Effective Work Samples to Evaluate AI-Augmented Decision Making Skills for Managers

In today's rapidly evolving business landscape, managers who can effectively leverage artificial intelligence to enhance their decision-making processes have a significant competitive advantage. AI-augmented decision making combines human judgment with machine intelligence, allowing managers to process larger volumes of data, identify patterns that might otherwise go unnoticed, and make more informed decisions with greater confidence and speed.

Evaluating a candidate's proficiency in AI-augmented decision making requires more than just theoretical knowledge assessment. Practical work samples that simulate real-world scenarios provide invaluable insights into how candidates approach AI tools, interpret AI-generated insights, and integrate those insights into their decision-making processes. These exercises reveal a candidate's critical thinking abilities, their understanding of AI's capabilities and limitations, and their skill in communicating AI-driven recommendations to various stakeholders.

The most effective managers in this space don't simply accept AI outputs at face value but know how to ask the right questions, recognize potential biases, and balance algorithmic recommendations with human expertise and organizational context. They understand when to rely on AI and when human judgment should take precedence. These nuanced skills are difficult to assess through traditional interview questions alone.

The following work samples are designed to evaluate a candidate's ability to work with AI tools in management contexts, interpret AI-generated insights, plan AI implementations, and make sound decisions using AI as a supportive tool rather than a replacement for managerial judgment. By observing candidates as they work through these exercises, hiring teams can gain valuable insights into how effectively candidates will leverage AI to drive better business outcomes.

Activity #1: Data-Driven Decision Analysis

This exercise evaluates a manager's ability to interpret AI-generated data insights and apply them to a business decision. Effective AI-augmented decision makers can extract meaningful conclusions from complex data, identify limitations in the analysis, and integrate these insights with their business knowledge to make sound recommendations.

Directions for the Company:

• Prepare a realistic business scenario with a decision that needs to be made (e.g., resource allocation, market expansion, product feature prioritization).
• Create a mock AI analysis dashboard or report with relevant metrics, trends, and recommendations. Include some clear insights but also some ambiguous or potentially misleading data points.
• Provide context about the business goals, constraints, and stakeholders involved.
• Allow 30-45 minutes for the candidate to review materials and prepare their recommendation.
• Have 1-2 interviewers available to ask questions about the candidate's decision-making process.

Directions for the Candidate:

• Review the business scenario and AI-generated analysis provided.
• Identify the key insights from the AI analysis that are most relevant to the decision at hand.
• Prepare a recommendation based on the AI insights combined with your business judgment.
• Be prepared to explain:
• Which AI-generated insights you found most valuable and why
• Any limitations or potential biases in the AI analysis
• How you integrated the AI insights with your own expertise
• Your final recommendation and the rationale behind it

Feedback Mechanism:

• After the candidate presents their recommendation, provide feedback on one aspect they handled well (e.g., their critical evaluation of the data or clear communication of insights).
• Provide one piece of constructive feedback about an area for improvement (e.g., overlooking a potential bias in the data or not considering a key business constraint).
• Ask the candidate to revise part of their recommendation based on this feedback, giving them 5-10 minutes to incorporate the new perspective.

Activity #2: AI Implementation Planning

This exercise assesses a manager's ability to strategically plan the implementation of an AI tool within their department. It tests their understanding of change management, stakeholder communication, and practical considerations when introducing AI into existing workflows.

Directions for the Company:

• Create a scenario describing a department with specific challenges that could be addressed by an AI solution (e.g., customer service team with high volume of repetitive inquiries, marketing team needing better customer segmentation).
• Provide information about the department's current processes, team composition, and any relevant constraints.
• Include a brief description of an AI tool that could help address these challenges, with its capabilities and limitations.
• Allow 45 minutes for the candidate to develop their implementation plan.

Directions for the Candidate:

• Review the department scenario and the proposed AI solution.
• Develop a 90-day implementation plan that addresses:
• Key milestones and timeline
• Required resources and potential costs
• Training needs for team members
• Change management approach
• Success metrics and evaluation methods
• Potential risks and mitigation strategies
• Create a one-page executive summary of your plan, highlighting the business case and expected outcomes.
• Be prepared to present your plan and answer questions about your approach.

Feedback Mechanism:

• Provide positive feedback on one aspect of the implementation plan that was particularly well-thought-out.
• Offer constructive feedback on one area that could be strengthened (e.g., overlooking a key stakeholder group or not adequately addressing data privacy concerns).
• Ask the candidate to revise the specific section of their plan that relates to the feedback, giving them 10 minutes to make adjustments.

Activity #3: AI-Informed Stakeholder Communication Role Play

This role play evaluates a manager's ability to effectively communicate AI-generated insights and recommendations to stakeholders who may have varying levels of AI literacy. It tests their skill in translating technical concepts into business value and addressing concerns about AI-driven decision making.

Directions for the Company:

• Prepare a scenario where an AI system has generated recommendations that challenge conventional wisdom or current practices within the organization.
• Create profiles for 1-2 stakeholders with different perspectives (e.g., a skeptical executive concerned about AI replacing human judgment, a technical team member questioning the AI methodology).
• Have interviewers role play these stakeholders during the exercise.
• Provide the candidate with the AI-generated recommendation and brief background on the stakeholders 30 minutes before the role play.

Directions for the Candidate:

• Review the AI-generated recommendation and stakeholder profiles.
• Prepare to explain the AI insights in business terms that will resonate with each stakeholder.
• During the 15-minute role play:
• Present the AI-generated recommendation clearly and concisely
• Explain how the AI arrived at this conclusion (in non-technical terms)
• Address potential concerns about the recommendation
• Propose a path forward that balances AI insights with human expertise
• Be prepared to answer challenging questions and address resistance from the stakeholders.

Feedback Mechanism:

• After the role play, provide feedback on one communication strength demonstrated by the candidate (e.g., effective translation of technical concepts or skillful handling of objections).
• Offer one piece of constructive feedback about their communication approach (e.g., not adequately addressing a stakeholder's concern or overemphasizing technical details).
• Give the candidate 5 minutes to reflect, then ask them to re-approach a specific part of the conversation incorporating the feedback.

Activity #4: Critical Evaluation of AI Recommendations

This exercise tests a manager's ability to critically evaluate AI-generated recommendations, identify potential biases or limitations, and make sound judgments about when to follow or override AI guidance. It assesses their understanding of AI ethics and responsible use of AI in decision making.

Directions for the Company:

• Create a scenario with an AI system that has generated recommendations for a sensitive business decision (e.g., employee performance evaluation, customer credit approval, resource allocation across diverse communities).
• Include some subtle biases, limitations, or ethical concerns in the AI's approach or recommendations.
• Provide context about the organization's values and relevant policies.
• Allow 30 minutes for the candidate to review and analyze the materials.

Directions for the Candidate:

• Review the scenario and AI-generated recommendations.
• Critically evaluate the recommendations by:
• Identifying potential biases or limitations in the AI's approach
• Assessing alignment with organizational values and policies
• Considering potential unintended consequences
• Determining where human judgment should supplement or override AI recommendations
• Prepare a written assessment (1-2 pages) that:
• Summarizes your evaluation of the AI recommendations
• Identifies specific concerns or limitations
• Provides your modified recommendations that address these concerns
• Outlines safeguards you would implement for future AI-augmented decisions in this area

Feedback Mechanism:

• Provide positive feedback on one aspect of their critical analysis that demonstrated strong ethical reasoning or bias detection.
• Offer constructive feedback on one area where they could have dug deeper or considered additional perspectives.
• Ask the candidate to verbally address how they would incorporate this feedback into their approach, giving them 5-10 minutes to articulate their revised thinking.

Frequently Asked Questions

How much AI technical knowledge should candidates have to complete these exercises?

These exercises are designed to test AI-augmented decision making for managers, not technical AI expertise. Candidates should understand AI concepts at a high level and know how to interpret and apply AI-generated insights, but they don't need to know how to build AI models or understand the technical details of algorithms.

Should we customize these exercises for our specific industry?

Yes, absolutely. While these exercises provide a general framework, they'll be most effective when adapted to your industry context. Use real (anonymized) data from your organization when possible, and create scenarios that reflect the types of decisions your managers typically face.

How should we evaluate candidates who have limited prior experience with AI tools?

Focus on their critical thinking, adaptability, and decision-making process rather than their familiarity with specific AI tools. Look for candidates who ask insightful questions about the AI outputs, recognize the need to balance AI insights with human judgment, and demonstrate a willingness to learn and adapt to new technologies.

What if we don't currently use AI tools in our organization?

These exercises are still valuable for assessing how future managers will approach AI as your organization adopts these technologies. You can frame the exercises as preparation for planned AI implementations or hypothetical scenarios. The skills being tested—critical thinking, data interpretation, strategic planning, and stakeholder communication—are valuable regardless of your current AI maturity.

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

Be mindful of potential biases in your scenarios and evaluation criteria. Provide clear instructions and equal preparation time for all candidates. Focus on evaluating the quality of thinking and decision-making rather than familiarity with specific tools or technologies that might reflect privileged access. Consider having diverse perspectives on your interview panel to ensure fair evaluation.

Can these exercises be conducted remotely?

Yes, all of these exercises can be adapted for remote interviews. For data analysis and planning exercises, provide materials in advance through secure sharing platforms. For role plays, use video conferencing. Consider extending time limits slightly to account for potential technical issues in remote settings.

As AI continues to transform business operations and decision-making processes, managers who can effectively leverage these tools while maintaining sound judgment will be invaluable assets to any organization. By incorporating these practical work samples into your hiring process, you can identify candidates who not only understand AI's potential but can thoughtfully apply it to drive better business outcomes.

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