AI governance
Narrative: AI governance is high-value, but decision latency is the main tax on scaling it cleanly.
Friction score: 71
Reduce approval depth for recurring policy patterns and assign one final owner per packet.
Operating Model Friction Index turns handoff complexity, tooling fragmentation, decision latency, and ownership ambiguity into one reusable board-facing friction surface.
Reduce approval hops in AI governance, standardize procurement proof reuse, tighten biotech handoffs, contain FinTech change blast radius, clarify nonprofit owners, and consolidate the robotics operator stack before these friction taxes grow further.
Narrative: AI governance is high-value, but decision latency is the main tax on scaling it cleanly.
Friction score: 71
Reduce approval depth for recurring policy patterns and assign one final owner per packet.
Narrative: Procurement is scalable, but evidence overhead is the main source of wasted effort.
Friction score: 66
Define one canonical answer-and-proof bundle so commercial teams stop rebuilding the same trust material.
Narrative: Biotech is credible, though its scaling drag lives in multi-owner handoff complexity.
Friction score: 74
Create a thinner QA-to-release closure path with one owner and one summarized evidence packet.
Narrative: FinTech has strong pull, though change friction keeps weakening execution reliability.
Friction score: 78
Isolate change surfaces and shrink the retest burden each control update creates.
The pressure map keeps remediation score, friction score, and recoverable margin visible in the same board-readable view.