Hiring nowAI product strategy and product management

AI Product Strategist

Also called GenAI Product Strategist

An AI Product Strategist decides which user problems an AI company should solve, and whether current model capability can support a product that works and pays for itself. They stop teams building impressive things nobody needs.

What they do

They study a market and a customer problem, then test whether today's models can solve it reliably enough. They run user interviews, build or commission quick prototypes, and read evaluation results with engineers and researchers. They check the economics: what each use costs to serve, what customers would pay for, and where the product breaks. They write up opportunities, rank them, and say no to weak ones. They work with founders, product managers, engineers and sales to turn the best idea into a clear product thesis with evidence behind it.

What a strong hire delivers

In the first months, a strong hire delivers a ranked set of product opportunities with evidence for each. They produce at least one validated product thesis that states the customer, the problem, the capability needed and the economics. They put a simple way of judging model quality against real user needs in front of the team. Roadmap debates become shorter because the reasoning is written down.

How you can tell they are good

Ask them to walk through an opportunity they assessed and then dropped. Good candidates explain why: capability limits, weak demand or poor margins. Ask them to show an evaluation result and say what decision it changed. Listen for specifics about customers, costs and failure cases. Be wary of vague market sizing, or enthusiasm for what a model might do next.

Why it is hard to fill

The title is new and used loosely. Some companies mean product manager, others mean market analyst or research lead. The real skill sits across customer insight, model behaviour and unit economics, and few people have all three. Most have grown from one side and learned the others on the job. Candidates with a strong CV in one area often turn out thin in another, so screening needs care.

Where to find them

Look at product managers who have shipped features built on language models, and applied researchers who moved towards customer work. Technical business analysts and strategy leads in AI start-ups are another source, as are consultants who have advised on AI adoption. Many sit in product teams at model providers, AI-native software companies and larger firms building internal AI products.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Product Strategist

  1. Tell me about an AI product opportunity you assessed. What did you recommend, and what evidence did you use?

    A strong answer names the customer, the problem and the evidence, such as interviews, prototype results and cost estimates. It shows a clear recommendation. Worry if the answer rests on market reports, opinion or excitement about the technology.

  2. Describe an idea you killed because the model could not do the job reliably. How did you know?

    Look for a concrete test, such as an evaluation set or prototype trial, and a clear threshold for good enough. They should explain how they told the team. Worry if they cannot describe how failure was measured.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We build AI products and need someone to decide which problems we should solve next. You will test ideas against what our models can do and what customers will pay for, and turn the best into clear product theses. You will work closely with founders, engineers and researchers.

What you will do

  • Identify and rank product opportunities based on customer need and model capability
  • Run user research and customer interviews to understand real problems
  • Build or commission prototypes to test ideas quickly
  • Work with engineers to read evaluation results and set quality thresholds
  • Model costs, pricing and margins for proposed products
  • Write opportunity analyses and product theses that support clear decisions
  • Recommend what to stop as well as what to start

What you will bring

  • Evidence of assessing or shipping AI-based products, with outcomes you can describe
  • Experience running user research and turning it into decisions
  • Ability to read model evaluation results and explain what they mean
  • Commercial and financial analysis skills, including cost to serve
  • Clear written analysis that others have acted on
  • Comfort working with technical teams on uncertain problems

Nice to have

  • Experience in applied research or technical analysis
  • Familiarity with product analytics and evaluation dashboards
  • Experience with agent-based products

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Product managementAdvancedChoose problems and manage product outcomes
  • Model evaluationAdvancedMeasure capability and failure modes credibly
  • Commercial and financial analysisWorkingAssess unit economics and value realisation
  • User researchWorkingStudy user needs, context and behaviour

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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