Endava’s AI-Driven Approach
Endava, a global technology services company with over 25 years of experience and a workforce of approximately 11,000, is transforming its software delivery process by integrating AI agents and implementing an AI-native methodology known as DavaFlow. The company has chosen OpenAI as its enterprise AI platform, providing employees access to ChatGPT Enterprise and Codex to incorporate AI into their daily workflows.
From Developer Experiments to DavaFlow
Initial experiments with AI-assisted coding and agentic workflows revealed new bottlenecks beyond engineering, highlighting the need for faster requirements gathering, business analysis, planning, and stakeholder coordination. This realization led to the development of DavaFlow, which embeds OpenAI technology throughout the entire delivery lifecycle, including meeting preparation, business planning, product discovery, software engineering, and deployment.
Integration of AI Across Teams
As AI agents became integral to daily operations, their use extended beyond development teams. Legal teams began utilizing AI for research and documentation, while project managers leveraged Codex to generate governance reports and summarize engineering progress. Commercial teams transitioned from spreadsheet-heavy planning to lightweight, AI-generated applications. For instance, during an internal pricing discussion, teams created a single-page pricing app instead of relying on traditional spreadsheets, significantly altering the nature of the conversation.
Outcomes and Lessons Learned
Endava has reported several key outcomes from its AI rollout, including:
- Accelerated software delivery through the integration of AI agents into engineering workflows.
- Expanded AI adoption across legal, finance, and operations teams.
- Reduced manual reporting and coordination tasks through AI-assisted workflows.
- Empowered teams to develop internal tools and applications without the need for dedicated engineering support.
- Established AI fluency as a requirement in hiring and promotion processes.
Key Principles for AI Adoption
Throughout the scaling process, several principles emerged regarding AI adoption:
- Treat AI adoption as a behavioral change rather than merely a software rollout.
- Encourage leaders to actively use AI to model and drive organization-wide adoption.
- Create opportunities for experimentation, even when outcomes may not be perfect.
- Involve non-technical teams early in the process to foster collaboration.
- Prioritize hands-on experience to help overcome skepticism about AI.
Future Directions
Looking ahead, Endava plans to focus on orchestration, which involves combining models, agents, workflows, and human expertise into integrated systems that fundamentally reshape organizational operations. Cloke expressed enthusiasm for the potential workflows that can be created by blending reasoning models and Codex agents with automation and enterprise-scale collaboration. As a practical application, the company utilizes ChatGPT Enterprise and Codex throughout its DavaFlow lifecycle, effectively leveraging these tools across its global workforce.
Original source: OpenAI News