Strategy question

How would you monetize ChatGPT?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Business strategy and monetization thinking for a consumer AI product with a large free user base and high inference costs.

Clarify whether the question is about ChatGPT specifically (already has Plus, Team, Enterprise, API) or a hypothetical from-scratch product.
Segment users by usage intensity and willingness to pay, such as casual askers, power users, developers, and businesses.
List monetization levers: subscription tiers, usage-based API pricing, enterprise seats, and ads or sponsored answers as a lower-trust option.
Weigh each lever against OpenAI's actual cost structure, since heavy users cost more in inference than they pay in a flat subscription.
Recommend a primary lever, for example expanding usage-based caps and enterprise seats rather than ads, to protect trust in answers.
Note the trade-off: ads risk perceived bias in answers, which threatens the core value proposition.

Recognizes that ChatGPT's costs scale with usage, so flat-fee subscriptions need usage caps or tiered limits to stay profitable.
Proposes enterprise and API revenue as the larger long-term lever versus consumer subscriptions alone.
Considers a freemium funnel: free tier drives adoption, Plus/Pro convert power users, API and Enterprise capture business value.
Flags that ads would need to be clearly separated from AI-generated answers to preserve trust.
Gives an illustrative assumption, such as estimating only a small single-digit percent of free users convert to paid, and reasons from there.

Jumping straight to ads without discussing the trust cost for an answer-engine product.
Ignoring that inference cost varies wildly by query complexity, making flat pricing risky.

Chapters of the AI PM course that teach what this question tests.