EconomicsMarkets, platform economics, AI economics
January 30, 2026 · 1 min read
Platform Economics and AI Cost Curves
How to reason about value capture when AI capability grows faster than organizational adaptation.
TL;DR
- Falling technical costs do not automatically create sustainable margins.
- Platform advantage depends on coordination design, not just model access.
- The key strategic question is where control points remain scarce.
Where value moves
When capability becomes easier to access, differentiation shifts toward workflow integration, trust, and distribution channels. The fastest mover is not always the long-term winner.
A structured lens
Layer 1: Capability
What can be produced technically, and at what variable cost?
Layer 2: Coordination
Who integrates tools into repeatable workflows with low failure risk?
Layer 3: Control points
Who controls demand access, switching friction, and decision interfaces?
Risk patterns
- Commoditization risk: capability is abundant, pricing collapses.
- Integration risk: cost savings are offset by operational instability.
- Governance risk: policy or compliance constraints reshape usable markets.
Questions to think about
- Which layer in your stack currently captures most value?
- If model capability doubles, which part of your moat remains intact?
- Are you competing on scarce control points or abundant components?