Effective Work Samples for Evaluating AI-Enhanced Benefits Selection Skills

AI-enhanced benefits selection and optimization represents a transformative approach to employee benefits management. As organizations seek to maximize the value of their benefits packages while controlling costs, professionals who can leverage artificial intelligence to analyze, predict, and optimize benefits selections are becoming increasingly valuable. These specialists bridge the gap between traditional HR benefits administration and cutting-edge data science, creating personalized benefits experiences that improve employee satisfaction and retention.

Evaluating candidates for roles requiring AI-enhanced benefits expertise presents unique challenges. The ideal candidate must demonstrate technical proficiency with AI tools and data analysis while also possessing deep knowledge of benefits administration and excellent communication skills. Traditional interviews often fail to reveal a candidate's true capabilities in these multifaceted areas.

Work samples provide a realistic preview of how candidates approach the complex challenges inherent in AI-enhanced benefits optimization. By observing candidates as they tackle representative tasks, hiring managers can assess both technical competence and practical application skills. These exercises reveal how candidates think through problems, leverage technology, and communicate complex concepts to stakeholders with varying levels of technical understanding.

The following work samples are designed to evaluate candidates' abilities to analyze benefits data, develop AI-driven optimization strategies, implement technological solutions, and effectively communicate recommendations to diverse audiences. Each exercise simulates real-world scenarios that professionals in this field encounter, providing valuable insights into which candidates possess the unique combination of skills required for success.

Activity #1: Benefits Data Analysis and AI Strategy Development

This activity assesses a candidate's ability to analyze benefits utilization data, identify patterns, and develop an AI-enhanced strategy for optimizing benefits offerings. It evaluates technical data analysis skills, strategic thinking, and the ability to connect data insights to practical benefits solutions.

Directions for the Company:

• Provide the candidate with a dataset containing anonymized employee benefits selection and utilization data for a fictional company (approximately 500-1000 employees).
• Include demographic information, current benefits selections, utilization rates, and satisfaction scores.
• Allow candidates 48 hours to review the data and prepare their analysis and recommendations.
• Schedule a 30-minute presentation followed by 15 minutes of questions.
• Ensure the dataset contains clear patterns that could be addressed through AI-enhanced benefits optimization (e.g., underutilization of certain benefits, demographic patterns in selection).

Directions for the Candidate:

• Analyze the provided benefits data to identify key patterns, trends, and opportunities for optimization.
• Develop a strategic proposal for how AI could be leveraged to improve benefits selection and utilization.
• Prepare a 30-minute presentation that includes:

1. Key findings from your data analysis
2. Specific AI applications you would recommend implementing
3. Expected outcomes and metrics for measuring success
4. Implementation considerations and potential challenges

• Be prepared to explain your analytical approach and defend your recommendations.

Feedback Mechanism:

• After the presentation, provide feedback on one strength (e.g., insightful data analysis, innovative AI application) and one area for improvement (e.g., more specific implementation details, clearer explanation of AI methodology).
• Ask the candidate to spend 10 minutes revising one section of their proposal based on the feedback, focusing on how they would address the improvement area.
• Evaluate both their initial work and their ability to incorporate feedback effectively.

Activity #2: AI-Driven Benefits Recommendation Engine Design

This exercise evaluates a candidate's ability to design a practical AI solution for personalized benefits recommendations. It tests technical knowledge of AI systems, understanding of benefits selection factors, and ability to create user-friendly technology solutions.

Directions for the Company:

• Create a scenario description for a mid-sized company (1,000-2,500 employees) looking to implement an AI-driven benefits recommendation engine.
• Include information about current benefits offerings, employee demographics, and specific challenges (e.g., low engagement with voluntary benefits, confusion during open enrollment).
• Provide a whiteboard or digital design tool for the candidate to sketch their solution.
• Allow 45 minutes for the exercise, including explanation and questions.

Directions for the Candidate:

• Design an AI-driven benefits recommendation engine that would help employees make optimal benefits selections based on their individual circumstances.
• Create a flowchart or system diagram showing:

1. Data inputs required (what information would the system collect from employees)
2. AI processing components (what algorithms or models would be used)
3. Output format and user experience (how recommendations would be presented)
4. Integration points with existing HR systems

• Explain how your system would address the specific challenges mentioned in the scenario.
• Be prepared to discuss technical considerations, privacy concerns, and implementation requirements.

Feedback Mechanism:

• Provide feedback on one strength of the design (e.g., thoughtful user experience, comprehensive data inputs) and one area for improvement (e.g., addressing privacy concerns, more specific AI methodology).
• Ask the candidate to spend 10 minutes revising their design based on the feedback.
• Observe how they incorporate the feedback and whether they can adapt their thinking to address new considerations.

Activity #3: Benefits Optimization Communication Role Play

This role play assesses a candidate's ability to explain complex AI-enhanced benefits concepts to non-technical stakeholders. It evaluates communication skills, benefits knowledge, and the ability to translate technical capabilities into business value.

Directions for the Company:

• Prepare a scenario where the candidate must explain a new AI-enhanced benefits optimization initiative to a group of department managers.
• Select 2-3 interviewers to play the roles of managers with different personalities (e.g., a skeptical finance manager, an enthusiastic HR manager, a technically challenged operations manager).
• Provide the candidate with a one-page brief on the AI benefits initiative 30 minutes before the role play.
• The brief should include technical details about the AI system, expected benefits, and implementation timeline.
• Prepare specific questions each "manager" will ask, including concerns about cost, employee privacy, and ease of use.

Directions for the Candidate:

• Review the provided brief about the AI-enhanced benefits optimization initiative.
• Prepare a 10-minute explanation of the initiative for department managers who have varying levels of technical knowledge.
• Your explanation should:

1. Clearly articulate how the AI system works in non-technical terms
2. Highlight specific benefits for employees and the organization
3. Address potential concerns proactively
4. Outline what managers need to know to support the initiative

• After your explanation, respond to questions from the managers, addressing their specific concerns.

Feedback Mechanism:

• Provide feedback on one communication strength (e.g., clear explanations, effective handling of objections) and one area for improvement (e.g., avoiding technical jargon, more concrete examples).
• Ask the candidate to re-explain one aspect of the initiative incorporating the feedback.
• Evaluate their ability to adapt their communication style and respond to feedback in real-time.

Activity #4: AI Benefits Implementation Project Planning

This activity evaluates a candidate's ability to plan and manage the implementation of an AI-enhanced benefits system. It tests project management skills, understanding of implementation challenges, and ability to coordinate cross-functional resources.

Directions for the Company:

• Create a scenario for implementing a new AI-enhanced benefits platform at a large organization.
• Include details about current systems, stakeholders, timeline constraints, and specific organizational challenges.
• Provide information about available resources (budget, team members, technology infrastructure).
• Allow candidates 60 minutes to develop their implementation plan.

Directions for the Candidate:

• Develop a comprehensive implementation plan for the AI-enhanced benefits platform described in the scenario.
• Your plan should include:

1. Key project phases and timeline
2. Required resources and team structure
3. Risk assessment and mitigation strategies
4. Change management and communication approach
5. Success metrics and evaluation methods

• Create a visual project roadmap showing major milestones and dependencies.
• Identify critical success factors and potential obstacles specific to AI implementation in benefits systems.
• Be prepared to explain your rationale for prioritization decisions and resource allocation.

Feedback Mechanism:

• Provide feedback on one strength of the implementation plan (e.g., comprehensive risk assessment, thoughtful change management approach) and one area for improvement (e.g., more realistic timeline, additional stakeholder considerations).
• Ask the candidate to revise one section of their plan based on the feedback.
• Evaluate their ability to incorporate feedback while maintaining the overall integrity of their implementation strategy.

Frequently Asked Questions

How long should we allocate for these work samples in our interview process?

These exercises vary in time commitment. Activity #1 requires 48 hours of preparation plus a 45-minute session. Activities #2 and #4 require approximately 60 minutes each, while Activity #3 needs about 45 minutes including preparation time. Consider spreading these across different interview stages or selecting the 1-2 most relevant to your specific role requirements.

Should we provide real company data for these exercises?

No, always use fictional or thoroughly anonymized data. Create realistic datasets that reflect typical patterns but don't contain any sensitive information. This protects your organization and avoids putting candidates in uncomfortable positions regarding data privacy.

What if candidates don't have deep technical AI knowledge but strong benefits expertise?

Adjust the technical depth of the exercises based on the specific role requirements. For positions that focus more on benefits strategy with AI support, emphasize the business application aspects rather than technical implementation details. The exercises can be modified to focus on how to leverage AI capabilities rather than how to build them.

How do we evaluate candidates consistently across these exercises?

Develop a structured scoring rubric for each exercise that aligns with the key competencies you're assessing. Include both technical and soft skill dimensions, and ensure all interviewers use the same criteria. Consider having multiple evaluators for each exercise to reduce individual bias.

Should we share these exercises with candidates in advance?

For Activities #1 and #4, providing advance notice is appropriate since they require significant preparation. For Activities #2 and #3, providing the general topic but not specific details allows you to assess how candidates think on their feet while still giving them a chance to mentally prepare.

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

Ensure exercises don't require specialized knowledge of specific AI tools unless absolutely necessary for the role. Focus on conceptual understanding and problem-solving approaches rather than familiarity with particular platforms. Offer reasonable accommodations for candidates who may need them, and be flexible with time constraints when possible.

AI-enhanced benefits selection and optimization represents a growing field that combines human resources expertise with advanced technology capabilities. By using these work samples, you can identify candidates who not only understand both domains but can effectively bridge them to create value for your organization and its employees. The right talent in this area can transform your benefits program from a standard offering to a strategic advantage in attracting and retaining top talent.

For more resources to enhance 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.

Build a complete interview guide for AI-Enhanced Benefits Selection and Optimization by signing up for a free Yardstick account