A Point of View for CIOs and Enterprise Technology Leaders
One SDLC stage runs at machine speed. The other six did not change.
AI coding tools work. 93% of development professionals now use AI; agentic adoption in coding has reached 84% to 90%, and in committed organizations, AI writes or assists with around half the code. At the keyboard, the problem is solved.
The rest of the software development life cycle did not keep pace. Testing sits at 55% to 64% adoption. Deployment and release sit at 13% to 22%. Requirements and architecture, the two stages that decide whether generated code fits the system at all, are barely used in industry. Only about 13% of teams have AI operating across the full life cycle.
This Point of View shows where that imbalance costs money, and what an enterprise has to put in place to close it.
What’s Inside
- The maturity gap across the SDLC Where AI has actually been adopted stage by stage, and why the two least automated stages are the ones that decide whether generated code works.
- What the tools genuinely deliver The problems AI coding tools have solved, the conditions under which the gains are largest, and what the leaders did differently.
- Where the gains stop Why output rises while delivery does not, including the downstream cost in bugs, incidents, review time, and technical debt.
- Five places the money leaks Requirements and architecture, review, testing, integration, and release and adoption. What goes wrong at each stage and why.
- What closes each gap A direct view of the controls that work, from written architecture before generation to mutation testing and funded review capacity.
- The way forward How agentic engineering remodels the life cycle, with clear ownership from requirements through to business sign-off and go-live.
Why This Matters
The next performance gap will not separate organizations that adopted AI coding tools from those that did not. Almost everyone has adopted them. It will separate organizations that redesigned the life cycle around those tools from those that bought the tool and changed nothing else.
The evidence is already visible. Only a quarter of companies report meaningful acceleration of their product development life cycle. Productivity actually fell in around 30% of companies after adopting agentic coding tools. Organizations that redesigned their processes before adopting the technology were more than twice as likely to report productivity gains above 20%.
Download the Point of View to see where your delivery gains are leaking, and the operating changes that convert faster coding into software that ships on plan, holds up in production, and gets used.
Ready to close the gap between code and delivery?
Talk to us about building agentic engineering capability inside your delivery teams.
