Executive Summary / Key Takeaways

• Endava is undergoing a deliberate and painful strategic shift from traditional digital transformation services to an AI-native delivery model, causing near-term revenue erosion and margin compression but potentially building a durable competitive advantage in outcome-based contracts.
• The company's Q1 FY26 results fell short of guidance due to a client credit and slower-than-expected pipeline conversion, forcing management to adopt a more conservative methodology that excludes unsigned large deals, reflecting the execution risk inherent in this transition.
• Endava's nearshore delivery model and proprietary Dava Flow framework offer genuine differentiation against larger competitors, but the company lacks the scale of rivals like EPAM (EPAM) and Cognizant (CTSH), leaving it vulnerable to client concentration and macro-driven budget cuts.
• The Banking and Capital Markets segment remains a bright spot with 37% growth, while the legacy Payments vertical continues to decline, illustrating how Endava's AI-driven core modernization approach is gaining traction in some verticals while traditional services face headwinds.
• Investors should monitor Dava Flow adoption rates and the conversion of the growing pipeline of large, outcome-based deals, as these will determine whether Endava can achieve the productivity gains and margin expansion management promises.

Setting the Scene: From Agile Native to AI Native

Endava plc, founded in 2000 and headquartered in London, spent its first two decades building a reputation as an agile-native digital transformation partner for financial services, TMT, and other industries. For most of its history, the company competed on the quality of its software engineering and nearshore delivery from Latin America, offering clients a cost-effective alternative to purely onshore providers. This positioning served Endava well enough to reach £772 million in annual revenue by FY25, but it also left the company vulnerable to the commoditization pressures that have plagued traditional IT services.

The strategic inflection point arrived in fiscal 2023, when management recognized that generative AI represented not just another technology wave but a fundamental reordering of how software gets built and delivered. Rather than incrementally adding AI tools to existing services, Endava made the bold decision to become "AI native"—embedding AI into every activity of the delivery lifecycle and rebuilding its operating model around what it calls Dava Flow. This transformation is not a marketing rebrand; it is a deep cultural and operational shift that touches every aspect of the business, from talent recruitment to pricing models to client engagement.

This matters because the IT services industry is experiencing a structural disruption. Traditional time-and-materials (T&M) contracts, where revenue grows linearly with headcount, are being displaced by AI-driven productivity gains that allow clients to achieve the same outcomes with fewer hours. Endava's management explicitly acknowledges this dynamic: "As we're delivering a much higher productivity, that is having an erosion on the revenue that's coming through the business." The company is essentially cannibalizing its legacy revenue stream to build a more defensible, higher-margin business. This creates a classic innovator's dilemma: the faster Endava succeeds at AI adoption, the more pressure it faces on near-term revenue.

Endava operates in a $500 billion global IT services market, competing against a spectrum of players from boutique consultancies to global giants. The company sits in the uncomfortable middle tier—larger than niche players but dwarfed by behemoths like Cognizant ($5.4 billion quarterly revenue) and EPAM Systems ($1.4 billion quarterly revenue). This scale disadvantage manifests in multiple ways: less bargaining power with talent, higher relative overhead, and limited ability to compete for the largest enterprise deals. However, Endava's Latin American nearshore footprint provides a 20-30% cost advantage versus purely onshore competitors, while offering better time zone alignment and cultural proximity to North American clients than purely offshore Indian firms.

Technology, Products, and Strategic Differentiation

Endava's Dava Flow framework represents the core of its AI-native transformation. Purpose-built for an environment where autonomous software agents participate in delivery, Dava Flow organizes the delivery lifecycle into four feedback-linked phases: Signal, Explore, Govern, and Evolve. Management positions this as "the next progression beyond agile," embedding AI into every activity to create a continuous stream of change. The framework is not merely a methodology but a proprietary system that Endava claims can deliver 5-10x productivity improvements on certain tasks.

This productivity leap creates both opportunity and risk. On one hand, it enables Endava to shift toward outcome-based pricing, where the company shares in the value created rather than simply billing for hours. Currently, 24% of revenue comes from outcome-based contracts, and management sees this rising. These deals can carry higher margins because Endava captures a portion of the productivity gains. On the other hand, the productivity gains erode traditional T&M revenue, creating a revenue headwind that management estimates at 3% impact to FY26 adjusted PBT margin from the transformation alone.

The company backs up its productivity claims with specific client examples. For a U.S. retail pharmacy chain, AI-enabled reviews and automated testing reduced manual effort by 25-30% and shortened migration time by 20-25%, implying a 30-35% productivity uplift. For a global energy provider, AI-assisted tools enabled code changes up to 30 times faster. These are not incremental improvements; they represent step-function changes in how software gets delivered. The "so what" for investors is that if Endava can consistently deliver these results, it can justify premium pricing and capture market share from slower-moving competitors.

Endava's partnership strategy accelerates this transformation. The company was selected for OpenAI's exclusive beta services partner program, becoming an implementation partner for Google (GOOGL) Agent Space, and forming alliances with AlixPartners, SideFX, and Backbase. These partnerships serve two purposes: they validate Endava's AI capabilities in the market, and they generate incremental pipeline opportunities. The OpenAI collaboration has already produced client acquisitions in insurance, while the Google partnership involves over 30 agent-based projects. However, these partnerships also create dependency—Endava's AI solutions are built on top of hyperscaler platforms, meaning it must constantly differentiate its value-add to avoid commoditization.

Financial Performance & Segment Dynamics

Endava's Q1 FY26 results illustrate the friction of transformation. Revenue declined 8.6% year-over-year to £178.2 million, missing guidance due to an unexpected client credit and slower pipeline conversion. Management described the credit as a "procedural matter" unrelated to work quality, but the bigger issue was that non-large strategic pipeline opportunities converted at only 50% of the high-end guidance assumption. This forced the company to adopt a more prudent approach to conversion assumptions for the remainder of the fiscal year.

The segment performance reveals a tale of two businesses. Banking and Capital Markets (BCM) grew 37.4% in FY25 and remains a strength, driven by core modernization projects where Endava's AI-driven approach is gaining traction. A large North American BCM client quadrupled its quarterly spend over the past year, demonstrating the value of Endava's specialized capabilities. Conversely, the Payments vertical declined 19% in FY25 as large clients reduced spend, though management notes it has stabilized compared to faster declines a year ago. The TMT segment weakened due to a large media client being acquired and shutting down Endava's project, while Mobility declined 11.7% due to planned ramp-downs.

The Healthcare segment's 103.8% growth in FY25 was entirely driven by the GalaxE acquisition, which expanded Endava's North American healthcare presence. While this acquisition provided scale, integration costs and operational alignment challenges are pressuring margins. Management expects the GalaxE systems cutover to complete by February 2025, with further cost optimization opportunities in FY26. The "so what" is that acquisitions can buy growth but not necessarily profitability, especially during a business model transformation.

Margin pressure is evident across the business. Adjusted PBT margin was 10.6% in FY25, down from 11.2% in FY24, and management expects a 3% negative impact in FY26 from the AI transformation and reinstated bonus scheme. The gross margin of 24.77% lags competitors like Globant (GLOB) (35.71%) and Cognizant (34.06%), reflecting Endava's smaller scale and higher relative overhead. However, the company maintains a healthy balance sheet with £47.2 million in cash and £193.2 million in borrowings, resulting in net debt of £146 million—manageable but not negligible for a company with £9.2 million in quarterly free cash flow.

Outlook, Management Guidance, and Execution Risk

Endava's FY26 guidance reflects both caution and confidence. Management lowered the full-year revenue range to £735-752 million, representing a 4.5% to 2.5% constant currency decline, down from the previous top-end of £765 million. This downgrade stems from the Q1 miss and a more conservative methodology that excludes unsigned large strategic deals until work begins. However, the guidance includes three recently signed large engagements that are expected to contribute roughly 50% of the revenue ramp in the second half.

The guidance methodology itself reveals management's learning process. Since May 2025, the company has excluded revenue from any unsigned large strategic opportunity until the statement of work is executed and delivery has begun. For non-large deals, management makes an assessment of conversion likelihood but has now lowered those assumptions after Q1's experience. This creates a more credible guidance framework but also means any upside from large deal wins will be back-end loaded and potentially not reflected in guidance until late in the cycle.

Management's commentary suggests the pipeline remains robust but conversion is unpredictable. "The fast moving nature of the AI world and the rate at which from a technical point of view, things are changing means that clients are hesitating to move fast and jump into their new programs," CEO John Cotterell explained. This client hesitation is exacerbated by macroeconomic turbulence, with some clients entering take-private discussions, others announcing cost-takeout programs, and automotive clients prioritizing supply chain reviews over IT projects. None of these deals are lost, but all have been pushed back.

The critical execution variable is Dava Flow adoption. Over 70% of services are now AI-related, up from just over 50% in the prior quarter, and more than half the workforce actively uses AI in projects. Management claims tasks that took days are now completed in minutes, with regular 10x productivity improvements. If these gains can be scaled across the organization, they should enable Endava to deliver on its outcome-based contracts profitably while improving margins. However, the "friction element" of training and adapting the workforce is impacting short-term margins, and attrition is running higher than historical levels as employees churn through the skills transition.

Risks and Asymmetries

The most material risk is that Endava's AI transformation fails to deliver the promised productivity gains at scale. While pilot projects show impressive results, scaling Dava Flow across thousands of employees and hundreds of clients is a different challenge. If the productivity improvements prove inconsistent or require more human oversight than anticipated, the outcome-based contracts could become margin-dilutive rather than accretive. Management acknowledges this risk, noting that the shift is causing "some erosion on revenue from the old time and materials model in the short term" while promising margin improvement in "outer years."

Client concentration amplifies execution risk. The top 10 clients represent 36% of revenue, with the largest clients showing declining average spend (£6.4 million in Q1 FY26 vs. £7.1 million a year ago). The loss or reduction of any major client—such as the large payments client that reclassified from UK to North America—creates immediate revenue headwinds. This concentration also gives clients leverage in negotiations, potentially pressuring pricing even as Endava tries to shift to value-based models.

Macroeconomic uncertainty creates a volatile demand environment. Management describes "inconsistent behavior from some clients with their business priorities shifting rapidly" and notes that "clients' desire to innovate remains strong; however, they are slow to sign large contracts in the current uncertain macroeconomic environment." This hesitation directly impacts pipeline conversion, which fell to 50% in Q1. If global macroeconomic turbulence increases, Endava could face both delayed new signings and unplanned ramp-downs on existing projects, as seen in the UK and Rest of World regions.

Competitive pressure is intensifying at the commodity end of the market. While Endava is "driving away from the commodity end anyway," clients are increasingly asking whether application maintenance and similar services can be done cheaper. This creates a squeeze on the remaining T&M revenue while the company invests heavily in higher-value AI capabilities. Larger competitors like Cognizant can leverage their scale to offer integrated solutions, while smaller, nimbler firms can undercut on price.

Valuation Context

At $6.67 per share, Endava trades at a market capitalization of $362 million and an enterprise value of $622 million, reflecting a challenging operating environment. The stock's valuation multiples tell a story of a company in transition: the price-to-sales ratio of 0.36x is well below peers like EPAM (2.19x) and Globant (1.22x), suggesting the market has priced in significant headwinds. The price-to-free-cash-flow ratio of 5.05x appears attractive but must be viewed in context of declining cash generation and margin pressure.

Endava's balance sheet provides some cushion but also reveals constraints. With £47.2 million in cash and £193.2 million in borrowings, the company carries net debt of £146 million. This represents a debt-to-equity ratio of 0.43, which is manageable but higher than EPAM's 0.04 and Cognizant's 0.08. The company's return on equity of 1.81% and return on assets of 1.94% significantly trail competitors, reflecting both margin pressure and asset intensity from the GalaxE integration.

The gross margin of 24.77% lags the peer group, with Globant at 35.71% and Cognizant at 34.06%, highlighting Endava's scale disadvantage. However, the company's operating margin of -1.63% is a function of transformation investments rather than structural unprofitability. Management expects these investments to pressure margins by 3% in FY26 before yielding improvement in outer years.

Comparing Endava to direct competitors reveals its positioning. EPAM Systems, with $1.4 billion in quarterly revenue and 19.4% growth, demonstrates the scale and momentum that Endava lacks. EPAM's enterprise value of $10.5 billion reflects its market leadership in digital engineering. Globant, at $3 billion market cap and 3.9% growth, shows the valuation premium for consistent, profitable expansion. Thoughtworks (TWKS), with negative margins and stagnant growth, represents the risk case for failing to adapt. Cognizant's scale and 7.4% growth illustrate the competitive pressure from larger incumbents.

Endava's valuation suggests the market is pricing the company as a show-me story. The low revenue multiple reflects skepticism about the AI transformation's ability to drive growth and margin expansion. However, if management can execute on the Dava Flow rollout and convert its pipeline of large outcome-based deals, the valuation could re-rate as investors gain confidence in the new business model's economics.

Conclusion

Endava stands at a critical inflection point where short-term pain from its AI-native transformation could either create a durable competitive moat or expose fundamental scale disadvantages that larger competitors exploit. The company's decision to accelerate the shift away from time-and-materials contracts, while causing immediate revenue erosion and margin compression, positions it to capture a disproportionate share of the enterprise AI services market as clients move beyond pilot projects to full-scale implementation.

The central thesis hinges on two variables: Dava Flow's ability to consistently deliver 5-10x productivity gains at scale, and Endava's capacity to convert its growing pipeline of large outcome-based deals into profitable revenue. The Q1 FY26 miss and guidance cut demonstrate that execution risk is real, particularly around pipeline conversion and client decision-making in a volatile macro environment. However, the 37% growth in Banking and Capital Markets and the new $100 million payments relationship suggest the AI-driven core modernization approach is resonating where it matters most.

For investors, the risk/reward asymmetry is clear. Downside risk includes further margin compression if the transformation costs exceed expectations, client concentration leading to unexpected revenue drops, and competitive pressure from larger players with deeper resources. Upside potential comes from margin expansion as Dava Flow scales, market share gains in high-growth verticals like healthcare and BCM, and a valuation re-rating as the market gains confidence in the new business model. The next two quarters will be decisive in determining whether Endava's AI-native gamble pays off or whether the company becomes a cautionary tale about the challenges of transforming a services business in real-time.