Effective Work Samples for Evaluating AI Change Management Strategy Skills

AI implementation represents one of the most significant organizational transformations many companies will undertake in the coming years. Unlike traditional technology implementations, AI introduces unique challenges: it often fundamentally changes how work is performed, raises complex ethical questions, and can trigger heightened anxiety among employees concerned about job displacement. This makes skilled AI change management strategists invaluable assets to organizations navigating this transition.

Evaluating a candidate's ability to develop effective AI change management strategies requires more than reviewing past experience or conducting standard interviews. The complexity of AI implementations demands practical demonstration of a candidate's approach to managing the human side of technological change. Work samples provide a window into how candidates analyze stakeholder concerns, develop communication strategies, address resistance, and create adoption plans specifically tailored to AI initiatives.

The best AI change management strategists combine technical understanding of AI capabilities with deep empathy for how these technologies impact people. They recognize that successful AI implementation is only partly about the technology itself—the greater challenge lies in preparing the organization culturally and operationally for transformation. Through carefully designed work samples, you can assess a candidate's ability to bridge this technical-human divide.

The following exercises are designed to evaluate a candidate's approach to key aspects of AI change management strategy development. Each activity simulates real challenges faced during AI implementations and provides opportunities to observe how candidates think through complex organizational dynamics. By incorporating these work samples into your hiring process, you'll gain valuable insights into which candidates possess the strategic thinking, communication skills, and change management expertise needed to guide your organization through successful AI transformation.

Activity #1: AI Impact Assessment and Stakeholder Analysis

This exercise evaluates a candidate's ability to analyze how AI implementation will affect different stakeholders within an organization and identify potential sources of resistance or support. Successful AI change management begins with a thorough understanding of organizational dynamics and the varying perspectives different stakeholders bring to technological change.

Directions for the Company:

• Provide the candidate with a detailed scenario of an AI implementation project your organization is considering or has implemented (e.g., implementing an AI-powered customer service chatbot, predictive maintenance system, or automated underwriting tool).
• Include information about the organization's structure, key departments, and current processes that would be affected.
• Prepare a template for the candidate to complete that includes sections for stakeholder identification, impact analysis, and prioritization.
• Allow 45-60 minutes for this exercise.
• Have a senior change management or AI implementation leader available to review the assessment.

Directions for the Candidate:

• Review the AI implementation scenario provided.
• Identify all key stakeholder groups that would be affected by this implementation.
• For each stakeholder group, analyze:
• How the AI implementation will impact their daily work
• Potential benefits they might experience
• Potential concerns or sources of resistance
• Their level of influence in the organization
• Their importance to the success of the implementation
• Create a stakeholder prioritization matrix that maps stakeholders based on their influence and impact.
• Recommend 3-5 key stakeholder groups that should receive priority attention in the change management strategy and explain why.

Feedback Mechanism:

• After reviewing the candidate's assessment, provide feedback on the comprehensiveness of their stakeholder identification and the depth of their impact analysis.
• Highlight one stakeholder group the candidate may have overlooked or underestimated.
• Ask the candidate to revise their prioritization matrix based on this feedback and explain how they would adjust their change management approach for this stakeholder group.

Activity #2: AI Resistance Management Strategy

This exercise assesses a candidate's ability to anticipate and address resistance to AI implementation. Resistance is inevitable during AI transformations, and skilled change managers develop proactive strategies to acknowledge concerns while moving the organization forward.

Directions for the Company:

• Create a scenario describing an AI implementation that has encountered significant resistance from a specific department or team.
• Provide details about the nature of the resistance (e.g., fear of job loss, concerns about decision quality, discomfort with new workflows).
• Include quotes or scenarios from resistant employees that illustrate their specific concerns.
• Prepare a template for the resistance management plan.
• Allow 45-60 minutes for this exercise.
• Have a senior change management or AI implementation leader available to review the plan.

Directions for the Candidate:

• Review the resistance scenario provided.
• Analyze the root causes of resistance, distinguishing between emotional, practical, and organizational factors.
• Develop a comprehensive resistance management plan that includes:
• Specific strategies to address each type of resistance identified
• Communication approaches tailored to resistant stakeholders
• Opportunities for stakeholder involvement in shaping the implementation
• Methods for demonstrating early wins and building confidence
• Metrics to track changes in acceptance over time
• Prioritize your recommendations based on potential impact and feasibility.
• Be prepared to present and discuss your plan with the interview team.

Feedback Mechanism:

• Provide feedback on the candidate's analysis of resistance factors and the creativity of their proposed solutions.
• Challenge one of their assumptions or approaches, suggesting a potential complication they didn't consider.
• Ask the candidate to revise one section of their plan based on this new information, observing how they adapt their thinking and incorporate feedback.

Activity #3: AI Change Communication Strategy Development

This exercise evaluates a candidate's ability to develop effective communication strategies for AI implementation. Clear, thoughtful communication is essential for building understanding, managing expectations, and fostering adoption of AI technologies.

Directions for the Company:

• Provide a scenario of an upcoming AI implementation that will significantly change how certain roles or departments operate.
• Include details about the organization's culture, current communication channels, and any past challenges with change communication.
• Prepare examples of messaging that has worked well in your organization previously.
• Allow 60 minutes for this exercise.
• Have marketing or internal communications representatives available to review the strategy.

Directions for the Candidate:

• Review the AI implementation scenario provided.
• Develop a comprehensive communication strategy that includes:
• Key messages for different stakeholder groups (executives, managers, end users, etc.)
• Communication timeline aligned with implementation phases
• Channel strategy (which messages go through which channels)
• Approach for gathering and responding to feedback
• Methods for measuring communication effectiveness
• Create sample communication artifacts such as:
• An announcement email from leadership
• Talking points for managers to use with their teams
• FAQ document addressing common concerns
• Be prepared to explain the rationale behind your communication choices.

Feedback Mechanism:

• Provide feedback on the clarity, empathy, and effectiveness of the candidate's communication strategy.
• Identify one stakeholder group whose needs might not be fully addressed by the proposed approach.
• Ask the candidate to develop an additional communication tactic specifically for this stakeholder group, observing how they tailor their approach to address specific concerns or information needs.

Activity #4: AI Training and Adoption Planning

This exercise assesses a candidate's ability to develop effective training and adoption strategies for AI tools. Successful AI implementation requires thoughtful approaches to building new skills and encouraging new behaviors throughout the organization.

Directions for the Company:

• Create a scenario describing an AI tool being implemented that will require significant learning and behavior change.
• Provide details about the tool's functionality, the skills required to use it effectively, and the diversity of user groups (technical proficiency, roles, locations).
• Include information about available training resources and constraints (budget, time, existing learning platforms).
• Allow 60 minutes for this exercise.
• Have L&D or training specialists available to review the plan.

Directions for the Candidate:

• Review the AI implementation scenario provided.
• Develop a comprehensive training and adoption plan that includes:
• Learning objectives for different user groups
• Training approaches and methodologies (e.g., instructor-led, self-paced, peer learning)
• Timeline for training delivery aligned with implementation phases
• Strategies for reinforcing learning and encouraging adoption
• Methods for identifying and supporting struggling users
• Metrics to evaluate training effectiveness and adoption rates
• Create a sample training module outline for one key user group.
• Develop an adoption incentive or gamification strategy to encourage ongoing use.
• Be prepared to discuss how your plan addresses different learning styles and potential resistance.

Feedback Mechanism:

• Provide feedback on the comprehensiveness and creativity of the candidate's training and adoption plan.
• Challenge one aspect of their approach, such as timeline feasibility or resource requirements.
• Ask the candidate to revise their plan to address this challenge, observing how they balance ideal approaches with practical constraints.

Frequently Asked Questions

How long should each of these work sample exercises take?

Each exercise is designed to take 45-60 minutes. However, you can adjust the scope based on your hiring timeline. For more senior positions, you might consider allowing candidates to complete one or two exercises before the interview and then discuss their approach during the interview itself.

Should we use real AI implementation projects from our organization for these exercises?

Using real projects provides the most relevant assessment, but you should modify sensitive details. If you haven't yet implemented AI, create realistic scenarios based on your industry and organizational structure. The key is to make the scenario detailed enough that candidates can demonstrate their strategic thinking.

How should we evaluate candidates who have experience with change management but limited AI knowledge?

Look for candidates who demonstrate strong change management fundamentals and an ability to ask insightful questions about the AI technology. The best candidates will recognize what they don't know and show how they would partner with technical experts to develop appropriate change strategies.

Can these exercises be adapted for remote interviews?

Yes, all of these exercises can be conducted remotely. Provide the scenarios and templates digitally, and use video conferencing for presentations and feedback discussions. Consider using collaborative tools like Miro or Google Docs to observe the candidate's thinking process in real-time.

How do we ensure these exercises don't disadvantage candidates from underrepresented groups?

Review your scenarios to ensure they don't contain cultural assumptions or jargon that might disadvantage certain candidates. Provide clear instructions and evaluation criteria, and ensure all candidates receive similar preparation materials and time allowances. Consider having diverse reviewers evaluate the work samples to minimize unconscious bias.

Should we share our evaluation criteria with candidates before the exercise?

Sharing general evaluation criteria (e.g., "We'll be looking at your stakeholder analysis, communication approach, and implementation planning") helps candidates understand expectations without revealing specific "right answers." This approach creates a more equitable assessment while still allowing you to observe authentic problem-solving approaches.

Effective AI change management is critical to realizing the full potential of artificial intelligence investments. By incorporating these work samples into your hiring process, you'll be able to identify candidates who can navigate the complex human and organizational challenges of AI implementation. The best candidates will demonstrate not only technical understanding of AI capabilities but also deep empathy for how these technologies impact people and processes.

Remember that successful AI change management requires a balance of strategic vision and practical execution. Look for candidates who can develop comprehensive strategies while also demonstrating the flexibility to adapt their approaches based on feedback and changing circumstances. By finding the right AI change management strategist, you'll significantly increase your organization's chances of successful AI transformation.

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