You invested in AI. Why aren’t you seeing bigger returns?
AI sped up the doing, not the delivery.
Where the returns went
Writing the code and drafting the work got faster. Getting work ready to build, and deciding whether what came back is right, didn’t, and that’s where work waits now. Your teams pull whatever’s ready, which is usually the small stuff like bugs and fixes. So they finish more small things and look busier than ever, while delivery of the strategic work leadership is paying for hasn’t moved.
- Teams finish more small work, and the big initiatives haven’t moved.
- Work piles up waiting on reviews, approvals, and decisions.
- Teams are busy all the time, and nobody can say when the strategic work will land.
- You can’t show what AI is returning, or whether it’s returning anything.
What we found with a client
We spent six months with a client rebuilding the way its teams worked, in the same months the AI tools arrived. By the end, the teams were finishing four to five times as many work items a month as in their last normal year, with smaller teams and work of about the same size. We still can’t tell you how much of that was AI, because Kanban, WIP limits, new team boards, and a restructure all landed in the same quarter. What we could show was that something real had changed, and where the work was still waiting.
Read the full story →AI Delivery Diagnostic
Two weeks. Fixed scope. $7,500.
We take an export from your work tracker, whether that’s Jira, Azure DevOps, or something else, and talk with the people doing the work. Then we show you:
- Whether your delivery actually changed since AI arrived
- Where work waits between “someone asked for it” and “it’s done”
- Whether your delivery is stable enough for a forecast to mean anything
- How much of your capacity goes to strategic work, and how much to the small stuff
- What it would take to fix, in the order we’d do it
You get a findings document and a readout with your leadership team. If the findings say we’re not the right fix, we’ll tell you.