Why AI-assisted programme assurance must govern provenance, omissions and reviewer challenge
Why funding should follow demonstrated results rather than approve promised scope once
What happens when AI removes the work that taught us how to lead programmes
What programme professionals must learn when fluent output becomes cheap and trustworthy action remains hard
The evidence for governing hand-offs, state, authority and recovery across enterprise agent workflows
Why enterprise agent systems need decision contracts, not just specialised roles
What generative AI reveals about programme work, professional learning and the limits of tool-led change
The honest delivery lesson from early generative AI programmes: safeguards that are not planned, funded and tested will not survive contact with the deadline
Behind the crowded idea lists, isolated pilots and the unresolved argument between central ambition and local adoption
What 2021 revealed from inside the programme: a new plan cannot rescue an unchanged system of authority
How boards built to choose became bodies that merely receive — and the decision deficit that follows
A step-by-step method for turning a closed programme into decisions the next one will actually use.
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