the EU AI Act, as well as a preference for on-premises solutions. Some of the use cases Levina and Hausdorf described included a law firm using Fujitsu-enabled AI solutions to analyze case data, contracts, corporate and public legal documents, and multiple deployments of Fujitsu-enabled private GPTs.

Additional observations

  • Fujitsu remains focused on targeting customers already aligned with the company around AI, a strategy that TBR believes speeds ROI and increases client retention.
  • In contrast to some peers in the IT services market, Fujitsu has capabilities across the entire AI technology stack — hardware, software and service — which Levina and Hausdorf called “highly appealing,” especially to European clients.
  • Levina and Hausdorf made two comments that, in TBR’s view, neatly sum up AI at present: “AI can be a knowledge management accelerator, but only if well-fed by an enterprise’s own data” and “maintaining control of data means owning your AI in the future.”

Fujitsu’s AI prowess makes it an invaluable partner

TBR has reported extensively on Fujitsu’s evolving AI capabilities and offerings, noting in a special report in May 2024: “TBR appreciates that Fujitsu’s combination of compute power and proven AI expertise makes the company a significant competitor and/or alliance partner for nearly every player fighting to turn GenAI [generative AI] hype into revenue.
 
“Second, Fujitsu’s vision of ‘converging technologies’ aligns exceptionally well with the more tectonic trends TBR has been observing in the technology space, indicating that Fujitsu’s market positioning is more strategic than transactional or opportunistic.” Add in Fujitsu’s deepening experience in delivering AI solutions to AI clients, and TBR continues to see tremendous near-term opportunity and growth for Fujitsu and its ecosystem partners.

Inside the AI Hardware Shift: Market Trends Every IT Decision Maker Should Watch in 2025

Register for Inside the AI Hardware Shift: Market Trends Every IT Decision Maker Should Watch in 2025

 

Silicon vendors and OEMs working together to support AI adoption

While OEMs are responsible for developing and delivering AI-driven and AI-enabling hardware offerings to market, silicon vendors’ innovations are at the heart of the AI hardware revolution.
 
The first wave of AI hardware demand has centered on high-performance AI infrastructure purpose-built to support large-scale AI model training workloads. But the rise of AI inferencing is giving way to a second wave of AI hardware demand as clients increasingly transition from the prototyping phase to the deployment phase with custom AI solutions. On the infrastructure side of the AI hardware market, OEMs such as Dell Technologies, Hewlett Packard Enterprise and Supermicro are integrating accelerated computing platforms from companies like NVIDIA. On the client devices side of the market, OEMs such as HP Inc. and Lenovo are developing new AI PC offerings based on system on a chip (SoC) platforms developed by AMD, Intel, Qualcomm and the like.
 
Join Senior Analyst Ben Carbonneau and Principal Analyst Angela Lambert Thursday, May 22, 2025, for an update on developments within the rapidly expanding AI PC and AI server markets as well as key findings from TBR’s AI PC and AI Server Market Landscape. This new research explores the nuances and interconnectedness of the semiconductor and OEM hardware industries, comparing market shares across various industry views and highlighting competitive analysis and forward-looking insights.

In this free session on AI hardware market trends you’ll learn:

  • TBR’s forecast for the AI PC and AI PC SoC markets
  • Our performance outlook for the AI server and AI server GPGPU (general-purpose computing on GPUs) markets
  • The latest industry trends and ecosystem partnerships
  • Key market dynamics contributing to and inhibiting growth

Register Now

 
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. Previous sessions can be viewed anytime on TBR’s Webinar Portal.
 

Google Cloud Cements Values of Enterprise Readiness, Full-stack AI and Hybrid Cloud at Next 2025

In April Google Cloud hosted its annual Next event to showcase new innovations in AI. Staying true to the theme of “A New Way to Cloud,” Google focused on AI, including how AI can integrate with enterprises’ existing tech landscape, with partners playing the role of orchestrator. After Google CEO Sundar Pichai spoke about the company’s achievements around Gemini, which is integral to Google Cloud’s strategy, Google Cloud CEO Thomas Kurian highlighted the business’s three key attributes: optimized for AI; open and multicloud; and enterprise-ready. Additionally, Google Cloud announced a series of new innovations that highlight how the company is trying to execute on these three areas to be the leader in modern AI development.

Google takes an end-to-end approach to AI

When discussing Google Cloud’s three key attributes, Kurian first highlighted how Google Cloud Platform (GCP) is optimized for AI. Based on our own conversations with IT decision makers, this claim is valid: many customers enlist GCP services purely for functional purposes, as they believe they cannot obtain the same performance with another vendor. This is particularly true of BigQuery, for large-scale data processing and analytics, and increasingly Vertex AI, which now supports over 200 curated foundation models for developers.
 
Within this set of models is, of course, Gemini, Google’s own suite of models, including the new Gemini 2.5 Pro, which has a context window of 1 million tokens and is reportedly now capable of handling advanced reasoning. To be fair, Google still faces stiff competition from other frontier model providers, but Google’s years of AI research through DeepMind and its ability to have models grounded in popular apps like Google Maps, not to mention Google Search, will remain among its key differentiators.
 
With that said, the AI software stack is only as effective as the hardware it runs on. That is why Google has been making some advances in its own custom AI accelerators, and at the event, Google reaffirmed its plans to invest $75 billion in total capex for 2025, despite the current macroeconomic challenges. A large piece of this investment will likely focus on paying for the ramp-up of Google’s sixth-generation TPU (Tensor Processing Unit) — Trillium — which became generally available to Google Cloud customers in December. Additionally, Google is making some big bets on the next wave of AI usage: inference.
 
At the event, Google introduced its seventh-generation TPU, dubbed Ironwood, which reportedly scales up to 9,216 liquid cooling chips linked through a high-powered networking layer, to support the compute-intensive requirements of inference workloads, including proactive AI agents. In 2024 there was a 3x increase in the number of collective TPU and GPU hours consumed by GCP customers, and while this was likely off a small number of hours to begin with, it is clear that customers’ needs and expectations around AI are increasing. These investments in AI hardware help round out key areas of Google’s AI portfolio ― beyond just the developer tools and proprietary Gemini models ― as part of a cohesive, end-to-end approach.
 

Watch now: Cloud market growth will slow in 2025, but will activity follow? Deep dive into generative AI’s impact on the cloud market in 2025 in the below TBR Insights Live session

 

Recognizing the rise of AI inference, Google Cloud reinforces longtime company values of openness and hybrid cloud

With its ties to Kubernetes and multicloud editions of key services like BigQuery and AlloyDB, Google Cloud has long positioned itself as a more open cloud compared to its competitors. However, in recent quarters, the company has seemed to hone this focus more closely, particularly with GDC (Google Distributed Cloud), which is essentially a manifestation of Anthos, Google’s Kubernetes-based control plane that can run in any environment, including at the edge. GDC has been the source of some big wins recently for Google Cloud, including with McDonald’s, which is deploying GDC to thousands of restaurant locations, as well as several international governments running GDC as air-gapped deployments.
 
At Next 2025, Google announced it is making Gemini available on GDC as part of a vision to bring AI to environments outside the central cloud. In our view, this announcement is extremely telling of Google Cloud’s plans to capture the inference opportunity. Per our best estimate, roughly 85% of AI’s usage right now is focused on training, with just 15% in inference, but the inverse could be true in the not-too-distant future. Not only that, but inference will also likely happen in distributed locations for purposes of latency and scale. Letting customers take advantage of Gemini to build applications on GDC — powered by NVIDIA Blackwell GPUs — on premises or at the edge certainly aligns with market trends and will help Google Cloud ensure its services play a role in customers’ AI inference workloads regardless of where they are run.

Boosting enterprise mindshare with security, interoperability and Google-quality search

Kurian mentioned that customers leverage Google Cloud because it is enterprise-ready. In our research, we have found that while Google Cloud is highly compelling for AI and analytics workloads, customers believe the company lacks enterprise-grade capabilities, particularly when compared to Microsoft and Amazon Web Services (AWS). But we believe this perception is changing, and Google Cloud is recognizing that to gain mindshare in the enterprise space, it needs to lead with assets that will work well with customers’ existing IT estates and do so in a secure way. This is why the pending acquisition of Wiz is so important. As highlighted in a recent TBR special report, core Wiz attributes include not only being born in the cloud and able to handle security in a modern way but also connecting to all the leading hyperscalers, as well as legacy infrastructure, such as VMware.
 
Google Cloud has been very clear that it will not disrupt the company’s multihybrid capability. In fact, Google Cloud wants to integrate this value proposition, which suggests Google recognizes its place in the cloud market and the fragmented reality of large enterprises’ IT estates. Onboarding Wiz, which is used by roughly half of the Fortune 500, as a hybrid-multicloud solution could play a sizable role in helping Google Cloud assert itself in more enterprise scenarios. In the meantime, Google Cloud is taking steps to unify disparate assets in the security portfolio.
 
At Next 2025, Google Cloud launched Google Unified Security, which effectively brings Google Threat Intelligence, Security Operations, Security Command Center, Chrome Enterprise and Mandiant into a single platform. By delivering more integrated product experiences, Google helps address clients’ growing preference for “one hand to shake” when it comes to security and lays a more robust foundation for security agents powered by Gemini, such as the alert triage agent within Google Security Operations and the malware analysis agent in Google Threat Intelligence to help determine if code is safe or harmful.
 
One of the other compelling aspects of Google’s enterprise strategy is Agentspace. Launched last year, Agentspace acts as a hub for AI agents that uses Gemini’s multimodal search capabilities to pull information from different storage applications (e.g., Google Drive, Box, SharePoint) and automate common productivity tasks like crafting emails and scheduling meetings. At the event, Google announced that Agentspace is integrated with Chrome, allowing Agentspace users to ask questions about their existing data directly through a search in Chrome. This is another clear example of where Google’s search capabilities come into play and is telling of how Google plans to use Agentspace to democratize agentic AI within the enterprise.

Training and more sales alignment are at the forefront of Google Cloud’s partner priorities

Google Cloud has long maintained a partner-first approach. Attaching partner services on virtually all deals; taking an industry-first approach to AI, particularly in retail and healthcare; and driving more ISV coselling via the Google Cloud Marketplace are a few examples. At Next 2025, Google continued to reaffirm its commitment to partners, implying there will be more alignment between field sales and partners, to ensure customers are matched with the right ISV or global systems integrator (GSI), a strategy many other cloud providers have tried to employ.
 
When it comes to the crucial aspect of training, partners clearly see the role Google Cloud plays in AI, and some of the company’s largest services partners, including Accenture, Cognizant, Capgemini, PwC, Deloitte, KPMG, McKinsey & Co., Kyndryl and HCLTech, have collectively committed to training 200,000 individuals on Google Cloud’s AI technology. Google has invested $100 million in partner training over the past four years, and as highlighted in TBR’s Voice of the Partner research, one of the leading criteria services vendors look for in a cloud partner is the willingness to invest in training and developing certified resources.

Google Cloud wants partners to be the AI agent orchestrators

As previously mentioned, Vertex AI is a key component of Google Cloud’s AI software stack. At Next 2025, Google Cloud introduced a new feature in Vertex called the Agent Development Kit, which is an open-source framework for building multistep agents. Google Cloud is taking steps to ensure these agents can be seamlessly connected regardless of the underlying framework, such as launching Agent2Agent (A2A), which is an open protocol, similar to protocols introduced by model providers like Anthropic.
 
Nearly all of the previously mentioned GSIs, in addition to Boston Consulting Group (BCG), Tata Consultancy Services (TCS) and Wipro, have contributed to the protocol and will be supporting implementations. This broad participation underscores the recognition that AI agents will have a substantial impact on the ecosystem.
 
New use cases will continue to emerge where agents are interacting with one another, not only internally but also across third-party systems and vendors. With the launch of the Agent Development Kit and the related protocol, Google Cloud seems to recognize where agentic AI is headed, and for Google Cloud’s alliance partners, this is an opportune time to ensure they have a solid understanding of multiparty alliance structures and are positioned to scale beyond one-to-one partnerships.

Final thoughts

At Next 2025, Google reportedly announced over 200 new innovations and features, but developments in high-powered compute, hybrid cloud and security, in addition to ongoing support for partners, are particularly telling of the company’s plans to capture more AI workloads within the large enterprise. Taking an end-to-end approach to AI, from custom accelerators to a diverse developer stack that will let customers build their own AI agents for autonomous work, is how Google Cloud aims to protect its already strong position in the market and help lead the shift toward AI inferencing.
 
At the same time, Google Cloud appears to recognize its No. 3 position in the cloud market, significantly lagging behind AWS and Microsoft, which are getting closer to each other in IaaS & PaaS revenue. As such, taking a more active stance on interoperability to ensure AI can work within a customer’s existing IT estate, and guaranteeing partners that have the enterprise relationships are the ones to orchestrate that AI, will help Google Cloud chart its path forward.

Trade Wars and the Professional Services Fallout: Talent, Growth and Operational Models in Flux

Significant market disruption likely in near and long term

Trade wars and tariff uncertainties conjure up visions of cargo ships, ports, factories and stacks of goods stranded by economic chaos, not consultants and IT services professionals. Fear, uncertainty and doubt are usually good for the consulting business, while the higher costs of running a business fuel demand for more outsourcing. This time, things might be different. This trade war, even if partially suspended for now, may significantly disrupt professional services, especially if tariffs continue creeping into new areas and the trust deficit continues to grow. Steel now, services later.
 
TBR believes three areas will likely experience added near-term stress if the trade war continues: acquisitions, sales cycles and staffing. Longer-term, more seismic changes may come to the H-1B visa program, regionalization efforts among the Big Four firms, and onshore/offshore talent models. Looming over all of these disruptions, at least at the moment, is the potential for a grand decoupling of the U.S. and China economies, with incomprehensible knock-on effects. Those near-term disruptions share a common denominator: macroeconomic uncertainty.
 
Making the business case for a significant acquisition becomes harder in a recession-fearing market. When clients extend sales cycles because they’re afraid to commit suddenly more precious resources to upgrades, modernizations or transformations, growth slows for consultancies and IT services companies. And when growth slows, so does hiring.
 
At its core, professional services is all about people. And when recruiting, rewarding and retaining people are pressured, everything is pressured. To understand how tariffs and trade wars could hurt consultancies and IT services companies, even in the short run, it is critical to step back and realize these professional services providers serve every industry. They may be in and of one industry themselves — professional services — but their clients span every industry that exists. When the steel, computer chip, automobile, bourbon and lumber industries get upended by tariffs, so do the consultancies and IT services companies serving them.
 

In 2025 IT services companies and consultancies will refine their alliances, articulate a clear joint value proposition, and align at both the leadership and salesforce levels. The most successful IT services companies and consultancies will be the ones that partner best. Learn more in TBR’s 2025 Ecosystems & Alliances Predictions special report.


 

Local and regional talent may be key to revenue growth

Powering through the near-term challenges, IT services companies and consultancies may then face structural changes to their operating environment, many centered on talent, starting with a reevaluation of the onshore/offshore mix. India-centric companies, which have historically relied on H-1B visas (at least to some degree; TBR appreciates that their reliance has varied widely), may find a less accommodating atmosphere in the U.S. and possibly even an unwillingness by potential candidates to relocate to the U.S.
 
At the same time, the Big Four firms may slow down their regionalization efforts, as having highly country-specific capabilities and dedicated staff may become a greater asset than more explicitly globalized organizations. TBR believes the more extreme outcomes around H-1B visas remain unlikely, while staying cognizant that the current trade war and tariff uncertainty also seemed unlikely a year ago. TBR does believe one highly likely outcome of the current trade crisis is a reassessment — by all IT services companies and global consultancies — of the overall onshore/offshore model. The recent uptick in global captive centers in India may be indicative of an enterprise trend toward more tightly owned and controlled offshore resources, but that was already the norm among IT services companies and consultancies prior to the trade war threat.
 
If trade wars persist, local and regional talent may become the key to sustained revenue growth, tied to local and regional economic growth overall. In other words, whichever company has the most and the best people on the ground in the fastest-growing places will continue to grow the most rapidly. It seems like a good time for the Big Four to have every country member firm run its own show as the on-the-ground market conditions start becoming even more disparate.
 

Watch now: TBR Principal Analyst & Practice Manager Patrick M. Heffernan discusses trend expectations for GenAI in the Professional Services market in 2025

Tariffs on services could further complicate market landscape

Returning to the starting image, trade wars evoke cargo ships, not consultants, and so far the Trump administration has not included services on the various tariff schedules. The U.S. currently runs a services trade surplus, and tariffs on services (as well as software) for various countries would be insanely difficult to assess. Artificial intelligence and the application of generative AI (GenAI) to procurement could make tariffs on services more manageable, but any efficiencies gained through those efforts would potentially erode the low-cost arbitrage advantage enjoyed by IT services companies and technology providers, damaging the overall U.S. trade balance.
 
Further complicating this picture, advances in AI and automation could mean any manufacturing jobs created in the U.S. as a direct result of tariffs would be digital FTEs, benefiting technology companies but undermining the Trump administration’s stated goals. In all, a mess, even if services remain off the tariff schedule.

Companies pursue multiple strategies around U.S.-China decoupling

Another potential scenario: Some economic and consulting leaders have been advocating for a U.S.-China decoupling for a few years, a possibility that is more likely now as every day brings another parry in the U.S.-China trade war. Some global consultancies have been kicked out of China. Others have downgraded their offices or quietly left on their own. And some are maintaining an arm’s-length relationship, and some are doing business as usual. Fools would predict which strategies will win out. TBR simply notes that companies may pursue multiple strategies.
 
For example, in August 2024 IBM closed its China Development Lab and China Systems Lab, laying off more than 1,000 employees across Beijing, Shanghai and Dalian. The closure was part of IBM’s initiative to relocate R&D functions to India and other countries due to competition and geopolitical tensions. However, IBM remains committed to working with clients in the Greater China region. In March IBM launched an initiative to expand in enterprise AI, hybrid cloud and industry-specific consulting services to drive digital transformation and implement AI and cloud solutions in China. As part of this initiative, IBM is working with China-based Great Wall Motor Co. Ltd. on digital transformation and global expansion. A complete decoupling may be unlikely, but consultancies and IT services companies that have financial flexibility and leaders who are prepared to take risks and withstand uncertainty will likely continue to thrive.

Here Comes KPMG: Client Trust, Alliance Focus and Tech-enabled Strategy Emphasized at 2025 Global Analyst Summit

Executing on its Collective Strategy through integrated scale and backed by robust strategic partnerships and platform-enabled services positions KPMG to remain a formidable competitor in the transforming professional services market

KPMG Global Chairman and CEO Bill Thomas kicked off the firm’s 2025 Global Analyst Summit by reinforcing the firm’s mission to be “the most trusted and trustworthy professional services firm.” As we have discussed at length across TBR’s professional and IT services research, firms like KPMG trade on trust with clients, alliance partners and employees. Putting a stake in the ground from the get-go provided Thomas and KPMG’s executives a strong foundation to rely on during the next two days as trust — at the human and technology level — was an underlying theme during presentations and demos.
As a member of the Big Four, KPMG has brand permission and a breadth of services that are relevant to nearly every role in any enterprise. As the firm executes on its Collective Strategy, TBR believes KPMG will accelerate the scale and completeness of its offerings, building on a solid foundation and expanding the gaps between KPMG and other consulting-led, technology-enabled professional services providers. ​
 
KPMG’s global solutions — Connected, Powered, Trusted and Elevate — which resonate with clients and technology partners, have now been brought together into one transformation framework under KPMG Velocity, providing KPMG’s professionals with clear insight into the firm’s strengths and strategy, and underpinning, in the near future, all KPMG’s transformation engagements. KPMG Velocity’s evolving strategy will challenge KPMG’s leaders to execute on the promise of that transformation during the next wave of macroeconomic pressures, talent management battles and technology revolutions. At the same time, KPMG’s leaders recognize that their priorities are transforming the firm’s go-to-market approach, unlocking the power of the firm’s people, reimagining ways of working, and innovating capabilities and service enhancements. ​
 
Success in executing these priorities, in TBR’s view, will come as KPMG shifts from building a foundation to scaling alongside the growing needs of its clients and as the era of GenAI presents yet another opportunity and challenge. Striking the right balance between elevating the potential of GenAI as a value creator and accounting for commercial and pricing model implications will test the durability of KPMG’s engagement and delivery frameworks. ​
 
Although the firm has placed in motion many of the aforementioned investments over the past 12 to 18 months, the one opportunity that is changing relates to speed. As one enterprise buyer recently explained to TBR: “GenAI will force all services vendors to change. The [ones] who [will] be [the] most successful will be [those] who do it fast.” With speed comes risk — which KPMG fully acknowledges and is why KPMG Velocity’s offering is a differentiator for the firm in the market. With KPMG Velocity, all of KPMG’s multidisciplinary and heritage risk and regulatory considerations have been embedded across each transformation journey to ensure clients can remain compliant and avoid the pitfalls that can often arise during transformation. ​
Continuing the firm’s presentation, Thomas outlined KPMG’s evolving Collective Strategy, noting that the firm is 18 months into its latest iteration focused on “accelerating trust and growth.” Among the key enablers of achieving this goal is KPMG’s collapsing of its organizational structure from 150 country-specific member firms to a cluster of 30 to 40 regionally organized “economic units.” TBR views this pivot as the most natural evolution of KPMG’s operating model. For the Big Four, the biggest challenge is how to demonstrate value through integrated scale. Once completed, the reorganization will allow KPMG to minimize such disruption and better compete for globally sourced opportunities from what the firm calls “transactions to transformation” and for large, multi-year, geographically dispersed enterprise, function and foundational transformations.
 
Following Thomas’ presentation, Carl Carande, KPMG U.S. & global lead, Advisory, and Regina Mayor, global head of Clients & Markets, amplified KPMG’s strategy, reinforcing the importance of the firm’s people, technology partners and technology — with AI the catalyst and change agent of success. For example, Carande recognized the technology relationships are changing in two ways. Relationships are becoming more exclusive, and the multipartner alliance framework offers a multiplier power — themes TBR has discussed at length throughout our Ecosystem Intelligence research stream.
 
Although KPMG continues to manage a robust network of alliance partners, highlighting its seven strategic partners — Google Cloud, Microsoft, Oracle, Salesforce, SAP, ServiceNow and Workday — solidifies its recognition of these vendors’ position throughout the ecosystem. Mayor expanded on Carande’s discussion around alliances through an industry lens, describing “alliance partners leaning in with KPMG” as they realize efforts to only sell the product will be insufficient. Meanwhile, on the KPMG side, alliance sales partners help figure out how to penetrate sector-specific alliance relationships.
 
Taking such a systematic approach across KPMG’s 7 sectors (with the desire to expand these to 14) will allow the firm to demonstrate value and support its evolving Collective Strategy to act as a globally integrated firm. Additionally, new offerings like KPMG Velocity (discussed in depth on Slide 6) will arm KPMG’s consultants with the necessary collective knowledge management to serve global clients locally, further supporting the firm’s strategy.
 
One could argue that many of KPMG’s steps, including launching partner-enabled industry IP, reinforcing trust, developing regionally organized operations, outlining a select few strategic partners, and investing in platform-enabled service delivery capabilities, resonate with the moves taken by many of its Big Four and large IT services peers. We see two differences.
 
First, KPMG is laser-focused on exactly which of the strategies above to amplify, rather than taking a trial-and-error approach. Second, it is about timing. Some of KPMG’s peers have tried these strategies for some time, with limited success because of poor execution or timing. We believe that as the professional services market goes through its once-in-a-century transformation, KPMG has an opportunity to ride the wave, provided it maintains internal consensus and executes on its operational and commercial model evolution with minimal disruption.
 

 

KPMG’s evolution will largely stem from orchestrating alliances with seven strategic technology partners

At the event, KPMG asserted the role of tech alliance partners in building the “firm of the future.” Although the firm works with a range of ISVs, a targeted focus on the firm’s seven strategic technology partners has become key to the company’s growth profile — with 50% of its consulting business alliance-enabled in the U.S. — and, as the case of previous audit client SAP shows, KPMG has been able to overcome barriers to ultimately help clients get the most out of technology. The firm’s approach of leading with client outcomes first and technology second is unchanged, but prioritizing a tech-enabled go-to-market approach will support KPMG’s position in the market behind two major trends.
 
The first trend is the overall maturation in partner alliance structures we see from the cloud vendors. Changes in programmatic structure, including bringing sales and partner delivery closer together, and an all-around shift in how partners are viewed among historically siloed vendors, could act as enablers for KPMG’s newer capabilities, including Velocity. Second, there is a big paradigm shift underway on where the value of tech exists. Increasingly, we see the firm moving down the stack, a trend enabled by agentic AI and customers’ need to harness their own data and build new applications. Across the Big Seven, there is no shortage of innovation. As the value of AI shifts down the technology stack, KPMG can leverage the technology to deliver business outcomes to clients.
 
To fully describe KPMG’s evolving technology alliance strategy and the firm’s growing capabilities, KPMG leaders hosted a panel discussion that included leaders from Microsoft, SAP, Salesforce and KPMG clients. Todd Lohr, KPMG’s head of Ecosystems for Advisory, set the stage by saying the firm views ecosystems as more than simply a collection of one-to-one alliances, but ecosystems are, instead, many-to-many relationships, an idea TBR has increasingly heard expressed by consultancies, IT services companies, hyperscalers and software vendors.
 
Having leaders from technology partners on stage to display a very common example of a tech stack — with SAP as the system of record (SOR), Salesforce in the front office, and Microsoft as the platform with Copilot — was a strong way to depict the “many-to-many relationships” structure and KPMG’s role in orchestrating the ecosystem, especially in scenarios where some of these ISVs may not have a native integration and/or formal collaboration with one another. Lohr noted that KPMG “needs to show up understanding how complicated multiparty relationships work before showing up and working them out ad hoc at the client.” That direct acknowledgment of the challenges inherent in multiparty alliances is decidedly not something TBR consistently hears from KPMG’s peers and partners.

KPMG moves away from vendor agnosticism

One of the most important takeaways for TBR from the summit was KPMG’s willingness, in the right circumstances, to aggressively abandon the typical agnostic approach to recommending technologies and instead make a specific technology recommendation where there is a deep understanding of the client needs. One client example highlighted this new(ish) approach. When the client reached out for advice on a sales-enablement platform, KPMG did not take an agnostic approach and, instead, told the client Salesforce was the only choice, based on KPMG’s evaluation.
 
Part of KPMG’s proposal rested on reworking the client’s processes so Salesforce could work as much out of the box as possible, limiting costs and customizations. As KPMG leaders described it, this reflected the opposite of most consultancies’ (and enterprises’) usual approach of forcing the business processes to work with a new technology. In a competitive bidding process, the lead KPMG partner, according to the client, answered questions on the Salesforce software and implementation issues without turning to others on the KPMG team, demonstrating mastery of Salesforce and the client’s IT environment that reassured the client about KPMG’s recommendations. Further, the client expressly did not want customization layers on top of Salesforce, knowing that would be more expensive over time.
 
Notably, the “fairly comprehensive implementation,” according to the client, took less than a year, including what the client said was “a lot of investment with KPMG in change management.” Recalling best practices TBR has heard in other engagements, the client team and KPMG called the Salesforce implementation Project Leap Frogs to avoid the word “transformation,” enabled champions across the enterprise, and held firm to the approach of making minimal customizations. In discussions with TBR, KPMG leaders confirmed that not being technology agnostic was contrary to the firm’s usual practice but was becoming more common.
 
Reinforcing that notion, a KPMG leader told TBR that the firm had lost a deal after it recommended Oracle and said SAP was not the right fit. The client selected SAP (for nontechnical reasons) but later awarded, without a competitive bidding process, Oracle-specific work to KPMG after noting respect for the firm’s honesty and integrity.

KPMG showcases client-centric innovation in action

ServiceNow implementation

A client story featuring a ServiceNow implementation that brought cost savings and efficiencies to the client notably emphasized change management, a core KPMG consulting capability that is sometimes overshadowed by technologies. The client described the “really good change management program that KPMG brought” as well as the emphasis on a clear data and technology core, out-of-the-box ServiceNow implementation, and limited customizations. In TBR’s view, KPMG’s approach with this engagement likely benefited considerably from the firm’s decades-long relationship with the client, playing to one of KPMG’s strengths, which the firm’s leaders returned to repeatedly in discussions with TBR: Trusted partnerships with clients create long-standing relationships and client loyalty.

Reimagining leaders

One client story centered on a five-day “reimagining leaders” engagement at the Lakehouse facility, conducted by the KPMG Ignition team. Surprisingly, KPMG included an immersive session with an unrelated KPMG team working on an unrelated client’s project that had little overlap with the business or technology needs of the leadership engagement client.
 
According to the KPMG Ignition team, the firm showcased how KPMG works, how innovation occurs at the working level, and how KPMG creates with clients, giving them confidence in KPMG’s breadth and depth of capabilities. Echoing sentiments TBR has heard during more than a decade of visiting transformation and innovation centers, KPMG Ignition leaders said that being enclosed on the Lakehouse campus made it easier for clients to be fully present throughout the engagement and removed from the distractions of day-to-day work.
 
KPMG kept the client in the dark about what to expect from the engagement, which prevented any biased expectations from creeping in before the engagement had even started. KPMG Ignition leaders shared additional insights, noting that it was a pilot program for rising leaders at the client, providing an immersive experience that showcased the power of the KPMG partnership.
 
Throughout the five-day immersion at KPMG Lakehouse, participants learned how to apply the methodologies that fuel innovation at KPMG while staying focused on one theme: reimagining leadership of the overall company and of the participants as next-generation leaders, as well as reimagining leadership capabilities at every level of the organization.
 
KPMG equipped the client’s leaders with methodologies emphasizing storytelling, design thinking and strategic insights, and strengthened the client’s culture by fostering high-performing, collaborative teams.
 
One final comment from the Ignition Center leaders: This pilot program “highlighted the fact that AI can be viewed as a wellness play across the agency if you free up capacity and understand what can be achieved.” Based on the use case and sidebar discussions TBR had with KPMG Ignition leaders, we believe Ignition Centers continue to evolve, although the basics remain the same: Get clients into a dedicated space outside their own office, use design thinking, and focus on business and innovation and leadership and change, not on technology.

The art of the possible

A final client story, presented on the main stage, wove together the themes of AI, transformation and trust. The client, a chemicals manufacturer and retailer, said KPMG consistently shared “what’s possible,” essentially making innovation an ongoing effort, not a one-off aspect of the relationship.
 
The client added that his company and KPMG had “shared values … and we understand each others’ cultures,” in part reinforced by KPMG dedicating the same team to the client during a multiyear engagement.
 
In TBR’s view, KPMG’s decision to highlight this client reinforced everything KPMG leaders had been saying during the summit: Relationships, built on consistent delivery and continually coming to the client with ideas and innovations, plus a commitment to the teaming aspect of the engagement, are KPMG’s superpower. Notably, this client was not a flashy tech company, a massive financial institution or a well-known government agency, and the work KPMG did was not cutting-edge or highly specialized but rather core KPMG capabilities — in short, what KPMG does well.

Velocity and GenAI: KPMG’s client-first approach to AI adoption and transformation

KPMG dedicated the second day of the analyst summit to AI, a decision that reflected the firm’s overall approach: Business decisions come first, enabled by technology. Supporting the firm’s AI strategy, KPMG has developed Velocity, a knowledge platform, AI recommendation and support engine underpinned by one universal method that pulls together every capability, offering and resource across the firm for the KPMG workforce. According to KPMG leaders, Velocity reinforces the firm’s multidisciplinary model and will become the primary way KPMG brings itself to clients.

In addition to sharing knowledge across the global firm, Velocity will help KPMG’s clients find the right AI journey that matches their ambitions — whether it be Enterprise, Function or Foundation — by allowing them to select a strategic objective they are trying to achieve, which function(s) they want to transform, and which technology platforms they want to transform on. The platform also reaffirms the firm’s acknowledgment of data’s role in AI. In fact, part of the rationale for Velocity was bringing the data modernization and AI business together while maintaining a focus on a sole client outcome. This means KPMG does not care whether customers build their data foundation with a hyperscaler or internally; as one leader in the AI Journey breakout session said, it is just about “helping clients do what they want to do.”

Velocity includes preconfigured journeys based on specific client needs, as developed, understood and addressed in all of KPMG previous engagements. Similar to many consultancies, KPMG begins engagements by developing an understanding of clients’ strategic needs and issues, rather than their technology stack. (TBR comment: easy to say, hard to do, especially when a firm has practices built around specific technologies).

Velocity is designed to add value to client engagements (including describing, calculating and being accountable). It will also bring a “tremendous amount of information” and is “highly tailorable,” according to a KPMG leader, who also noted that the platform’s adoption, use and usefulness over time will be key. KPMG leaders said the core aspects of AI — even agentic AI — are all the same, separated only by planning and orchestration. For example, KPMG’s AI Workbench underpins how it is bringing agents and AI-enabled services to its clients and its people. Velocity, then, is a KPMG offering where every step is focused on achieving client outcomes, which comes back to understanding clients’ key business issues, not simply their technology stack.

The launch of Velocity internally (starting in March 2025) into its largest member firms brings to life KPMG’s approach to AI. KPMG expects its member firms to be able to start unlocking the power of Velocity beginning in May, and will launch Velocity externally later in the year. Amid caution on the client side around the adoption and implementation of AI technologies, KPMG’s David Rowlands, head of AI, discussed how KPMG wants to be client zero around AI, helping to ease clients’ ethics and security concerns by working through experimentation and into adoption and scale. Rowlands highlighted the firm’s attention to knowledge and need to fully benefit from AI. Training around AI, including the definition of AI and how to use it; creating trust within AI; and learning effective AI prompts also fit within this strategy, enabling both KPMG and clients to effectively embed AI across people and operational strategies.

 

Velocity, AI and the future of audits

Three other AI-centric comments from KPMG leaders stood out for TBR:

  • With AI, “the road to value is paved with human behavior and change,” according to Rowlands, reflecting the firm’s emphasis on the business over the technology and the importance of change management — a core KPMG consulting strength.
  • Rowlands also noted that AI is a critical national infrastructure, dependent on energy, connectivity and networks, and should be considered a national investment priority and national security issue. In TBR’s view, framing AI this way — not as just a tool or another service to be sold — adds credibility to KPMG’s AI efforts.
  • According to Per Edin, KPMG’s AI leader, “ROI is clear and documented, but still not enough adoption to be as measurable as desired.” In TBR’s view, Edin’s sentiments track closely with TBR’s Voice of the Customer and Voice of the Partner research, which have repeatedly shown that interest and investments in AI have outpaced adoption, particularly at scale.

In a breakout session, KPMG walked through the firm’s well-established KPMG Clara platform, a tool designed to help the firm complete its audits more quickly and accurately. In essence, KPMG creates a digital twin of an organization, reflecting the firm’s understanding of where AI can be applied. KPMG Clara Transaction Scoring enables auditors to deliver what the firm calls “audit evidence” and note “outlier” transactions. According to KPMG leaders, “AI agents perform audit procedures and document results for human review, just like junior staff.”
 
Critically, KPMG Clara audits every transaction, not just a sample of transactions, increasing the likelihood of catching problems, issues and outliers. By flagging high-risk transactions, KPMG can deploy professionals to focus on solving real problems rather than adjudicating false positives or meaningless issues. In TBR’s view, this represents the proverbial “higher-value task” long-promised by robotic process automation, AI and analytics.
 
When pressed by TBR, KPMG leaders said clients were not looking for rate cuts but rather for higher-quality audits and new insights into their operations. Importantly, clients also expect to spend less time on an audit, freeing up professionals’ time: The client can do what they do, and KPMGers can stay focused on reflected issues and generate new insights.
 
TBR remains a bit skeptical, but if clients do not expect a rate cut when KPMG deploys AI to speed up the audit process and instead expect to spend less time internally on what should be a higher-quality audit, TBR considers that a fantastic way to position AI while also reducing KPMG’s professionals’ time. There are two unanswered questions: What happens to the apprenticeship model, in which less-experienced KPMG professionals learn the art, not the science, of audit? And, in a few years, will 95,000 professionals conduct 400,000 audits (twice the current number) or will 50,000 professionals (half the current staff) complete 200,000 audits?
 
Regardless, as the company rolls out internally developed generative AI (GenAI) tools, the learning and experience captured through the firm’s implementation and change management process will undoubtedly be integrated into customer engagements involving third-party solutions. With SAP and Salesforce in attendance, KPMG zeroed in on each vendor’s AI strategy and how the firm plans to support it. To focus on Salesforce, Lohr echoed Salesforce CEO Marc Benioff in calling Agentforce the most successful Salesforce launch ever, which suggests a recognition from KPMG leadership of Salesforce’s agentic AI strategy.
 
For its part, KPMG highlighted the recent launch of an Agentforce Incubator, an experimental experience that can be delivered to clients from any location — a client site, Salesforce event or a KPMG office — to ignite the ideation stage and begin exploring the road map from proof of concept to production. During one-on-one conversations, TBR explored KPMG’s view of its role in the agentic AI, and we found it to be both pragmatic and valuable — similar to how the firm must be opinionated in broader digital transformation engagements.
 
KPMG’s journey to becoming an AI orchestrator will require the firm to take a stance on a vendor-by-vendor basis and arrive on-site with a preconceived understanding of the best path forward for clients given their goals. In addition to having an opinion, KPMG also recognizes it must help facilitate the road maps it lays out to clients, which will involve a heavy change management component, as well as a more technical design and development element. With the Agentforce example, once a targeted business outcome is established, an AI agent needs to be designed and developed to achieve the outcome. In many cases, a customer may lack the internal technical resources necessary to build the agent and tackle the problem. As KPMG avoids vendor agnosticism, the company can focus on building out technical resources with the vendors it chooses, building deeper benches with technical training associated with its strategic partners.

KPMG’s Lakehouse offers unique setting for analyst event

As it did less than 18 months ago when KPMG broke from the traditional analyst event style, the firm did it again. Hosting 62 analysts and dozens of global executives, clients and partners at a flagship Lakehouse facility for two days of both formal and informal interactions, presentations, client use cases and demos, KPMG demonstrated agility in terms of the delivery and engagement format, yet, with a steady hand, continued to execute on its vision with its global solutions — Connected, Powered, Trusted and Elevate — and proven IP, methods and enablers coming together through Velocity.
 
KPMG held one-on-one sessions between analysts and executives midway through the first day so that executives were present and engaged. Additionally, KPMG saved the all-about-AI-and-nothing-else sessions for the second day, which came off as, “We get AI is important, but we are also realistic and keeping our heads on straight and not being ‘me too, me too’ about AI.” KPMG senior executives sat in on both the client case study and platform breakout sessions. Subtle message to analysts: This stuff matters enough across the firm to be worth KPMG partners’ time even if it is not in their area.

Conclusion

As a member of the Big Four, KPMG has brand permission and a breadth of services that are relevant to nearly every role in any enterprise. As the firm executes on its Collective Strategy, TBR believes KPMG will accelerate the scale and completeness of its offerings, building on a solid foundation and expanding the gaps between KPMG and other consulting-led, technology-enabled professional services providers. 

KPMG’s global solutions — Connected, Powered, Trusted and Elevate — which resonate with clients and technology partners, have now been brought together into one transformation framework under KPMG Velocity, providing KPMG’s professionals with clear insight into the firm’s strengths and strategy, and underpinning, in the near future, all KPMG’s transformation engagements. KPMG Velocity’s evolving strategy will challenge KPMG’s leaders to execute on the promise of that transformation during the next wave of macroeconomic pressures, talent management battles and technology revolutions. At the same time, KPMG’s leaders recognize that their priorities are transforming the firm’s go-to-market approach, unlocking the power of the firm’s people, reimagining ways of working, and innovating capabilities and service enhancements. 

Success in executing these priorities, in TBR’s view, will come as KPMG shifts from building a foundation to scaling alongside the growing needs of its clients and as the era of GenAI presents yet another opportunity and challenge. Striking the right balance between elevating the potential of GenAI as a value creator and accounting for commercial and pricing model implications will test the durability of KPMG’s engagement and delivery frameworks. 

Although the firm has placed in motion many of the aforementioned investments over the past 12 to 18 months, the one opportunity that is changing relates to speed. As one enterprise buyer recently explained to TBR: “GenAI will force all services vendors to change. The [ones] who [will] be [the] most successful will be [those] who do it fast.” With speed comes risk — which KPMG fully acknowledges and is why KPMG Velocity’s offering is a differentiator for the firm in the market. With KPMG Velocity, all of KPMG’s multidisciplinary and heritage risk and regulatory considerations have been embedded across each transformation journey to ensure clients can remain compliant and avoid the pitfalls that can often arise during transformation.

Special report contributors: Catie Merrill, Senior Analyst; Kelly Lesizcka, Senior Analyst; Alex Demeule, Analyst; Boz Hristov, Principal Analyst