How Endava is redesigning software delivery around AI agents

Here's the thing: relying on AI agents for software delivery isn't a silver bullet. While Endava claims to accelerate processes using ChatGPT Enterprise and Codex, the reality is that many teams struggle with the foundational data quality before diving into AI. If you're considering this approach, be wary of the complexity it introduces. AI agents can automate workflows, but they also require robust infrastructure and a culture that embraces change. Without these in place, you're setting yourself up for disappointment.

What they're not saying is that the effectiveness of these AI agents in actual delivery environments remains largely unverified. It's easy to throw terms like 'AI-native culture' around, but the real question is: how well do these tools integrate with existing workflows? Competing solutions like Jira or ServiceNow have established themselves with proven track records. If you’re already using those platforms, the allure of a shiny new tool may not outweigh the risks of disruption.

The catch here is that while automation can reduce manual effort, it won't solve the underlying issues of inefficiency or misalignment in teams. If your organization is not ready to adapt its culture and processes, then no amount of AI will streamline your delivery. Endava's approach might appeal to forward-thinking teams eager for transformation, but it may leave others stranded in the hype.

If you're part of a team that prioritizes operational readiness and has a clear strategy for integrating AI, then this could be worth exploring. However, for those still wrestling with data governance and quality, it’s wise to hold off and ensure your foundation is solid before building these new capabilities on top. Test this offering only if you can back it up with the required infrastructure and culture to support it.