Endava (DAVA) Morgan Stanley Technology, Media & Telecom Conference 2026 summary

Strategic focus and client engagement

• Emphasis on engaging C-suite executives to align solutions with client business objectives, particularly leveraging AI to drive efficiency and competitive advantage.

• Shift toward outcome-based contracts and the introduction of an AI-native delivery approach called Endava Flow, which is resonating with clients and generating a strong pipeline.

• Recent wins, such as with Paysafe and Nexus, highlight traction in the payments sector and broader financial services.

• Stabilization and contract extensions achieved with the largest clients, with new opportunities emerging from their ongoing business transformations.

• Geographic strength noted in the UK, North America, and Asia, with sectoral momentum in payments, banking, capital markets, and insurance.

AI initiatives and operational transformation

• Endava Flow is a tool-agnostic, agentic AI delivery methodology designed to address enterprise needs, focusing on upfront architectural planning and outcome-based execution.

• AI investments are tracked through KPIs such as revenue growth, margin improvement, win rates, and longevity of client partnerships.

• Internal efficiency gains realized in legal, finance, and sales, with a shift to higher-quality C-suite engagement salespeople.

• The methodology enables significant productivity improvements, unlocking previously unviable legacy system projects and allowing clients to achieve more with existing budgets.

• Endava Flow's flexibility allows clients to integrate any AI tool, reducing risk from technology shifts and supporting long-term partnerships.

Financial outlook and investment impact

• Q4 guidance anticipates an 8% quarter-on-quarter uplift, with 70-75% of revenue underpinned by contracted and committed deals.

• Margin pressure is attributed to intentional investment in AI capabilities and staff, with a 3% impact expected to abate as groundwork is completed by fiscal 2027.

• The business model aims to blend traditional and AI-enabled services, targeting a margin recovery to 20-30% as the mix shifts over time.

• Long-term contracts and outcome-based pricing are expected to drive operational leverage and improved unit economics.

• The company positions itself as having already navigated the trough of disillusionment in AI adoption, now entering a phase of scaling and margin improvement.