Effective Work Samples to Evaluate AI Process Improvement Skills in Candidates

Organizations increasingly rely on artificial intelligence to transform their operations, streamline workflows, and drive innovation across departments. Finding candidates who can effectively leverage AI for cross-functional process improvement requires more than reviewing resumes and conducting standard interviews. These individuals must possess a unique blend of technical AI knowledge, business process expertise, change management skills, and cross-departmental collaboration abilities.

Traditional interviews often fail to reveal a candidate's true capabilities in applying AI to real-world business challenges. While candidates may articulate theoretical knowledge, their practical ability to identify opportunities, design solutions, and implement AI-driven improvements across organizational boundaries remains untested. This gap between interview performance and on-the-job effectiveness can lead to costly hiring mistakes.

Work samples and role plays provide a window into how candidates actually approach AI-driven process improvement. By simulating realistic scenarios, you can observe candidates' thought processes, problem-solving approaches, and communication skills in action. These exercises reveal not just what candidates know about AI, but how they apply that knowledge to create value across different business functions.

The following work samples are designed to evaluate a candidate's ability to identify AI opportunities, develop implementation strategies, communicate with stakeholders, and measure the impact of AI solutions across organizational boundaries. Each exercise targets specific aspects of AI-driven process improvement while maintaining a focus on cross-functional collaboration and business value creation.

Activity #1: Process Analysis and AI Opportunity Identification

This exercise evaluates a candidate's ability to analyze existing business processes, identify inefficiencies, and propose appropriate AI solutions that span multiple departments. Strong candidates will demonstrate both technical AI knowledge and business process improvement expertise while considering cross-functional impacts and dependencies.

Directions for the Company:

• Provide the candidate with documentation of a real (or realistic) cross-functional business process that involves multiple departments (e.g., order-to-cash, procurement, customer onboarding).
• Include process maps, key metrics, pain points, and brief descriptions of the systems involved.
• Allow 45-60 minutes for the candidate to review materials and prepare their analysis.
• Have a panel representing different functions (IT, operations, finance, etc.) available for the presentation and Q&A.

Directions for the Candidate:

• Review the provided business process documentation.
• Identify 2-3 key areas where AI could improve efficiency, accuracy, or value across multiple departments.
• For each opportunity, specify:
• The AI technology/approach you would recommend
• Expected benefits for each department involved
• Data requirements and potential integration challenges
• Implementation considerations and timeline
• Prepare a 10-minute presentation of your findings and recommendations.
• Be prepared to answer questions about your approach and recommendations.

Feedback Mechanism:

• After the presentation, provide feedback on one strength (e.g., "Your identification of natural language processing for contract analysis would benefit both legal and procurement teams") and one area for improvement (e.g., "Consider how the proposed solution would impact downstream departments").
• Ask the candidate to revise one of their recommendations based on the feedback, giving them 5-10 minutes to adjust their approach and explain how they would address the concern.

Activity #2: Cross-Functional AI Implementation Planning

This exercise assesses a candidate's ability to develop a practical implementation plan for an AI solution that affects multiple departments. It tests their understanding of change management, technical implementation steps, and their ability to coordinate activities across organizational boundaries.

Directions for the Company:

• Create a scenario where an AI solution has been approved for implementation (e.g., an AI-powered forecasting system that will affect sales, operations, and finance).
• Provide information about the organization structure, key stakeholders, current systems, and the selected AI solution.
• Include any relevant constraints (budget, timeline, resource limitations).
• Allow 60 minutes for the candidate to develop their implementation plan.

Directions for the Candidate:

• Develop a comprehensive implementation plan for the AI solution that addresses:
• Key milestones and timeline
• Required resources from each department
• Data integration and system changes
• Training and change management activities
• Risk mitigation strategies
• Success metrics and measurement approach
• Create a responsibility matrix showing which departments own which aspects of the implementation.
• Identify potential cross-functional challenges and how you would address them.
• Prepare to present your plan in 15 minutes, focusing on how you would coordinate activities across departments.

Feedback Mechanism:

• Provide feedback on one strength (e.g., "Your phased approach minimizes disruption to daily operations") and one area for improvement (e.g., "Consider adding more detail about how you would handle resistance from the finance team").
• Ask the candidate to revise the portion of their plan related to the improvement feedback, giving them 10 minutes to adjust and explain their new approach.

Activity #3: Stakeholder Communication Role Play

This role play evaluates a candidate's ability to communicate complex AI concepts to non-technical stakeholders and build buy-in across different departments. It tests their change management skills, empathy, and ability to translate technical benefits into business value for various functions.

Directions for the Company:

• Prepare a scenario where the candidate must present an AI process improvement initiative to stakeholders from different departments.
• Create role cards for 2-3 interviewers who will play stakeholders with different concerns:
• A skeptical operations manager concerned about disruption
• A finance leader focused on ROI and cost
• A department head worried about job displacement
• Provide the candidate with information about the AI initiative, its benefits, and brief profiles of the stakeholders.
• Allow 20 minutes for preparation and 15-20 minutes for the role play.

Directions for the Candidate:

• Review the information about the AI initiative and stakeholder profiles.
• Prepare a brief presentation (5 minutes) explaining the initiative in business terms.
• Be ready to address concerns, answer questions, and build buy-in from stakeholders with different priorities.
• Focus on communicating how the AI solution will benefit each department specifically.
• Demonstrate how you would handle resistance and objections from different functional perspectives.
• Your goal is to gain support for the initiative from all stakeholders.

Feedback Mechanism:

• After the role play, provide feedback on one communication strength (e.g., "You effectively translated technical concepts into business benefits for the operations team") and one area for improvement (e.g., "Consider addressing the human impact concerns more directly").
• Give the candidate 5 minutes to re-approach the stakeholder who had the strongest objections, incorporating the feedback to improve their communication approach.

Activity #4: Data-Driven AI Solution Evaluation

This exercise tests a candidate's ability to evaluate the effectiveness of an implemented AI solution across multiple departments and recommend improvements. It assesses analytical skills, critical thinking, and the ability to balance competing priorities from different functional areas.

Directions for the Company:

• Create a scenario where an AI solution has been implemented for 6-12 months across multiple departments.
• Provide data showing the solution's performance, including:
• Key metrics from each affected department (before and after implementation)
• User feedback from different functional areas
• Technical performance data
• Cost information
• Include some contradictory information (e.g., one department seeing great results while another struggles).
• Allow 45-60 minutes for analysis and preparation.

Directions for the Candidate:

• Analyze the provided data to evaluate the AI solution's effectiveness across all departments.
• Identify patterns, inconsistencies, and potential root causes for varying results.
• Develop 3-5 specific recommendations to improve the solution's performance for all departments.
• Prioritize your recommendations based on potential impact and feasibility.
• Prepare a 10-minute presentation of your analysis and recommendations.
• Be ready to explain your analytical approach and how you balanced competing departmental needs.

Feedback Mechanism:

• Provide feedback on one analytical strength (e.g., "Your identification of the data quality issues affecting the finance team's results was insightful") and one area for improvement (e.g., "Consider how your recommendations might create new challenges for the customer service department").
• Ask the candidate to revise one recommendation based on the feedback, giving them 10 minutes to adjust their approach and explain how they would address the concern.

Frequently Asked Questions

How long should we allocate for these work samples?

Each exercise requires 60-90 minutes total, including preparation, presentation, and feedback. For remote candidates, consider sending materials in advance and scheduling a video call for the presentation and feedback portions. You can also use these exercises as half-day or full-day assessment centers for final candidates.

Should we use real company data for these exercises?

While using real data provides the most authentic assessment, confidentiality concerns may require creating realistic fictional scenarios. If using real data, ensure it's anonymized and doesn't reveal sensitive information. The key is providing enough context and detail for candidates to demonstrate their skills effectively.

What if we don't have representatives from multiple departments available for the exercises?

Ideally, include stakeholders from different functions to evaluate how candidates navigate cross-functional dynamics. If this isn't possible, ensure interviewers are briefed to represent different departmental perspectives during role plays and Q&A sessions. Alternatively, record the candidate's presentation for later review by stakeholders from other departments.

How should we evaluate candidates' performance on these exercises?

Create a structured scorecard aligned with the key skills required for AI-driven process improvement: technical AI knowledge, business process expertise, cross-functional thinking, communication skills, and change management abilities. Have each evaluator score independently before discussing, and weight the scores based on the relative importance of each skill to your specific needs.

What if a candidate has limited experience with our specific industry?

Focus your evaluation on the candidate's approach and thinking process rather than industry-specific knowledge. Strong candidates will ask clarifying questions and apply transferable principles from their experience. Consider providing additional industry context in the exercise materials to level the playing field.

How can we make these exercises accessible for remote candidates?

For remote assessments, use collaborative tools like Miro or Mural for process mapping, shared documents for planning exercises, and video conferencing with breakout rooms for role plays. Send materials in advance with clear instructions, and ensure candidates have access to necessary technology. Consider breaking longer exercises into multiple sessions if needed.

The process of finding candidates who excel at applying AI across functional boundaries requires going beyond traditional interviews. These work samples provide a comprehensive view of how candidates approach complex, cross-functional AI initiatives—from identifying opportunities to planning implementation, managing stakeholders, and measuring results.

By incorporating these exercises into your hiring process, you'll gain deeper insights into candidates' practical abilities and significantly improve your chances of selecting individuals who can successfully drive AI-powered process improvements across your organization. For more resources to enhance your hiring process, explore Yardstick's tools for creating AI job descriptions, generating targeted interview questions, and developing comprehensive interview guides.

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