Why AI Alone Won't Fix Software Delivery:
Building a Connected Engineering System for Enterprise Scale
Developer adoption of AI coding tools is nearly universal. Yet for many organizations, the productivity gains remain underwhelming. While AI coding assistants help individual developers complete tasks faster, enterprise delivery metrics often remain unchanged. The reason is simple: the challenge is not tactical, it's systemic. AI tools can accelerate coding, but they don't address the broader delivery constraints that slow software engineering organizations.
Watch Devipad Tripathy, Head of Digital Engineering and Enterprise Transformation at Xebia, in conversation with Akshat Vaid, Partner, Engineering Services and Information Technology at Everest Group, as they discuss why this delivery gap persists and what enterprises can do to bridge it.
- The real reasons AI investments often underdeliver.
- A framework for overcoming fragmented engineering workflows.
- Insights into closing the gap between AI and delivery.
- How connected engineering drives measurable productivity gains.
- The governance model required for enterprise-scale AI.
- A blueprint for operationalizing AI across your SDLC.
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