AI features can spread quickly. A capability that feels differentiated today may become a standard model feature tomorrow. Pricing power helps reveal whether a startup owns durable customer value or is temporarily packaging scarce technology.

Start with the customer outcome

Products tied to measurable revenue, labor savings, risk reduction or workflow speed have a clearer basis for pricing than products sold only on novelty.

Test willingness to absorb price changes

Discount-heavy growth can hide weak pricing power. Review renewals, expansion and customer behavior when promotional pricing ends.

Look at alternatives

If customers can recreate the product with a generic model and minimal integration, the startup may face rapid price compression. Workflow depth, proprietary data and distribution can make substitution harder.

Switching costs should be healthy

Integrations, accumulated configuration and team workflows can create legitimate switching costs. Artificial data lock-in may protect revenue temporarily but can damage trust.

Gross margin sets a floor

Pricing power must cover variable inference and support costs. Rapid usage growth is less attractive if every additional dollar carries nearly equivalent serving expense.

Segment by customer value

Enterprise buyers may pay for governance, security and integration that individual users do not value. Pricing power can therefore vary sharply by segment.

Combine this analysis with AI startup revenue quality to understand whether the monetization model reinforces durable value.

The strongest pricing power comes from becoming difficult to replace because the product reliably solves an important problem—not because access to a particular model is temporarily scarce.