Effective Work Samples for Evaluating Cross-Functional AI Project Collaboration Skills

In today's AI-driven business landscape, the ability to collaborate effectively across functional boundaries has become a critical skill. AI projects rarely succeed in isolation—they require seamless coordination between data scientists, engineers, product managers, business stakeholders, and end users. Candidates who excel at cross-functional AI collaboration can bridge technical and business worlds, translate complex concepts for diverse audiences, and navigate the unique challenges that arise when implementing AI solutions.

Traditional interviews often fail to reveal a candidate's true collaborative abilities in AI contexts. While candidates may claim strong cross-functional skills on their resumes, these claims are difficult to verify through conversation alone. Work samples and role plays provide a window into how candidates actually perform in realistic scenarios, revealing their communication style, technical translation abilities, stakeholder management approach, and problem-solving methods.

The complexity of AI projects creates unique collaboration challenges that require specific skills. Technical team members must explain complex concepts to non-technical stakeholders. Business leaders must articulate requirements in ways that technical teams can implement. Project managers must coordinate across disciplines with different vocabularies, priorities, and working styles. Effective work samples should evaluate these nuanced abilities.

By implementing the following exercises, you'll gain valuable insights into how candidates navigate the intricate dynamics of cross-functional AI collaboration. These activities simulate real-world scenarios that AI professionals encounter when working across departmental boundaries, providing a much clearer picture of a candidate's capabilities than traditional interview questions alone.

Activity #1: AI Project Kickoff Facilitation

This role play evaluates a candidate's ability to facilitate a critical meeting between technical and non-technical stakeholders at the beginning of an AI project. Effective cross-functional collaboration starts with establishing shared understanding, aligning expectations, and creating a foundation for ongoing communication. This exercise reveals how candidates bridge knowledge gaps and create alignment across diverse perspectives.

Directions for the Company:

• Set up a 20-minute role play where the candidate facilitates a kickoff meeting for a new AI project.
• Assign 2-3 interviewers to play different stakeholder roles: a technical lead (data scientist/ML engineer), a business stakeholder (department head/executive), and optionally a product manager.
• Provide the candidate with a brief on the fictional AI project 24 hours in advance, including:
• Project goal (e.g., implementing a customer churn prediction model)
• Key stakeholders and their primary concerns
• Known challenges or constraints
• Expected timeline and resources
• Instruct role players to embody realistic stakeholder concerns: technical feasibility, business impact, timeline expectations, data availability, etc.
• Observe how the candidate manages different perspectives and establishes a collaborative foundation.

Directions for the Candidate:

• Review the project brief and prepare to facilitate a 20-minute kickoff meeting.
• Your goal is to establish a shared understanding of the project, align expectations, and set the foundation for successful cross-functional collaboration.
• During the meeting, you should:
• Ensure all stakeholders understand the project goals and scope
• Address concerns from both technical and business perspectives
• Establish a common vocabulary for discussing the project
• Identify potential challenges and initial steps for addressing them
• Outline next steps and communication protocols
• Be prepared to translate technical concepts for business stakeholders and business requirements for technical team members.

Feedback Mechanism:

• After the role play, interviewers should provide feedback on one aspect the candidate handled effectively and one area for improvement.
• The candidate will then have 5 minutes to reflect on the feedback and explain how they would adjust their approach if they could redo a portion of the meeting.
• Evaluate both the candidate's initial performance and their receptiveness to feedback.

Activity #2: AI Implementation Planning Exercise

This exercise assesses a candidate's ability to develop a comprehensive cross-functional plan for implementing an AI solution. Planning is where collaboration frameworks are established, dependencies are identified, and potential friction points are addressed proactively. This activity reveals how candidates think about orchestrating work across different functions and anticipate collaboration challenges.

Directions for the Company:

• Provide the candidate with a case study of an AI implementation scenario, such as:
• Deploying a recommendation engine across multiple product lines
• Implementing an AI-powered forecasting tool for the finance department
• Integrating a natural language processing solution into customer service operations
• Include details about the organization structure, key stakeholders, technical environment, and business objectives.
• Give the candidate 30-45 minutes to develop an implementation plan.
• Provide access to a whiteboard or digital collaboration tool for creating their plan.
• Prepare questions to probe their thinking about cross-functional dependencies and collaboration mechanisms.

Directions for the Candidate:

• Review the AI implementation scenario and develop a cross-functional implementation plan.
• Your plan should include:
• Key phases and milestones
• Cross-functional team structure and roles
• Communication and collaboration protocols
• Decision-making frameworks
• Risk management approach, particularly for cross-functional risks
• Success metrics from both technical and business perspectives
• Be prepared to present your plan in 10 minutes, focusing on how you've designed it to facilitate effective cross-functional collaboration.
• After presenting, you'll answer questions about your approach and rationale.

Feedback Mechanism:

• Interviewers should provide feedback on one strength of the implementation plan and one area that could be improved from a cross-functional collaboration perspective.
• The candidate will have 5-10 minutes to revise one section of their plan based on the feedback.
• Evaluate both the initial plan and how thoughtfully the candidate incorporates feedback.

Activity #3: Technical-to-Business Translation Exercise

This exercise evaluates a candidate's ability to translate complex AI concepts and technical information into business-friendly language. Effective cross-functional collaboration requires bridging knowledge gaps and ensuring all stakeholders can participate meaningfully in discussions. This activity reveals how candidates adapt their communication to different audiences while maintaining accuracy.

Directions for the Company:

• Prepare a technical AI document that would typically be created by data scientists or ML engineers, such as:
• A model performance report with metrics and visualizations
• A technical explanation of an algorithm being considered for implementation
• A data quality assessment with technical findings
• Provide the candidate with this document and ask them to prepare a business-friendly explanation.
• Optionally, provide a brief on the fictional business stakeholders who will receive this information, including their roles, technical background, and key concerns.
• Allow 20-30 minutes for preparation.

Directions for the Candidate:

• Review the technical AI document provided.
• Prepare a 5-7 minute presentation or written summary that translates this technical information for business stakeholders.
• Your translation should:
• Maintain technical accuracy while using accessible language
• Focus on business implications and value
• Address potential questions or concerns from non-technical stakeholders
• Include appropriate visualizations or analogies that make concepts more understandable
• Highlight decision points or recommendations in business terms
• Be prepared to explain your translation choices and how you decided what to emphasize or simplify.

Feedback Mechanism:

• Interviewers should provide feedback on one effective aspect of the translation and one area where the business relevance or clarity could be improved.
• The candidate will have 5 minutes to revise a portion of their translation based on the feedback.
• Evaluate both the initial translation and the candidate's ability to incorporate feedback effectively.

Activity #4: AI Project Stakeholder Alignment Role Play

This role play assesses a candidate's ability to navigate conflicting priorities and perspectives in an AI project. Cross-functional collaboration often involves reconciling different departmental goals, timelines, and success metrics. This exercise reveals how candidates build consensus, manage tensions, and find solutions that address diverse stakeholder needs.

Directions for the Company:

• Create a scenario where an AI project is facing stakeholder alignment challenges, such as:
• The data science team wants more time for model refinement, while business stakeholders are pushing for faster deployment
• Legal/compliance has raised concerns about an AI solution that product and engineering teams are eager to launch
• Different departments have conflicting requirements for an AI tool that will serve multiple functions
• Assign 2-3 interviewers to play stakeholders with conflicting perspectives.
• Provide the candidate with a brief overview of the situation 24 hours in advance, including project background and stakeholder positions.
• The role play should last 20-25 minutes.

Directions for the Candidate:

• Review the scenario information provided.
• Prepare to facilitate a discussion between stakeholders with conflicting priorities or perspectives regarding an AI project.
• Your goal is to:
• Ensure all perspectives are heard and understood
• Identify underlying interests beyond stated positions
• Find areas of potential compromise or creative solutions
• Build consensus around a path forward that addresses key concerns
• Document agreed-upon next steps and responsibilities
• During the role play, demonstrate techniques for managing tension, building trust across functions, and creating alignment without authority.

Feedback Mechanism:

• After the role play, interviewers should provide feedback on one effective stakeholder management technique the candidate used and one approach that could be improved.
• The candidate will have 5 minutes to reflect on the feedback and explain how they would handle a specific moment in the conversation differently.
• Evaluate both the candidate's initial stakeholder management approach and their receptiveness to feedback.

Frequently Asked Questions

How much time should we allocate for these cross-functional AI collaboration exercises?

Most of these exercises require 45-60 minutes total, including setup, execution, feedback, and candidate response to feedback. The AI Implementation Planning Exercise may require slightly longer (60-75 minutes) to allow adequate time for plan development. Consider spreading these activities across different interview sessions rather than attempting multiple in a single interview.

What if we don't have interviewers with both technical and business backgrounds to participate in the role plays?

While having interviewers with diverse backgrounds is ideal, you can prepare non-technical interviewers with scripts and key talking points to simulate technical stakeholders, and vice versa. Provide them with common questions or concerns that stakeholders in those roles typically raise. The focus is on the candidate's collaboration approach rather than the technical depth of the conversation.

How should we adapt these exercises for candidates with different levels of experience?

For more junior candidates, simplify the scenarios and focus on fundamental collaboration skills like clear communication and active listening. For senior candidates, increase the complexity by adding more stakeholders, introducing organizational politics, or including global/cross-cultural elements. Adjust expectations for the sophistication of solutions based on experience level.

Can these exercises be conducted remotely?

Yes, all of these exercises can be adapted for remote interviews. Use video conferencing with breakout rooms for role plays, collaborative online tools like Miro or Google Jamboard for planning exercises, and screen sharing for presentations. Send materials in advance and ensure candidates have the necessary technology access.

How do we ensure these exercises don't disadvantage candidates from different backgrounds?

Provide clear instructions and background materials well in advance. Avoid industry-specific jargon or examples that might be familiar only to candidates from certain backgrounds. Focus evaluation on collaboration approaches and adaptability rather than prior knowledge of specific AI applications. Consider offering a brief pre-exercise call to answer questions about the format.

Should we use real company projects as the basis for these exercises?

Using simplified versions of real projects can make the exercises more relevant, but be careful about confidentiality. Create fictional scenarios inspired by real challenges your organization has faced, changing specific details while maintaining the core cross-functional dynamics. This approach tests relevant skills without exposing sensitive information.

Cross-functional collaboration is the backbone of successful AI implementation. By incorporating these work samples and role plays into your interview process, you'll gain valuable insights into how candidates navigate the complex human dynamics of AI projects. These exercises reveal abilities that traditional interviews often miss: translating technical concepts, aligning diverse stakeholders, planning across functional boundaries, and building bridges between different organizational languages and priorities.

Remember that the most successful AI initiatives aren't just technically sound—they're built on a foundation of effective cross-functional collaboration. By evaluating these skills thoroughly during your hiring process, you'll build teams capable of turning AI potential into business reality.

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

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