Ivan Heredia, Andrew Briscoe, Geraint Jones and Mordecai
Tool adoption often becomes aimless experimentation. The discipline is matching each tool to a specific job — research-and-reference platforms versus generative creative assistants — and reverse-engineering from the outcome you want.
The workforce is becoming expert in a technology before leadership is. Governance is playing catch-up, so the move is to lean in while still reverse-engineering from real KPIs and outcomes.
Much corporate AI adoption began as an external, share-price-driven mandate rather than from a customer or business problem — and some organizations are now unwinding that backwards start.
You can rush to build tools that make you faster without making you better. The higher-leverage work is training people and reshaping the governance around how tools get used.
In large, matrixed organizations the constraint is rarely ideas or resources — it's permission. Progress comes from engendering belief through proof points and micro-experiments, not from technology.
Innovation only becomes real when an organisation solves an actual problem and ships something; an idea on its own doesn't count.
