Failure modes to avoid
The traps that quietly sink AI leads.
Knowing the anti-patterns is half the battle. These are the ways the role most often goes wrong.
Key ideas
- 1
Becoming the bottleneck — if every AI feature needs you, you've failed. Multiply through champions and paved roads.
- 2
Hype without substance — demos with no evals get found out. Always attach a number and a way to verify quality.
- 3
Ignoring governance until it bites — one PII-in-a-prompt incident can set the whole program back. Guardrails first.
- 4
Going non-technical too fast, or becoming the “AI police” who only says no (teams then route around you via shadow AI).
- 5
Boiling the ocean, selling with vanity metrics, and ignoring the human/fear dimension.
The big traps
- Bottleneck: centralizing all building instead of enabling teams.
- Hype: evangelizing without evals; you lose credibility when it breaks.
- Governance-last: in a regulated insurer, a data leak sets you back months.
- Losing your technical edge: standards stop landing when you can't build.
- AI police: only saying no drives shadow AI; be the easy yes path.
- Ocean-boiling: trying to transform every BU at once instead of sequencing.
- Vanity metrics & ignored fear: erode trust and create blockers.
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