Endava (DAVA) Q1 2026 Earnings Call Transcript

Image source: The Motley Fool.

DATE

Tuesday, Nov. 11, 2025 at 8:00 a.m. ET

CALL PARTICIPANTS

• Chief Executive Officer — John Cotterell
• Chief Financial Officer — Mark Thurston

Need a quote from a Motley Fool analyst? Email pr@fool.com

RISKS

• Revenue decline -- Revenue decreased 8.6% year-over-year to £178.2 million, primarily due to an unexpected client credit and lower conversion of non-strategic pipeline opportunities.
• Margin compression -- Adjusted profit before tax (PBT) margin fell to 5.5% from 9.9%, as productivity gains from AI adoption reduced billable volumes under traditional models.
• Operating loss -- Loss before tax of £8.5 million compared to a prior-year profit of £4.2 million.
• Pipeline conversion headwinds -- Management reduced guidance, stating, "we've taken a more prudent line on the pipeline conversion in the non-strategic deal space."

TAKEAWAYS

• Revenue -- £178.2 million for the three months ended Sept. 30, 2025, representing an 8.6% decrease year-over-year; down 7.3% in constant currency terms.
• Adjusted profit before tax (PBT) -- £9.9 million for the three months ended Sept. 30, 2025, down from £19.2 million in the same period in the prior year.
• Adjusted diluted earnings per share -- £0.05 for the three months ended Sept. 30, 2025, a decrease from £0.25 in the same period in the prior year, based on a reduced share count of 53.2 million diluted shares.
• Geographic revenue mix -- North America comprised 42% of revenue, Europe 24%, UK 28%, and Rest of World 6%; North America revenue decreased 1% due to FX, with underlying constant currency growth.
• Client concentration -- Ten largest clients contributed 36% of total revenue, consistent with the prior year; average spend per top client declined 9.9% to £6.4 million, with 2% of that decline from FX.
• Adjusted free cash flow -- £9.2 million, up from £3.5 million in the prior year.
• Borrowings -- £193.2 million at period-end, up from £180.9 million sequentially and £132.6 million year-over-year.
• Capital expenditure -- 1.7% of revenue, compared to 0.6% in the prior year.
• Headcount -- 11,636 employees, a 2% decrease year-over-year, with targeted hiring in AI roles through the DARVAx Academy resulting in 470 new hires.
• Strategic deals -- Three large signed agreements, including a five-year, up to $100 million partnership with a payments company, are expected to provide step-change revenue contributing roughly half of second-half ramp-up.
• Delivery model shift -- Outcome-based contracts comprised 24% of revenue with 76% from time-and-materials; management noted rapid progression toward AI-native delivery models, stating, "over 70% of our services are AI related."
• Pipeline guidance methodology -- Revenue from unsigned large strategic deals is excluded from guidance until contract execution and delivery begin; non-large opportunities are assessed for likelihood and timing.
• Q2 guidance -- Revenue expected between £179 million and £182 million, a constant currency decrease of 8%-7% year-over-year; adjusted diluted EPS projected at £0.15-£0.17.
• Full-year 2026 guidance -- Revenue expected between £735 million and £752 million, down 4.5%-2.5% in constant currency year-over-year; full-year adjusted diluted EPS forecast at £0.80-£0.88.
• Share repurchase -- As of Oct. 31, 2025, Endava (NYSE:DAVA) repurchased 7.1 million ADSs for $115.9 million, with $34.1 million authorization remaining.

SUMMARY

The quarter's financial underperformance was primarily attributed to an unanticipated client credit event and lower conversion of non-strategic pipeline opportunities. Management attributed revenue and margin headwinds to accelerated adoption of AI-native delivery, which is causing short-term compression in billable activity under legacy models. Endava underscored that recent large deals, including a five-year $100 million payments partnership and two additional multiyear contracts, are already signed and will be material drivers for second-half revenue acceleration. The company described a disciplined shift in client engagement, noting that outcome-based contracts are rising and that over 70% of delivered services now include AI components. Leadership indicated ongoing investment in workforce upskilling, higher attrition relating to this technology pivot, and clear prioritization of AI capability development supported by measurable client productivity gains.

• Cotterell said, "So the $100 million deal is not a renewal of one of our larger payments clients. It is an existing payment client, but really quite small. And well over 85-90% of that deal is net new revenue to us," clarifying the impact and nature of this major partnership.
• Management confirmed their guidance methodology excludes unsigned large deals, providing greater visibility for forecasted figures.
• Thurston explained, "we've taken a more prudent line on the pipeline conversion in the non-strategic deal space," directly addressing reduced conversion assumptions.
• Recruitment efforts focused on AI talent, with DARVAx Academy receiving 2,900 applicants and yielding 470 hires, signaling a substantial internal workforce transition.
• Endava's adjusted free cash flow rose while cash and cash equivalents fell sequentially and year-over-year, suggesting working capital or investment-related outflows.
• The shift to outcome-based, AI-enabled client solutions is eroding traditional time-and-materials revenue but is expected to support improved margin and growth as the transition matures.

INDUSTRY GLOSSARY

• Dava Flow: Endava's proprietary AI-native delivery life cycle framework, incorporating autonomous software agents and iterative, feedback-linked phases to drive productivity and operational efficiency in technology projects.
• Outcome-based contracts: Engagements that tie payment and revenue to defined client results or deliverables rather than time and material inputs.
• Time and materials (T&M): A contract model where the client is billed based on hours worked and materials used, as opposed to fixed or outcome-based pricing.
• Agentic workflows: Processes enhanced or executed by autonomous AI agents designed to independently handle specific tasks within a digital or operational framework.
• SDLC: Software development life cycle, the structured process followed for software creation and evolution, referenced in context of AI-driven productivity improvements.
• DARVAx Academy: Endava's internal program aimed at recruiting and training AI-native talent across delivery locations.

Full Conference Call Transcript

John Cotterell, Endava's Chief Executive Officer, and Mark Thurston, Endava's Chief Financial Officer. Before we begin, a quick reminder to our listeners. Our presentation and our accompanying remarks today include forward-looking statements, including, but not limited to, statements regarding our guidance for Q2 fiscal year 2026 and for the full fiscal year 2026, the impacts of headwinds facing our industry and business trends in our industry, including with respect to developments with AI enhancements to our technology and offerings, our pipeline of client opportunity and our ability to convert such opportunities into contracted orders.

The benefits of our partnerships, our pricing models, demand from clients for our technology services, our ability to create long-term value for our clients, our people, and our shareholders, and our business strategies, plans, operations, and growth opportunities. These statements are subject to risks and uncertainties that could cause actual results to differ materially from those contained in the forward-looking statements. Actual results and the timing of events may differ materially from the results or timing predicted or implied by such forward-looking statements, and reported results should not be considered as an indication of future performance.

Please note that these forward-looking statements made during this conference call speak only as of today's date, and we undertake no obligation to update them to reflect subsequent events or circumstances other than to the extent required by law. For more information, please refer to the Risk Factors section of our annual report filed with the Securities and Exchange Commission on 09/04/2025, and in other filings that Endava makes from time to time with the SEC.

Laurence Madsen: Also during the call, we'll present both IFRS and non-IFRS financial measures. While we believe the non-IFRS financial measures provide useful information for investors, the presentation of this information is not intended to be considered in isolation or as a substitute for the financial information presented in accordance with IFRS. Reconciliation of such non-IFRS measures to the most directly comparable IFRS measures are included in today's earnings press release, as well as the investor presentation, both of which you can find on our Investor Relations site or on the SEC website. A link to the replay of this call will also be available on our website. With that, I'll turn the call over to John.

John Cotterell: Thank you, Laurence, and welcome everyone. We appreciate you joining us for our first quarter fiscal year 2026 earnings call. Endava continues to be deeply engaged by and with major companies across the world as they look for support in navigating the journey towards AI, whilst ensuring operational resilience in existing platforms and devices. We believe the partnerships with major technology giants and the decisions we took three years ago led to the development of our AI native change delivery life cycle, now branded Dava Flow, see us well placed for the coming years. However, we continue to navigate the challenges associated with this transition in business models, delivery approach, and acceleration of the new AI-driven digital wave.

The first quarter results were lower than guided, primarily due to an unexpected credit made to a client that arose subsequent to our last earnings call, as well as certain non-large strategic pipeline opportunities that did not convert into revenue during the quarter as anticipated. While these factors weighed on our performance, our ability to secure a multiyear strategic relationship with a leading payments company of up to $100 million demonstrates the strength of our client relationships. This partnership will utilize the best of Endava's global delivery case capability as well as our AI and advanced engineering capabilities to streamline our clients' technology platforms and enhance existing capabilities.

This represents a prime example of the type of deal and partnership we are targeting. Utilizing our capability as an AI native technology agnostic transformation partner, our broader partner ecosystem is already generating incremental potential pipeline opportunities, and client interest in Dava Flow is accelerating. I will return to each of these topics later in the call. Following the sales leadership realignment announced last quarter, we recently hired a Chief Growth Officer for Commercial Services, for Europe and North America. These changes are already sharpening our customer engagement model, which is evident in the composition of our potential opportunity pipeline, which we are tracking closely.

We remain committed to disciplined cost management to protect margins while continuing to focus on growth. Starting with an update on our AI-related engagements. AI now anchors many clients' technology roadmaps, and we are partnering across a spectrum of projects, from early proof of concept to enterprise-wide rollouts and subsequent optimization efforts. Following the engagement for a leading U.S. healthcare services provider, where we deployed AI to automate the intake and summarization of medical bills and supporting documentation, we have now advanced integration into the clients' adjuster portal and enable both new real-time and scheduled processing support peak volumes.

The architecture is built for compliance and auditability, U.S. data residency, and targets high accuracy to meet over 95% precision while holding unit costs below 0.5% per page. Early performance indicates faster, more consistent decisions and a clear path to materially lower per claim handling costs. Building on the enterprise ChatGPT program, our collaboration with a leading financial compliance technology provider has progressed. We partnered with OpenAI to drive a company-wide deployment of ChatGPT Enterprise anchored in governance and enablement. Within three months, more than 500 licenses were rolled out with a single sign-on, role-based access, and audit logging.

Key team members across finance, legal, IT client services, and support received train-the-trainer enablement to develop high-value use cases and custom GPTs reinforced by structured communication, weekly show-and-tell sessions, and continuous measurements. Adoption has scaled, with growing catalogs of validated use cases, and measurable productivity gains are emerging in document workflows and client service operations. These first two client cases are examples we have previously discussed on earnings calls, and I'm covering them to show how these engagements are progressing, to show how engagements are building and deepening once production solutions are in place. For a leading U.S. retail pharmacy chain, we are modernizing a core handheld application by upgrading its code base using AI-assisted analysis, leveraging GitHub Copilot.

We completed a comprehensive assessment and prepared a two-phase execution plan that targets the highest impact fixes and de-risks the upgrade. The resulting playbook is designed to be repeatable across other applications, strengthen security, reduce technical debt, and support a faster release cadence. Initial results indicate AI-enabled reviews and automated testing are lowering manual effort by between 25-30% and shortening migration time by between 20-25%, implying a projected productivity uplift between 30-35% once both phases are completed. For a global energy and utilities provider that runs large-scale power grid simulations, we migrated a 400,000-line Fortran system. We built AI-assisted passes and automation tools with agent coding tools to preserve program flow while refactoring syntax and improving memory management.

We also identified code sections tied to domain concepts to speed future feature delivery. This approach reduced manual edit risk and enabled automated conversion at scale. Initial benchmarks indicate up to close to 30 times faster code changes with improved reliability. For an e-learning serving over 12,000 healthcare and human services organizations, we developed an AI-enabled content studio that streamlines the entire content life cycle: drafting, review, quality assurance, export, and accreditation for a catalog of 7,000 plus courses. Built on Windsurf and integrated with the client's enterprise AI infrastructure, the platform generates course outlines and transcripts, runs policy-based QA agents, automates SCORM imports, and compares accreditations standards. Automation rules and validation tests further enhance compliance and operational consistency.

Results show end-to-end authoring efforts have fallen by approximately 30% and modeling shows projected time savings of 30% to 50% when scaling updates across the full course library. Turning to partnerships, our investment in our partnership with OpenAI is expanding. As we've enrolled a group of Endava engineers in OpenAI's newly launched partner-exclusive certification program. Our team is pursuing multiple opportunities across the OpenAI product suite through training created by OpenAI that is only available to service partners. This is another step to deepen our knowledge and advance our AI native to delivery capability. On the commercial side, the joint go-to-market framework we created in partnership with OpenAI is producing measurable results, with wins in the insurance sector.

We continue to grow our dedicated Google Cloud business unit. In collaboration with Google Cloud, we continue to increase the number of Gemini enterprise projects that we are actively engaged in. Each engagement follows a production-grade reference architecture with explicit safety and audit controls, ensuring that pilot outcomes can be migrated into compliant enterprise environments. One of these projects involves a leading UK bank, where we are rolling out AI-enabled digital assistance that give employees fast, secure access to internal and market data. Early pilot results indicate shorter query resolution times and improved policy compliance, laying a foundation for institution-wide adoption of agentic workflows.

We also continue to strengthen our partnership with Salesforce by investing in AgenTik AI and innovation, with a focus on applying agent force across Salesforce's core clouds to assist customer-facing teams, streamline operations, and unlock new levels of engagement and productivity. This reflects Endava's commitment to staying at the forefront of Salesforce innovation and helping clients turn emerging AI capabilities into real measurable impact. And now with an update on our large strategic deals, defined as multiyear large-scale engagements. In addition to the multiyear payments deal I mentioned earlier, we deepened our engagement with Convex, an international specialty reinsurer, by signing a new agreement.

This builds on the success we have achieved together in recent years as Convex continues to invest in innovative technology deliver consistently high-quality service. This partnership enables us to deliver a range of capabilities enabling Convex to continue creating a business that has data at its heart and a strong emphasis on analytics to make better underwriting decisions. In mobility, we have extended and expanded our long-standing partnership with Toyota Racing Development, as their official IT consulting partner in 2026 and beyond. As part of the partnership, Endava will leverage its AI-enabled accelerators and frameworks to modernize core Toyota racing development production systems and enable digital transformation for the business.

Next, let me outline how our delivery model is evolving and what that means to execution and client outcomes. The pace of AI innovation remains exceptionally fast, and the nature of our client discussions has evolved just as quickly. Where a few courses ago we were explaining foundational concepts such as intelligent agents, we are now examining how those agents can be deployed to deliver measurable efficiency across customer-facing and core operations. Clients are starting to move beyond the search for a single killer app application and are instead seeking opportunities to embed AI throughout their technology stacks and operating models.

This marks the beginning of the transition from chasing incremental changes brought about by embracing AI to notable productivity changes. We're now spending time shaping larger-scale projects, can only be delivered through the strategic adoption of AI. Purpose-built for an environment in which autonomous software agents participate in delivery, Dava Flow treats flow as the next progression beyond agile. By embedding AI into every activity, the delivery life cycle is organized into four yet feedback-linked phases: Signal, Explore, Govern, and Evolve. Throughout all phases, human oversight, human in the loop guides AI contributions, and the system learns and improves with each cycle. In Signal, we deploy market and estate scanning agents to surface and qualify opportunities.

The agent reacts to signals in the market or client environment and feeds qualified opportunities into the life cycle with confidence scores. In Explore, we use human-AI collaboration to convert these signals into evidence solution designs, producing prototypes, requirements, and models at pace. The aim is to reduce uncertainty and finalize what needs to be built supported by evidence. In Govern, we assemble and automate the build. Engineer oversight combines with agent-generated code to enforce best-in-class controls. Evolve is the post-deployment phase where the solution is in production with continuous improvement. Human in the loop checkpoints span every phase so that each iteration strengthens the next.

AI agents watch the system's telemetry, user behavior, and performance data to detect anomalies or opportunities. Across the four phases, we take our lifetime experience of distributed agile at scale and optimize our approach to best organize agents at work, agentic checkpoints, and humans in the loop at the core of the new approach. We have equipped our teams with playbooks and training materials, and all delivery teams are expected to complete Endava flow training and immersion before the close of the current financial year. We ended the quarter with 11,636 Endavans, representing a 2% decrease from the same period last year.

We are deepening our AI talent pool and embedding new capabilities across the business, positioning Endava to help clients turn emerging technology into near-term operational gains. We're expanding and upskilling our AI talent while trimming roles where market demand has declined. Our inaugural DARVAx Academy, created to train the next generation of AI-skilled professionals, drew 2,900 applicants and resulted in 470 hires across nine delivery locations. And our recent Tech Fest engineering event brought together those new hires working in 48 cross-functional teams to address 24 client-inspired challenges. Every team produced a working minimal viable product under mentor guidance.

Before we conclude, I want to recognize every Endarvon for the perseverance and focus you continue to show as we steer through this period of rapid digital evolution and translate change into opportunity. Our priorities remain clear: sustain growth that endures, safeguard the distinctive culture that defines us, and deliver technology solutions that equip our clients to set the pace confidently in an ever-shifting market. I'll now hand over to Mark for a closer look at our quarterly financial results and guidance for the upcoming quarter and the remainder of the fiscal year.

Mark Thurston: Thanks, John. Endava's revenue totaled £178.2 million for the three months ended 09/30/2025, compared to £195.1 million in the same period in the prior year, representing an 8.6% decrease. In constant currency, our revenue decreased 7.3% from the same period in the prior year. As John already mentioned, the first quarter results were lower than anticipated, primarily due to a matter in the United States, relating to an unexpected credit made to a client that arose subsequent to our last earnings call, as well as failure to convert certain non-large strategic pipeline opportunities into revenue as previously anticipated.

Loss before tax for the three months ended 09/30/2025, was £8.5 million, compared to a profit of £4.2 million in the same period in the prior year. Our adjusted PBT for the three months ended 09/30/2025 was £9.9 million, compared to £19.2 million in the same period in the prior year. Our adjusted PBT margin was 5.5% for the three months ended 09/30/2025, compared to 9.9% for the same period in the prior year. Our adjusted diluted earnings per share was £0.05 for the three months ended 09/30/2025, calculated on 53.2 million diluted shares as compared to £0.25 in the same period in the prior year calculated on 59.4 million diluted shares.

Revenue from our 10 largest clients accounted for 36% of revenue for the three months ended 09/30/2025, in line with the same period last fiscal year. The average spend per client from our 10 largest clients decreased from £7.1 million to £6.4 million for the three months ended 09/30/2025, as compared to the three months ended 09/30/2024, representing a 9.9% year-over-year decrease. Of this, FX movement contributed to a 2% year-over-year decrease, and the rest of the decline is in line with the rest of the business. In the three months ended 09/30/2025, North America accounted for 42% of revenue, Europe for 24%, UK for 28%, while the rest of the world accounted for 6%.

Revenue from North America decreased by 1% for the three months ended 09/30/2025, over the same period last fiscal year. The decrease was driven by FX, with underlying constant currency growth. The unexpected client credit mentioned in my opening comments is more than offset by the reclassification of a large payments client from the UK to North America. The relationship with the client is now based there. Comparing the same periods, revenue from Europe declined 12.8% due mainly to weakness in the TMT and mobility verticals. The UK decreased 17.9% due mainly to the reclassification of the client referred to above to North America. And the rest of the world increased 9%.

Our adjusted free cash flow was £9.2 million for the three months ended September 30, 2025, up from £3.5 million during the same period last fiscal year. Our cash and cash equivalents at the end of the period totaled £47.2 million at 09/30/2025, compared to £59.3 million at 06/30/2025, and £52.8 million at 09/30/2024. Our borrowings totaled £193.2 million at 09/30/2025, compared to £180.9 million at 06/30/2025, and £132.6 million at 09/30/2024. Capital expenditure for the three months ended 09/30/2025, as a percentage of revenue, was 1.7%, compared to 0.6% in the same period last fiscal year. We remain committed to our share repurchase program.

As of 10/31/2025, Endava repurchased 7.1 million ADSs for $115.9 million under the program, and we had $34.1 million remaining for repurchase under its share repurchase authorization. Before moving on to the guide, I'd like to provide some context. As a reminder, since May 2025, we are utilizing a guidance methodology under which revenue for any unsigned large strategic opportunity in the pipeline is excluded until the related statement of work is executed and delivery has begun. By contrast, for our non-large strategic deal pipeline, we make an assessment of likelihood and timing of conversion and likely timing of revenue.

Turning to the guide for the remainder of the fiscal year, we have reassessed our non-large deal pipeline and lowered our conversion into revenue assumptions. Additionally, the client-specific issue in the United States weighed on first-quarter results and will continue to affect the remainder of the fiscal year. While the three large signed engagements John highlighted are reflected in our guidance and partially underpin the expected revenue uplift in the second half.

Mark Thurston: Now moving on to our outlook. Our guidance for Q2 fiscal 2026 is as follows: Endava expects revenue to be in a range of £179 million to £182 million, representing a constant currency revenue decrease of between 8-7% on a year-over-year basis. Endava expects adjusted diluted EPS to be in the range of £0.15 to £0.17 per share. Our guidance for the full fiscal year 2026 is as follows. Endava expects revenue to be in the range of £735 million to £752 million, representing a constant currency revenue decrease of between 4.5-2.5% on a year-over-year basis. Endava expects adjusted diluted EPS to be in the range of £0.80 to £0.88 per share.

This above guidance for Q2 fiscal year 2026 and the full fiscal year 2026 assumes the exchange rates on 10/31/2025. The exchange rate was GBP 1 to USD 1.32 and EUR 1.14. This concludes our prepared comments. Operator, we are now ready to open the line for Q&A.

Operator: We will now begin the question and answer session. Your tone phone. First question today comes from Bryan Bergin with TD Cowen. Please go ahead.

Bryan Bergin: Hey, guys. Thanks for taking the question. I guess I'll start on the client credit. Can you share some more detail on this credit that was not foreseen and weighed on performance? Just any sizing of that in context, curious if it was due to company execution or maybe a choice by the client made to pull back on something. Is it isolated or could this reoccur elsewhere?

Mark Thurston: So it was unexpected, Bryan. It arrived after we guided last quarter. It isn't related to remediating work. I'll qualify it as being a more procedural matter. In terms of the impact, if it hadn't happened, we would have been at around the bottom of the revenue guide. And certainly, in terms of EPS, we would have been right in the middle of the range that we set last quarter. I can't really go into any more detail than that at this stage.

Bryan Bergin: Okay. Okay. And I guess on demand and the pipeline conversion then, is that a demand issue or would you say some friction in the changes in the commercial responsibilities? Just curious how whether you would say that demand has or client sentiment has changed much at all here in the last quarter. Maybe if you could just talk about how demand trends progress through the first quarter and to the early part of 2Q now?

John Cotterell: Yes.

Mark Thurston: I mean, in terms of the comment around pipeline conversion in the quarter, the significant impact on revenue was the credit note we just mentioned. Pipeline conversion, we did convert pipeline. So against the high end, it was about 50% of and against the low end, we were about 80%. So not as high as we would have anticipated. But in the light of that sort of performance and the ongoing sort of review of pipeline quality, we've looked at our assumptions for the rest of the year. And that's resulted in it's actually downgrading from top of the guide at £765 million to £752 million.

It is actually offset though by some of the big wins that John highlighted on his script. So they add step change revenue basically in the second half. So they do underpin part of the ramp as we see going through into mainly Q3, Q4, but we've taken a more prudent line on the pipeline conversion in the non-strategic deal space.

Bryan Bergin: Okay, understood. Thank you.

Mark Thurston: Thanks, Bryan.

Operator: The next question comes from Maggie Nolan with William Blair. Please go ahead.

Maggie Nolan: Hi, thank you. I understand the commentary on how you're considering pace of conversions from here for the non-large accounts. But can you comment on whether there's been any client churn at unusual levels in this quarter versus recent past?

John Cotterell: Hi, Maggie. There hasn't been a growth in client churn. And just to be clear, the client that Mark was referring to where we had the credit is an ongoing and not in decline. It's just a more conservative view based on the conversations that we've been having around that inflow of the non-large deal pipeline, which is what we guide against.

Maggie Nolan: Okay. Thank you. And then can you talk a little bit about how you're quantifying any Brexit productivity gains from Endava flow? And just the ability to kind of drive this at scale across your model?

John Cotterell: Yeah. So, we're seeing the AI shift essentially going through two steps. There's the sort of Gen AI with a bit of AgenTik coming in, where organizations are largely applying a bit of an accelerator from AI to an agile methodology. And getting in that sort of 20% to 30% range productivity improvement that people are talking about. What we're seeing with Dava Flow is taking that next step into using agents to do a far bigger element of the design and coding. All under human guidance and government. And through that getting significant step-ups in productivity. In the five to 10 times type range as I covered on the call last time.

Now, for us, that gives us an opportunity alongside some of these bigger deals that we're working on to significantly accelerate transformation and change in client environment. And through doing that, to actually deliver a lot of benefit to the client, but also look at pulling through wider margins through that huge added value that we're delivering. Now, the big deal that I covered with the large payments client is very much based on those principles. Taking that Dava Flow capability to accelerate transformation for them, help with new product development, and some joint go-to-market together. So it's and it's very illustrative of the type of deal larger deal that we're working on.

And, but we're not putting into our guidance as Mark is highlighted over the last couple of quarters.

Maggie Nolan: Thank you.

John Cotterell: Thanks, Maggie.

Operator: The next question comes from Nate Svensson with Deutsche Bank. Please go ahead.

Nate Svensson: Hey, thanks for the questions. John, wanted to go back to something you said at the beginning of the prepared remarks. I think you mentioned that you're navigating challenges associated with the transition in business model delivery approach and the acceleration of the AI wave. I guess just from my perspective, given the growth in the business, the lower guide, it seems like there's been some struggles with everything that's going on. So I'm just hoping you can take a step back and maybe talk at a higher on what your strategy is to successfully navigate these changes. I know there's macro considerations, but I guess beyond that, what do you think isn't going right?

And what's the plan internally to try to turn things around and ultimately capitalize on some of the opportunities that are ahead of you?

John Cotterell: Yes. Thanks, Nate. So, for us, we're pushing very, very hard on this shift to being AI native. Our vision is that over the next two to three years, AI becomes a much, much more significant player in our industry in the way in which people deliver to clients, deliver code, deliver requirements, and so on. And in pushing hard on that shift, we are moving much faster away from the old models than I believe many of our peers are. The result of which is that we are accelerating deliveries to clients in the current environment under the old T and M model largely. This quarter, we were 24% outcome-based, which is still rising.

But it does mean that 76% of our revenue is coming in a T and M basis. As we're delivering a much higher productivity, that is having an erosion on the revenue that's coming through the business. That is being offset by the growth in demand for our new AI native approaches. Where every Endavan is using AI every day in the delivery of to our clients. And that shift is very, very fast. Last quarter, I reported that half of just over half of our services were AI related. Covering using AI to change and accelerate the SDLC, software development life cycle. Or identifying client workflows or indeed in deploying AI in the physical world.

This quarter, that greater than half has moved to over 70% of our services. Are AI related on the same measure. So it is a strong shift and strong acceleration productivity. And that is having headline let's say, it's headwinds for us on revenue. On the old model. The strategy and the focus is all around driving the fastest shift we possibly can to the new model. Where we are writing more outcome-based deals with clients which locks in the opportunity to deliver greater benefit to the client using AI, but also to improve our margins. And we are seeing that come through in the rising proportion of outcome-based deals, and in the margins attached. To those deals.

And so that's the strategic shift that we are going through. We are pushing through it very fast and we're probably carrying more pain in the short term. Because of that accelerated shift to the future state. That we're pushing through.

Nate Svensson: Makes sense, and I appreciate the detailed response there. Did want to follow-up on this $100 million deal with a leading payments company. My guess is that would be a renewal with maybe one of your two large payments partners, but maybe you can correct me if that is indication, it was a new logo. But beyond that, maybe you could use that deal as kind of a launch point to expand more into general commentary on pricing and productivity commitments you're having to make in the current difficult macro sort of in order to get these larger deals across the finish line?

John Cotterell: So the $100 million deal is not a renewal of one of our larger payments clients. It is an existing payment client, but really quite small. And well over 85-90% of that deal is net new revenue to us. And it is around helping that client transform their business. They are equally excited about us helping them do that as we are about helping them drive the transformation and bringing our engineering skills to bear on their estate. Mark, do you want to pick up on the pricing?

Mark Thurston: Yes. I mean, pricing, I mean, as John said in terms of the revenues, we are still mainly time and materials. So we'd still look at the average rate per workday and it is very much stable quarter to quarter. Our issue is volume more than anything else certainly in the T and M space.

Nate Svensson: Guys. Nice to hear about the payments win.

John Cotterell: Thanks,

Operator: The next question comes from James Faucette with Morgan Stanley. Please go ahead.

Antonio Jaramillo: Hey, guys. Thanks for the question. It's Antonio on for James. Wanted to ask about your fiscal year 2026 guide. It looks like in the back half there's still a strong acceleration. And I know that you mentioned those three large deals are contemplated in that, but what gives you confidence that those large three deals will sort of come through in the back half? Any color there would be appreciated. Thanks.

John Cotterell: So the three deals are signed. So they are committed spend that involves ramp up in the second half. I'll let Mark give you a little more color. They are. And it's not just those three deals, they're additive.

Mark Thurston: So we've signed deals going back to Q1, sorry when we were guiding Q1 at the end of the year. So there was a further sort of layering on of, I'll call it step change revenue because that's typically the nature of it. And that layering on of these larger deals onto the run rate, which we'll refer to the non-strategic deal revenue stream, gives confidence in that back half. I mean, there is still a pipeline, you know, to convert. As we sort of highlighted when we were discussing the Q1 performance.

So there is always sort of risk in the figure, but we have given a range of £752 million to £735 million which we think accommodates that risk in terms of the pipeline conversion on the non-strategic big deals.

Antonio Jaramillo: Got it. That's helpful.

Antonio Jaramillo: And then as a follow-up, I wanted to ask on your capital allocation priorities. Like how are you balancing investment within AI and also share buybacks? Just to get a sense of that as well.

Mark Thurston: The share buyback continues. We still have $150 million approval from the board. We continue to invest. I mean, part of this year, we highlighted there was going to be margin impact through the investment in this shift mainly in terms of technology and onboarding people. And that still remains the case. As John said, we are pushing very fast on this. And sacrificing near-term profitability for the upswing in profitability that we think will come through in at the outer years.

Antonio Jaramillo: Great. Thank you guys so much.

Operator: The next question comes from Jonathan Lee with Guggenheim Partners. Please go ahead.

Jonathan Lee: Great. Thanks for taking my questions. Can you help decompose what's contemplated in your outlook across the high and low end of the range as it relates to pipeline conversion required and the levels go get required and whether you've given any sort of allowance for macro uncertainty?

Mark Thurston: Well, in terms of the range for the full year, if this is excluding obviously any strategic deal pipeline, which is growing strongly, 79% to 81%. In the current quarter, it is very high, it's about 95% to 93%. So we think the quarter for Q2 adequately is ranged. It does take into account that the quarter ending December, we have a lower number of working days, which is a headwind. Against the sort of revenue when you look at it sort of sequentially. But we have strong confidence in Q2.

So Q3 and Q4 where we have the higher levels of pipeline, we have done a sanitization of the pipelines being proposed in the business, and we believe that those are achievable. And as I said, we have reduced the overall guide to take account of that.

Jonathan Lee: Thanks for that color. And as you think about some of the margin challenges you're facing, how are you thinking about the potential for expansion levers and investments into the end of the calendar year and into the start of 2026?

Mark Thurston: Well, I think as you've probably seen, Endava has high operational leverage, which is a sort of a negative and positive. So we're very much driven by top-line performance and reacting accordingly. You know, and visibility has to be good for us to react in sort of time. So if we have slow revenue progress, we have to take out costs, you know, as we respond to that. But similarly, with increasing revenue, we get a strong profitability, you know, recovery, which is what is implied in the full-year guide. That we get on that growth trajectory. And yes, there are some strong sequential growth quarter on quarter. Implied by those larger deals starting to deliver revenue.

But it does give us high operational leverage, which moves up our gross margin quite significantly and delivers strong EBITA performance.

John Cotterell: Anything that I'd add to that is if you look at that strategic pivot that we're talking about going through at the moment, that does have a margin impact. There's a friction element of that change, the change of skills making sure that you know, our people are moving to being AI native and having to take action where people are unable to make that shift. Or carrying skills that become less important. In an AI native world going forward. So that friction element is also hitting the short-term margin picture.

Jonathan Lee: Thanks for that clarity.

John Cotterell: Thanks, Jonathan.

Operator: The next question comes from Phani Kanumuri with HSBC. Please go ahead.

Phani Kanumuri: Thanks, John and Mark for taking my question. My question is on your headcount. There seems to be a bit of increase quarter on quarter. Is this an anticipation for demand in the second half of the year? And then how do you see the headcount strategy in terms of the AI productivity that you're seeing? And the macro headwinds that you're seeing for, let's say, the rest of the fiscal year? Thank you.

John Cotterell: Yes. So a lot of the increase in the headcount seen is the DARVAX Academy that I talked about on the call. Where we're specifically targeting bringing in strong AI native leaders across the organization. As well as bringing in graduates who know, from their university background more AI native, but perhaps less experienced from a coding and governance point of view so that you can create that mix of teams who've got that natural affinity with AI, with prompt engineering and so on. Alongside the experience headcount. And so enabling that shift is part of the friction element. I was talking about for Jonathan.

Where we're investing in the people who move into that space and then getting them placed into client environments. So that's part of that shift up in headcount. We still continue to see us training and bringing in AI native people and losing people who are not going to make that shift into the future. And so you're still seeing an attrition level that's running higher than it has been historically. Because of that churn that's going through the business. And we anticipate that will carry on for another couple of quarters before we settle down into being much more completely in the new world.

Phani Kanumuri: Thank you.

John Cotterell: Thanks, Phani.

Operator: The next question comes from Puneet Jain with JPMorgan. Please go ahead.

Puneet Jain: Hi. Thanks for taking my question. I wanted to follow-up on like the $100 million deal, the one that has 85%, 90% of new work. Can you share like more details like the duration of that revenue or type of work you will do specifically around new development versus managed services? And then why that client and that deal led to like a very different outcome than others like are these type of deals replicable?

John Cotterell: Yeah. So it's a very exciting deal for us. It's a headline of a number of other deals that we're working on that would fall into the same category. The duration is over five years and it's a commitment on the part of the client to spend that level of money with us in return for us driving accelerated transformation for them. It is almost all in the new development space rather than in the managed services space. And there are a number of pillars of transformation, of new product development, and of joint go-to-market exploration of capability. That is built into how we will deliver value back to the client for that spend that they have committed.

It's a very close partnership mindset. Where together we're going to help transform that part of the market. And obviously, it's in the payment space. So we bring a lot of payments experience as well as the AI capabilities and so on that I've been talking about.

Puneet Jain: Got it. And can you also talk about the timing given like the second half guidance for revenue implies give or take £10 million in incremental revenue of quarters in Q3 and Q4. So can ramp in this deal and the large two other large deals alone drive that incremental revenue? In the second half of this year?

Mark Thurston: So incrementally, you know, your math is right around the ten a quarter. It's not quite phased that way, but your maths is roughly right. The deals that we've landed, I've contributing roughly about sort of 50% of that ramp. And the balance is coming from the pipeline conversion on the existing sort of run rate. That is after us look, and that is the non-strategic deals revenue sort of stream, if I can put it that way. So it's coming half and half from the big deals that we have landed but also some of the pipeline conversion in the existing run rate business, if I can call it that.

Puneet Jain: Got it. Thank you.

Mark Thurston: Thanks, Puneet.

Operator: This concludes our question and answer session. I would like to turn the conference back over to John Cotterell for any closing remarks.

John Cotterell: Thank you all for joining us today. In closing, we anticipate a gradual recovery over the balance of the year with being assisted by those large strategic deals that we recently signed or indeed signed back in the summer. Which kick in, in our H2. Our broader partner ecosystem is already generating incremental potential pipeline opportunities. And client interest in Dava Flow is accelerating. So I look forward to speaking with you all on our next earnings call in February. Thank you very much.

Operator: The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.

This article is a transcript of this conference call produced for The Motley Fool. While we strive for our Foolish Best, there may be errors, omissions, or inaccuracies in this transcript. Parts of this article were created using Large Language Models (LLMs) based on The Motley Fool's insights and investing approach. It has been reviewed by our AI quality control systems. Since LLMs cannot (currently) own stocks, it has no positions in any of the stocks mentioned. As with all our articles, The Motley Fool does not assume any responsibility for your use of this content, and we strongly encourage you to do your own research, including listening to the call yourself and reading the company's SEC filings. Please see our Terms and Conditions for additional details, including our Obligatory Capitalized Disclaimers of Liability.

The Motley Fool has positions in and recommends Endava Plc. The Motley Fool has a disclosure policy.