Ciaran Hale shares how Deputy moved from fragmented AI experiments to a centralised AI and data foundation on AWS. By standardising infrastructure, introducing governance guardrails, and building reusable components, Deputy enabled teams to scale AI with confidence. This shift also transformed internal adoptionembedding AI into everyday workflowsand unlocked new customer value through Deputy AI, delivering smarter automation and insights in-product. A practical blueprint for building an AI-native organisation.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Going from "scattered AI experiments" to "AI-native operating model" requires a centralised platform team, not just decentralised exploration. Standards, governance guardrails, reusable components.
Why it matters
Without standards, every team builds its own broken stack. You end up with five vector DBs, three orchestration frameworks, and zero shared evals.
The hard parts
Platform teams without enforcement get ignored. Platform teams with enforcement become bottlenecks. Both fail.
Playbook moves
(1) Make the golden path so easy that paving your own is the harder option. Reusable components beat policy memos. (2) Embed platform engineers in product teams for the first quarter. (3) Measure platform adoption as the team's KPI.
The surprise
"AI-native" is mistakenly framed as a tech change. It's actually a *procurement* change. Your buying decisions need to weight "agent-friendly APIs" and "structured outputs" as first-class criteria. Half the AI roadblocks come from vendors whose APIs aren't built for this.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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