Endava (DAVA) TD Cowen's 54th Annual Technology, Media & Telecom Conference summary

Market and demand trends

• Demand has been volatile, with a recent top-line miss, but AI-related demand is firming and moving from proof of concept to production in client conversations.

• Middle East conflict caused direct revenue impact and broader uncertainty, especially in banking and capital markets across North America and the UK.

• Legacy digital transformation work remains but is under pressure as clients shift focus to AI-driven projects; volume, not pricing, is the main issue.

• Clients are not cutting budgets but are moving slowly, with project work ending and new initiatives taking longer to close.

• Procurement and client readiness are key hurdles in transitioning to new commercial models and AI adoption.

Business model evolution and deal structure

• Transitioning from time-and-materials to outcome-based and fixed-price contracts, aiming for longer-term, larger engagements for better visibility and margins.

• AI-native revenues now represent 15% of total, with major deals like Paysafe delivered through the Dava.Flow methodology.

• Larger deals are now targeted from the outset, requiring higher-level, outcome-focused pitches and deeper industry knowledge.

• Pipeline for large deals is strong but conversion is slow due to complex negotiations and client processes.

• More granular pipeline management and mature management involvement are being implemented to improve forecasting and minimize surprises.

AI strategy and Dava.Flow methodology

• Dava.Flow is a flexible, agent-based methodology for AI delivery, emphasizing rapid ideation, backlog creation, and governance, rather than a fixed platform.

• Adoption is growing, with client engagements increasing from 3 to 12 in two quarters, but broader rollout depends on internal training and client readiness.

• Dava.Flow enables faster, outcome-based delivery and higher margins, especially in payments, with potential for expansion to other sectors.

• Revenue from Dava.Flow projects can be lumpy but is expected to be steadier and more profitable than traditional models, with some contracts including revenue share.

• The approach is differentiated by deep domain expertise, tool-agnostic flexibility, and strong partnerships, notably with OpenAI.