Effective Work Sample Exercises for Hiring Top AI Product Managers

In the rapidly evolving field of artificial intelligence, finding the right AI Product Manager can make the difference between a successful product launch and a costly misstep. AI Product Managers sit at the critical intersection of business strategy, user needs, and cutting-edge technology, requiring a unique blend of technical understanding, strategic vision, and cross-functional leadership.

Traditional interviews often fail to reveal a candidate's true capabilities in these areas. While resumes and behavioral questions provide some insights, they rarely demonstrate how candidates will perform in real-world scenarios that demand quick thinking, practical problem-solving, and effective communication across technical and non-technical teams.

Work samples offer a window into how candidates approach actual challenges they'll face on the job. For AI Product Managers specifically, these exercises can reveal their ability to translate complex technical concepts into user value, prioritize features in an uncertain landscape, and communicate effectively with diverse stakeholders—from data scientists to business executives.

The following work samples are designed to evaluate the essential competencies of successful AI Product Managers: strategic thinking, cross-functional collaboration, technical understanding, and customer-centricity. By incorporating these exercises into your hiring process, you'll gain deeper insights into each candidate's capabilities and identify those truly prepared to lead your AI product initiatives.

Activity #1: AI Feature Prioritization Exercise

This exercise evaluates a candidate's ability to make strategic decisions about product features based on competing factors like user needs, technical feasibility, and business impact—a core responsibility for any AI Product Manager. It reveals how candidates think about trade-offs and how they justify their decisions to stakeholders.

Directions for the Company:

• Prepare a fictional AI product scenario with 8-10 potential features to be prioritized. Include a brief product description, target users, and business objectives.
• For each feature, provide a short description, estimated development effort (high/medium/low), potential user impact, and any technical dependencies or limitations.
• Allow candidates 30 minutes to review the materials and prepare their prioritization.
• Schedule a 45-minute session: 20 minutes for the candidate to present their prioritization and 25 minutes for questions and feedback.
• Prepare challenging questions about their prioritization decisions to test their reasoning.

Directions for the Candidate:

• Review the AI product scenario and feature list provided.
• Create a prioritized roadmap for the next two quarters, selecting which features to build first and which to defer.
• Prepare to explain your prioritization methodology and the reasoning behind your decisions.
• Be ready to discuss how you would communicate this prioritization to engineering teams and business stakeholders.
• Consider potential technical challenges in implementing AI features and how these influenced your decisions.

Feedback Mechanism:

• After the presentation, provide specific feedback on one aspect of their prioritization approach that was particularly strong.
• Then offer one suggestion for improvement, such as considering additional factors in their decision-making or strengthening their justification for certain choices.
• Give the candidate 5-10 minutes to revise their prioritization based on this feedback, focusing on how they incorporate the new perspective.

Activity #2: Cross-Functional Communication Role Play

This exercise tests a candidate's ability to translate complex AI concepts for different audiences and navigate the challenges of cross-functional collaboration—essential skills for bridging the gap between technical teams and business stakeholders.

Directions for the Company:

• Create a scenario involving a technical AI challenge that needs to be explained to different stakeholders.
• Prepare role descriptions for three different stakeholders: a data scientist, a marketing executive, and a customer success manager.
• Assign three interviewers to play these roles, each with different concerns and questions about the AI product.
• Provide the candidate with a technical brief about the AI feature or challenge 24 hours before the exercise.
• Schedule a 45-minute session with 15 minutes per stakeholder conversation.

Directions for the Candidate:

• Review the technical brief about the AI feature or challenge.
• Prepare to explain this feature/challenge to three different stakeholders with varying technical backgrounds.
• For each stakeholder, you'll need to:
• Explain the feature/challenge in terms relevant to their role
• Address their specific concerns
• Answer their questions
• Gain their buy-in or support
• Adapt your communication style and technical depth appropriately for each audience.

Feedback Mechanism:

• After each stakeholder conversation, the interviewer should provide brief feedback on the candidate's communication effectiveness.
• After all three conversations, identify one communication approach that worked well across stakeholders.
• Then suggest one improvement in how technical concepts were translated for non-technical audiences.
• Give the candidate 5 minutes to re-explain a key concept to the marketing executive, incorporating the feedback.

Activity #3: AI Product Roadmap Planning

This exercise evaluates a candidate's strategic thinking and ability to develop a coherent product vision and roadmap for an AI product. It tests their understanding of AI technology trends, market dynamics, and how to sequence product development to deliver value incrementally.

Directions for the Company:

• Create a brief for a new AI product opportunity, including:
• Market context and competitive landscape
• Available data assets and AI capabilities
• Business objectives and constraints
• User research highlights
• Provide this brief to candidates 48 hours before the exercise.
• Schedule a 60-minute session: 30 minutes for presentation and 30 minutes for questions and discussion.
• Prepare questions that challenge assumptions and test how the candidate handles uncertainty.

Directions for the Candidate:

• Review the AI product opportunity brief provided.
• Develop a 12-month product roadmap that outlines:
• The product vision and key value propositions
• Major milestones and releases
• Key features and capabilities to be developed
• Success metrics for each phase
• Potential risks and mitigation strategies
• Prepare a presentation (10-12 slides) explaining your roadmap and strategic rationale.
• Be prepared to discuss how you would adapt the roadmap if certain AI capabilities prove more challenging than anticipated.

Feedback Mechanism:

• After the presentation, highlight one particularly strong aspect of the candidate's strategic thinking or roadmap planning.
• Then suggest one area where the roadmap could be strengthened, such as addressing technical risks earlier or providing more clarity on success metrics.
• Give the candidate 10 minutes to revise one section of their roadmap based on this feedback, explaining their adjustments.

Activity #4: AI User Problem Analysis and Solution Design

This exercise assesses a candidate's customer-centricity and problem-solving skills by challenging them to identify user needs and design AI-powered solutions. It reveals how candidates think about applying AI capabilities to solve real problems rather than just implementing technology for its own sake.

Directions for the Company:

• Prepare a user research summary for a specific domain (e.g., healthcare, finance, retail) with 3-4 key user problems or pain points.
• Include relevant user quotes, behavioral observations, and contextual information.
• Provide information about available data sources and AI capabilities that could potentially be leveraged.
• Schedule a 60-minute session: 15 minutes for review, 25 minutes for solution design, and 20 minutes for presentation and questions.

Directions for the Candidate:

• Review the user research summary and available data/AI capabilities.
• Select one key user problem to focus on.
• Design an AI-powered solution that addresses this problem, including:
• The core user experience and value proposition
• Required data inputs and AI capabilities
• How the solution would evolve as more data becomes available
• Potential limitations or ethical considerations
• Sketch your solution (can be low-fidelity wireframes or a simple flow diagram).
• Prepare to explain how your solution addresses the user need and why you chose this approach over alternatives.

Feedback Mechanism:

• After the presentation, highlight one aspect of the candidate's solution that effectively leverages AI to address the user need.
• Then suggest one way the solution could better address user context or constraints.
• Give the candidate 10 minutes to refine their solution based on this feedback, focusing on how they incorporate the user-centered improvement.

Frequently Asked Questions

Q: How should we evaluate candidates who have strong strategic skills but limited technical AI knowledge?
A: Focus on their ability to ask good questions about technical feasibility and their willingness to learn. Strong product managers can develop technical knowledge, but strategic thinking and collaboration skills are harder to teach. Consider pairing them with a technically strong team if their other skills are exceptional.

Q: Should we expect candidates to create polished presentations for these exercises?
A: No, the focus should be on substance rather than style. Clear thinking and communication are more important than perfect slides. Let candidates know that rough sketches and bullet points are acceptable as long as their ideas are clearly conveyed.

Q: How do we ensure these exercises don't take too much of the candidate's time?
A: Be respectful of candidates' time by clearly communicating expectations and time commitments upfront. For take-home components, limit preparation time to 1-2 hours. Consider offering flexibility in scheduling and be transparent about the entire interview process.

Q: How should we adapt these exercises for candidates with different levels of experience?
A: For more junior candidates, provide additional context and simplify the scenarios. For senior candidates, include more strategic complexity and ambiguity. Adjust your evaluation criteria based on the expected level of expertise for the role.

Q: What if a candidate's approach is completely different from what we expected?
A: This can actually be valuable! Evaluate the reasoning behind their approach rather than whether it matches your preconceived solution. Strong candidates may bring fresh perspectives that challenge your assumptions. Focus on whether their approach is logical, addresses the core problems, and demonstrates the key competencies you're assessing.

Q: How do we ensure these exercises don't introduce bias into our hiring process?
A: Create clear evaluation criteria based on the competencies required for the role before reviewing any candidate submissions. Have multiple evaluators assess each candidate independently before discussing. Be mindful of how cultural references or assumed knowledge might disadvantage certain candidates.

Finding the right AI Product Manager requires going beyond traditional interviews to see candidates in action. These work samples will help you identify individuals who can truly bridge the gap between AI technology and business value. By incorporating these exercises into your hiring process, you'll gain deeper insights into each candidate's capabilities and make more informed hiring decisions.

Ready to take your AI Product Manager hiring process to the next level? Visit our resources at AI Job Descriptions, AI Interview Question Generator, and AI Interview Guide Generator to create comprehensive hiring materials. Check out the full job description for this role at AI Product Manager Job Description.

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