His sequence: start with the business outcome or constraint rather than an AI use case; map the current workflow, including handoffs, exceptions, required data, where context drops, and which meetings exist only because information or decisions are locked up; redesign by deciding what to remove, automate or augment; deploy with change management and measurement; then run a learning loop of user feedback and tweaks before scaling. He compares this to deploying a product.

“AI is not something that you add into an existing process because then all you're typically doing is you're just adding one extra step or one extra layer, but you're not really solving the business outcome or the root problem.”

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