Essential Work Samples for Evaluating AI Transformation Leadership Skills

Leading an organization through AI transformation requires a unique blend of technical understanding, strategic vision, change management expertise, and ethical leadership. As AI technologies continue to reshape industries, companies need leaders who can navigate this complex landscape while driving meaningful business outcomes. The right AI transformation leader can accelerate adoption, mitigate risks, and create sustainable competitive advantages.

Evaluating candidates for AI transformation leadership roles presents unique challenges. Traditional interviews often fail to reveal a candidate's ability to translate AI knowledge into practical business applications or their capacity to lead teams through significant technological change. Without proper assessment, organizations risk hiring leaders who understand AI conceptually but struggle to implement it effectively within existing business structures.

Work samples and role plays provide a window into how candidates approach real-world AI transformation challenges. These exercises reveal critical thinking patterns, decision-making frameworks, and leadership styles that might otherwise remain hidden in conventional interviews. By observing candidates tackle realistic scenarios, hiring teams can better predict future performance and cultural fit.

The following four activities are designed to evaluate key competencies required for successful AI transformation leadership. Each exercise tests different aspects of the role, from strategic planning and ethical decision-making to cross-functional leadership and resource allocation. By incorporating these activities into your interview process, you'll gain deeper insights into each candidate's readiness to lead your organization's AI journey.

Activity #1: AI Transformation Roadmap Development

This exercise evaluates a candidate's ability to develop a strategic vision for AI implementation while considering organizational readiness, technical feasibility, and business priorities. Successful AI transformation leaders must be able to create comprehensive roadmaps that balance ambition with pragmatism, addressing both technical and organizational challenges.

Directions for the Company:

• Provide the candidate with a brief (1-2 page) description of a fictional company, including its industry, size, current technology landscape, business goals, and key challenges.
• Include basic information about the company's current AI maturity level (e.g., limited AI adoption, siloed AI projects, or early-stage implementation).
• Give candidates 24-48 hours to prepare a high-level AI transformation roadmap.
• Allocate 30 minutes for presentation and 15 minutes for questions during the interview.
• Ensure the interview panel includes stakeholders from technology, business, and change management functions.

Directions for the Candidate:

• Review the company profile and develop a 12-18 month AI transformation roadmap.
• Your roadmap should include:
• Assessment of the organization's AI readiness
• 3-5 priority AI initiatives with clear business outcomes
• Required capabilities (technical, talent, data)
• Implementation approach and timeline
• Change management considerations
• Key success metrics
• Prepare a 15-minute presentation explaining your roadmap and strategic rationale.
• Be prepared to discuss how you would adjust the roadmap based on different scenarios (e.g., budget constraints, talent shortages, or competitive pressures).

Feedback Mechanism:

• After the presentation, provide specific feedback on one strength (e.g., "Your prioritization of use cases showed strong business acumen") and one area for improvement (e.g., "The change management approach could be more detailed").
• Ask the candidate to spend 5-10 minutes revising one aspect of their roadmap based on the feedback, explaining their thought process as they make adjustments.
• Observe how receptive the candidate is to feedback and how effectively they incorporate it into their thinking.

Activity #2: AI Ethics and Governance Role Play

This role play assesses a candidate's ability to navigate complex ethical considerations in AI implementation while balancing innovation with responsible use. Leaders of AI transformation must be prepared to address ethical dilemmas, establish appropriate governance frameworks, and communicate effectively with diverse stakeholders about sensitive issues.

Directions for the Company:

• Create a scenario involving an ethical dilemma related to AI implementation (e.g., algorithmic bias in a hiring tool, privacy concerns with customer data, or transparency issues with an AI decision-making system).
• Assign roles to your interview team members (e.g., concerned board member, skeptical department head, enthusiastic data scientist).
• Provide the candidate with a brief description of the scenario 30 minutes before the exercise.
• Allocate 20-25 minutes for the role play and 5-10 minutes for reflection and feedback.
• Prepare specific questions that challenge the candidate's position from different stakeholder perspectives.

Directions for the Candidate:

• Review the ethical dilemma scenario and prepare to lead a meeting addressing the concerns.
• Your objectives are to:
• Demonstrate understanding of the ethical implications
• Propose a balanced approach that addresses concerns while enabling innovation
• Outline governance principles or frameworks that would help prevent similar issues
• Build consensus among stakeholders with different priorities
• Begin the meeting by framing the issue and your proposed approach, then engage with stakeholders to address their concerns.
• Be prepared to adjust your approach based on new information or perspectives that emerge during the discussion.

Feedback Mechanism:

• After the role play, provide feedback on one strength (e.g., "You effectively balanced ethical considerations with business needs") and one area for improvement (e.g., "Consider addressing the technical complexity in more accessible language").
• Ask the candidate to spend 5 minutes reflecting on how they would refine their approach based on the feedback.
• Have them briefly explain what they would do differently if they could restart the conversation with one particular stakeholder.

Activity #3: Cross-functional AI Implementation Simulation

This simulation evaluates a candidate's ability to lead diverse teams through the challenges of implementing AI solutions. Successful AI transformation requires bringing together technical and business stakeholders, managing resistance to change, and ensuring alignment across different organizational functions.

Directions for the Company:

• Create a scenario involving the implementation of an AI solution that affects multiple departments (e.g., an AI-powered customer service chatbot that impacts sales, marketing, and support teams).
• Prepare role descriptions for 3-4 team members representing different functions (e.g., IT director, department head, frontline manager, data scientist).
• Assign these roles to your interview team members, providing them with specific concerns, priorities, and resistance points.
• Give the candidate information about the AI project and stakeholder profiles 1 hour before the exercise.
• Allocate 30 minutes for the simulation and 10 minutes for reflection.

Directions for the Candidate:

• Review the AI implementation scenario and stakeholder profiles.
• Prepare to facilitate a cross-functional meeting with the following objectives:
• Align stakeholders on the project goals and success metrics
• Address concerns and resistance from different departments
• Develop a collaborative approach to implementation
• Establish clear roles, responsibilities, and next steps
• During the 30-minute meeting, demonstrate your ability to:
• Translate technical concepts for non-technical stakeholders
• Mediate conflicts between different priorities
• Build consensus while maintaining momentum
• Balance short-term disruption with long-term benefits

Feedback Mechanism:

• After the simulation, provide feedback on one strength (e.g., "You effectively addressed the marketing team's concerns about brand consistency") and one area for improvement (e.g., "Consider spending more time understanding the IT team's technical constraints").
• Ask the candidate to spend 5 minutes addressing the improvement area by re-engaging with the relevant stakeholder.
• Observe how the candidate adjusts their approach and whether they demonstrate improved effectiveness.

Activity #4: AI Investment Prioritization Exercise

This exercise assesses a candidate's ability to make strategic decisions about AI investments, balancing technical feasibility, business impact, and organizational readiness. Leaders of AI transformation must be able to evaluate competing initiatives and allocate limited resources effectively.

Directions for the Company:

• Create profiles for 5-7 potential AI initiatives across different business functions (e.g., predictive maintenance in operations, customer churn prediction in marketing, document processing automation in legal).
• For each initiative, provide information on:
• Estimated implementation cost and timeline
• Potential business impact (quantitative and qualitative)
• Technical complexity and data requirements
• Organizational readiness and potential resistance
• Specify constraints (e.g., budget limitations, technical resources, timeline).
• Give candidates the materials 1 hour before the exercise.
• Allocate 20 minutes for the candidate's presentation and 15 minutes for questions.

Directions for the Candidate:

• Review the AI initiative profiles and constraints.
• Develop a prioritization framework that considers business impact, technical feasibility, organizational readiness, and strategic alignment.
• Apply your framework to rank the initiatives and select 2-3 for immediate implementation.
• Prepare to present your prioritization approach, explaining:
• Your evaluation criteria and why they matter
• Your ranking of initiatives with clear rationale
• Implementation sequence and dependencies
• How you would measure success
• Risks and mitigation strategies
• Be prepared to defend your choices and discuss trade-offs.

Feedback Mechanism:

• After the presentation, provide feedback on one strength (e.g., "Your framework effectively balanced short-term wins with strategic initiatives") and one area for improvement (e.g., "Consider incorporating more data readiness factors into your evaluation").
• Introduce a new constraint or changed assumption (e.g., "What if your budget was cut by 30%?" or "What if the CEO mandated a focus on customer experience?").
• Give the candidate 5-10 minutes to adjust their prioritization based on the new information and feedback.
• Evaluate their ability to adapt their thinking while maintaining a coherent strategic approach.

Frequently Asked Questions

How much technical AI knowledge should candidates demonstrate in these exercises?

While candidates should have sufficient technical understanding to evaluate AI solutions and communicate with technical teams, these exercises focus more on leadership and strategic capabilities. Look for candidates who can translate technical concepts for business audiences and ask insightful questions rather than those who simply demonstrate technical depth.

Should we customize these exercises for our specific industry?

Yes, absolutely. While these exercises provide a general framework, you should adapt the scenarios, company profiles, and AI initiatives to reflect your industry's specific challenges and opportunities. This customization will help you evaluate how well candidates understand your business context.

How do we evaluate candidates who have strong technical AI backgrounds versus those with strong change management experience?

Consider using a balanced scoring rubric that weights different competencies based on your organization's specific needs. Some organizations may need stronger technical leadership, while others may prioritize change management expertise. Ideally, look for candidates who demonstrate a balance of both, with particular strength in the areas most critical to your current transformation stage.

What if a candidate proposes an approach that's very different from what we expected?

This can actually be valuable information. Evaluate the quality of their reasoning rather than adherence to your expected approach. Strong candidates may bring fresh perspectives that challenge your assumptions. However, their approach should still demonstrate sound strategic thinking, business acumen, and practical feasibility.

How can we make these exercises fair for candidates with different backgrounds?

Provide sufficient context and background information so candidates aren't disadvantaged if they lack specific industry or company knowledge. Focus evaluation on their approach, reasoning, and leadership capabilities rather than prior knowledge. Consider providing pre-reading materials to level the playing field.

Can these exercises be conducted virtually?

Yes, all of these exercises can be adapted for virtual interviews. For the roadmap and prioritization exercises, candidates can share their screens during presentations. Role plays and simulations can be conducted via video conference, though you may need to provide more structure and facilitation to ensure effective interaction.

Leading AI transformation requires a unique combination of technical understanding, strategic vision, and change leadership capabilities. By incorporating these work samples and role plays into your interview process, you'll gain deeper insights into candidates' readiness to guide your organization through this complex journey. Remember that the most successful AI transformation leaders balance technological innovation with organizational realities, bringing together diverse stakeholders around a shared vision for AI-enabled success.

For more resources to support your hiring process, explore Yardstick's suite of AI-powered tools, including our AI Job Descriptions generator, AI Interview Question Generator, and AI Interview Guide Generator.