Essential Work Samples for Evaluating AI Implementation Skills in Non-Technical Candidates

Implementing AI solutions has become a critical business function across industries, even for professionals without deep technical expertise. As organizations increasingly adopt AI technologies, the ability to strategically implement these tools without coding knowledge has become a valuable skill set. The most successful non-technical AI implementers possess a unique combination of business acumen, project management capabilities, and enough AI literacy to bridge the gap between technical teams and business objectives.

Evaluating candidates for roles involving AI implementation without technical expertise requires assessing their ability to identify valuable use cases, evaluate solutions, plan implementations, and navigate ethical considerations. Traditional interviews often fail to reveal these practical skills, as candidates may articulate theoretical knowledge without demonstrating applied capabilities.

Work samples provide a realistic preview of how candidates approach AI implementation challenges. By observing candidates tackle representative tasks, hiring managers can assess their problem-solving approach, critical thinking, and ability to translate business needs into AI solutions. These exercises reveal how candidates navigate ambiguity, prioritize competing demands, and communicate complex concepts to stakeholders with varying technical backgrounds.

The following work samples are designed to evaluate candidates' abilities to implement AI solutions without requiring coding or deep technical expertise. Each exercise targets different aspects of the AI implementation process, from identifying opportunities to planning deployments and addressing ethical considerations. By incorporating these exercises into your hiring process, you'll gain valuable insights into which candidates can effectively bridge the gap between AI's potential and practical business applications.

Activity #1: AI Use Case Identification & Prioritization

This exercise evaluates a candidate's ability to identify valuable AI applications within a business context and prioritize them based on feasibility, impact, and resource requirements. Strong candidates will demonstrate business acumen by connecting AI capabilities to specific business challenges, while realistically assessing implementation complexity and potential ROI.

Directions for the Company:

• Prepare a brief (1-2 page) description of a fictional or anonymized company, including its industry, key business challenges, available data assets, and current technology infrastructure.
• Include 3-4 departmental pain points that might benefit from AI solutions (e.g., customer service bottlenecks, inventory management issues, marketing personalization challenges).
• Provide the candidate with this information 24 hours before the interview to allow for preparation.
• Allocate 20-30 minutes for the candidate's presentation and 10-15 minutes for questions and feedback.
• Prepare a scoring rubric that evaluates the candidate's understanding of AI capabilities, business alignment, prioritization logic, and implementation considerations.

Directions for the Candidate:

• Review the provided company information and identify 3-5 potential AI use cases that could address business challenges.
• For each use case, describe:
• The specific business problem being solved
• The type of AI solution that would address it (e.g., document processing, predictive analytics, conversational AI)
• The expected business impact (quantified if possible)
• Implementation complexity (low/medium/high)
• Data requirements and potential challenges
• Create a prioritization matrix or framework to rank these opportunities.
• Prepare a brief presentation (5-7 slides) explaining your recommendations and prioritization logic.
• Be prepared to discuss why certain use cases were selected over others.

Feedback Mechanism:

• After the presentation, provide specific feedback on one strength (e.g., "Your prioritization framework effectively balanced business impact with implementation complexity").
• Offer one area for improvement (e.g., "Consider addressing data privacy implications more explicitly in your evaluation").
• Ask the candidate to revise their prioritization based on the feedback and explain how this changes their recommendations.
• Observe how receptive they are to feedback and how effectively they incorporate it into their thinking.

Activity #2: AI Vendor/Solution Evaluation

This exercise assesses a candidate's ability to evaluate AI vendors and solutions without getting lost in technical details. It tests their capacity to ask the right questions, identify key evaluation criteria, and make informed decisions about AI partnerships and technologies.

Directions for the Company:

• Create profiles for three fictional AI vendors offering solutions for a specific business need (e.g., customer service chatbots, predictive maintenance, or content moderation).
• Include in each profile: company background, solution overview, pricing model, implementation timeline, integration capabilities, and 2-3 client testimonials.
• Intentionally include some ambiguities and trade-offs between the vendors (e.g., one has better performance but higher cost, another has faster implementation but fewer features).
• Provide these materials to the candidate 24 hours before the interview.
• Prepare to role-play as representatives from each vendor who can answer questions.

Directions for the Candidate:

• Review the vendor profiles and prepare a structured evaluation approach.
• Develop a set of 8-10 critical questions you would ask each vendor to clarify their offerings and determine fit.
• Create an evaluation matrix with criteria weighted by importance for this specific business need.
• During the exercise, you'll have 15 minutes to interview "representatives" from each vendor (role-played by the interviewer).
• After the interviews, take 10 minutes to complete your evaluation and prepare a recommendation.
• Present your recommendation, including:
• Your evaluation methodology
• Key differentiators between vendors
• Your final recommendation with rationale
• Implementation considerations for the chosen solution

Feedback Mechanism:

• Provide feedback on the effectiveness of the candidate's evaluation criteria and questioning strategy.
• Highlight one aspect of their approach that was particularly effective.
• Suggest one area where their evaluation could be improved (e.g., "You might want to consider data ownership and portability more explicitly in your criteria").
• Ask the candidate to revise one portion of their evaluation framework based on this feedback and explain how it might change their approach.

Activity #3: AI Implementation Planning

This exercise evaluates a candidate's ability to develop a comprehensive implementation plan for an AI solution, addressing cross-functional coordination, change management, and risk mitigation without focusing on technical development details.

Directions for the Company:

• Create a scenario where an AI solution has been selected (e.g., an AI-powered customer segmentation tool, a document processing system, or a forecasting solution), and now needs to be implemented.
• Provide context about the organization: team structure, key stakeholders, existing systems that need integration, and any relevant constraints or requirements.
• Include a brief description of the selected AI solution and its expected benefits.
• Prepare a list of potential implementation challenges that the candidate should address (without explicitly stating them).
• Allocate 45-60 minutes for this exercise.

Directions for the Candidate:

• Review the provided scenario and develop a comprehensive 90-day implementation plan for the AI solution.
• Your plan should include:
• Key milestones and timeline
• Required resources and team structure
• Stakeholder management approach
• Data preparation and governance considerations
• Integration with existing systems
• Training and change management strategy
• Success metrics and measurement approach
• Risk identification and mitigation strategies
• Create a visual representation of your implementation plan (e.g., Gantt chart, roadmap, or project plan).
• Prepare a brief presentation explaining your approach and key considerations.
• Be ready to discuss how you would adapt the plan if certain assumptions change.

Feedback Mechanism:

• Provide specific feedback on the strengths of the implementation plan (e.g., "Your stakeholder management approach effectively addresses potential resistance points").
• Identify one area that could be improved or that may present unexpected challenges.
• Ask the candidate to revise that portion of their plan based on your feedback.
• Evaluate how well they adapt their approach and whether they demonstrate flexibility while maintaining a structured implementation methodology.

Activity #4: AI Ethics and Risk Assessment

This exercise assesses a candidate's ability to identify and address ethical considerations and potential risks in AI implementation. It evaluates their awareness of responsible AI practices and their approach to mitigating unintended consequences without requiring technical expertise in AI fairness algorithms.

Directions for the Company:

• Develop a scenario describing an AI application that presents potential ethical challenges (e.g., an HR tool for screening candidates, a credit approval system, a customer service prioritization system, or a content moderation tool).
• Include details about the data being used, the decisions being automated or augmented, and the stakeholders affected.
• Prepare a list of ethical considerations that should be addressed (without explicitly stating them).
• Allocate 30-45 minutes for this exercise.
• Consider having someone play the role of a concerned stakeholder (e.g., privacy officer, legal counsel, or customer advocate) who will raise questions during the presentation.

Directions for the Candidate:

• Review the provided AI implementation scenario.
• Conduct an ethics and risk assessment that identifies:
• Potential biases in the data or algorithm
• Privacy implications and data protection considerations
• Transparency and explainability requirements
• Potential unintended consequences or misuse
• Compliance with relevant regulations (e.g., GDPR, CCPA)
• Impact on different stakeholder groups
• Develop a framework for ongoing monitoring and governance of the AI system.
• Create a one-page summary of your assessment and recommendations.
• Be prepared to present your findings and respond to questions from stakeholders with different perspectives.

Feedback Mechanism:

• Highlight one aspect of the candidate's ethical assessment that was particularly thorough or insightful.
• Identify one ethical consideration or risk that was overlooked or could be explored more deeply.
• Ask the candidate to develop a more detailed mitigation strategy for this newly identified risk.
• Evaluate how the candidate balances ethical considerations with business objectives and whether they can articulate a practical approach to responsible AI implementation.

Frequently Asked Questions

How long should these work sample exercises take?

Each exercise is designed to take 30-60 minutes, with additional time for feedback and discussion. For remote candidates, consider spreading the exercises across multiple interview sessions. For on-site interviews, you might select 2-3 exercises that best align with your specific needs.

Do I need AI expertise to evaluate candidates using these exercises?

While some familiarity with AI concepts is helpful, these exercises are designed to evaluate business and implementation skills rather than technical expertise. Focus on assessing the candidate's structured thinking, business acumen, and practical approach to implementation challenges.

Should candidates have access to resources during these exercises?

Yes, allowing candidates to use internet resources during preparation reflects real-world conditions. However, during the actual presentation or discussion, it's best to limit external resources to focus on the candidate's prepared thinking and ability to respond to questions.

How should I adapt these exercises for different seniority levels?

For junior roles, simplify the scenarios and focus on one or two aspects of implementation. For senior roles, increase complexity by adding constraints, stakeholder conflicts, or resource limitations that require more sophisticated prioritization and planning.

What if my organization has a specific AI use case in mind?

Feel free to adapt these exercises to focus on your specific use case or industry. Replacing the generic scenarios with anonymized versions of actual challenges your organization faces can make the assessment more relevant while giving candidates insight into the real work they would be doing.

Can I combine elements from different exercises?

Absolutely. These exercises are modular by design. You might combine the use case identification with implementation planning for a more comprehensive assessment, or focus solely on vendor evaluation if that's most relevant to your needs.

AI implementation without technical expertise has become a critical skill set as organizations increasingly adopt these technologies. By incorporating these practical work samples into your hiring process, you'll be able to identify candidates who can effectively bridge the gap between AI's potential and practical business applications, regardless of their technical background.

The most successful candidates will demonstrate a structured approach to implementation, strong business acumen, stakeholder management skills, and an awareness of ethical considerations—all without needing to write a single line of code. These exercises help reveal those capabilities in ways that traditional interviews simply cannot.

For more resources to improve your hiring process, check out Yardstick's AI Job Description Generator, AI Interview Question Generator, and AI Interview Guide Generator.

Build a complete interview guide for evaluating AI implementation skills by signing up for a free Yardstick account here