Endava AI Integration: Redesigning Software Delivery with OpenAI Agents

Endava has redesigned its software delivery and organizational operations by embedding OpenAI technology and AI agents across its entire workforce. This transformation shifts AI from a supplementary productivity tool to the primary operating model for the company's software delivery lifecycle.

AI-Native Software Delivery via DavaFlow

Endava has integrated OpenAI technology into every stage of its proprietary DavaFlow lifecycle. This integration ensures that AI is the first consideration in problem-solving rather than an afterthought.

While initial adoption focused on AI-assisted coding and agentic workflows for developers, Endava identified that engineering output was no longer the primary bottleneck. Consequently, the company expanded AI usage to accelerate requirements gathering, business analysis, planning, and stakeholder coordination.

Cross-Functional AI Adoption

AI adoption at Endava extends beyond engineering teams to encompass legal, finance, and operations. The company utilizes ChatGPT Enterprise and Codex to automate non-technical workflows:

• Legal Teams: Streamlining research and documentation workflows.
• Project Managers: Using Codex to generate governance reports and summarize engineering progress.
• Commercial Teams: Replacing spreadsheet-heavy planning with lightweight, AI-generated applications, such as interactive pricing apps.
• Leadership: Utilizing agents to summarize projects, automate communications, and manage inboxes asynchronously.

Organizational Impact and Results

By treating AI adoption as a behavioral change rather than a software rollout, Endava has achieved several key operational outcomes:

• Accelerated Delivery: Software delivery speed has increased through the integration of AI agents into engineering workflows.
• Reduced Overhead: Manual reporting and coordination tasks have been reduced via AI-assisted workflows.
• Democratized Tooling: Teams can now build internal applications and tools without requiring dedicated engineering support.
• Cultural Shift: AI fluency is now a formal expectation for hiring and promotion across the organization.

Strategic Principles for Enterprise AI Rollout

Based on the rollout across its 11,000-person global workforce, Endava identifies several core principles for successful AI integration:

• Behavioral Focus: AI adoption must be treated as a change in behavior, not merely a software deployment.
• Leadership Engagement: Leaders must actively use AI to drive organization-wide adoption.
• Experimental Culture: Organizations must create space for experimentation, accepting that initial outcomes may be imperfect.
• Early Inclusion: Non-technical teams should be brought into the AI process early in the transition.
• Direct Experience: Hands-on use is the most effective method for overcoming skepticism.

Future Outlook: Orchestration and Operating Models

Endava views the next phase of enterprise AI as a shift toward orchestration. This involves combining reasoning models, Codex agents, and human expertise into integrated systems. According to CTO Matthew Cloke, AI is evolving from a productivity layer into the operating model itself, where the goal is to combine various tools and agents to reshape how organizations fundamentally operate.