Effective Work Samples for Evaluating AI Deal Desk Automation Skills

Deal Desk automation through artificial intelligence represents a significant evolution in how organizations manage complex sales transactions. As companies increasingly adopt AI to streamline pricing approvals, contract analysis, and deal workflows, the need for professionals who can effectively implement and manage these technologies becomes critical. The intersection of sales operations expertise and AI implementation skills creates a unique talent profile that can be challenging to evaluate through traditional interview methods alone.

Work samples provide a window into how candidates approach real-world challenges in AI-powered Deal Desk environments. By observing candidates as they tackle practical scenarios, hiring managers can assess not only technical knowledge but also problem-solving approaches, process design thinking, and the ability to translate business requirements into technological solutions. These practical evaluations reveal how candidates balance efficiency with compliance, automation with human oversight, and technical implementation with business value.

The most effective Deal Desk AI specialists demonstrate a blend of sales operations knowledge, technical understanding, and strategic thinking. They must be able to identify opportunities for automation, design effective AI-enhanced workflows, and communicate complex technical concepts to stakeholders across sales, finance, legal, and executive teams. Work samples that simulate these challenges provide invaluable insights into a candidate's capabilities beyond what resumes and traditional interviews can reveal.

The following work samples are designed to evaluate candidates' abilities to implement AI solutions in Deal Desk operations across four key dimensions: process automation design, data analysis and optimization, technical implementation planning, and stakeholder communication. Each exercise simulates a realistic challenge that AI Deal Desk specialists commonly face, providing a comprehensive view of the candidate's readiness for the role.

Activity #1: Deal Approval Workflow Automation Design

This exercise evaluates a candidate's ability to design an AI-enhanced workflow for deal approvals—a core function of modern Deal Desks. Candidates must demonstrate understanding of both business processes and AI capabilities, showing how they would automate routine approvals while maintaining appropriate controls for complex or high-risk deals.

Directions for the Company:

• Provide the candidate with your current deal approval process documentation, including approval thresholds, required stakeholders, and common exceptions.
• Include sample deal data from 10-15 past deals (anonymized) with various characteristics (size, discount level, product mix, customer type).
• Allow 45-60 minutes for the candidate to complete the exercise.
• Have a whiteboard or digital drawing tool available for the candidate to sketch their proposed workflow.
• Ensure a technical team member and a business stakeholder are present to evaluate the response.

Directions for the Candidate:

• Review the current deal approval process and sample deal data provided.
• Design an AI-enhanced approval workflow that:
• Automatically routes straightforward deals for quick approval
• Flags deals requiring human review based on specific risk factors
• Learns from past approvals to improve future routing decisions
• Create a visual representation of your proposed workflow, clearly indicating where AI would be applied and how it would interact with human approvers.
• Explain what data points the AI would use to make routing decisions and how the system would improve over time.
• Be prepared to discuss how your solution balances efficiency with appropriate risk management.

Feedback Mechanism:

• After the candidate presents their solution, provide feedback on one aspect they handled well (e.g., "Your approach to exception handling was particularly thoughtful") and one area for improvement (e.g., "The solution could better address how to handle novel deal structures the AI hasn't seen before").
• Give the candidate 10 minutes to revise their approach based on the improvement feedback, focusing specifically on that aspect of the solution.
• Observe how receptive they are to feedback and how effectively they incorporate it into their revised solution.

Activity #2: AI-Driven Pricing Optimization Analysis

This exercise assesses the candidate's ability to leverage AI for data-driven decision making in pricing strategies—a key advantage of AI-enhanced Deal Desks. It tests analytical skills, business acumen, and the ability to translate complex data insights into actionable recommendations.

Directions for the Company:

• Prepare a dataset of historical deals (30-50 deals) including variables such as:
• Initial quote amount
• Final negotiated price
• Discount percentage
• Deal cycle length
• Customer size/industry
• Products/services included
• Win/loss outcome
• Include some anomalies and patterns in the data that aren't immediately obvious.
• Provide basic information about your current pricing strategy and business objectives.
• Allow 60 minutes for the candidate to analyze the data and prepare recommendations.
• Have a spreadsheet tool or basic data analysis platform available.

Directions for the Candidate:

• Analyze the provided deal data to identify patterns that could inform an AI-driven pricing optimization strategy.
• Identify at least three specific opportunities where AI could improve pricing decisions based on the patterns you observe.
• Create a brief proposal outlining:
• What pricing factors an AI system should consider
• How the system would make recommendations (e.g., discount ranges, bundling opportunities)
• What business rules should override AI recommendations
• How you would measure the effectiveness of the AI pricing system
• Prepare to present your findings and recommendations in a 10-minute presentation, focusing on business impact rather than technical details.

Feedback Mechanism:

• After the presentation, provide specific feedback on one strength (e.g., "Your identification of the relationship between deal size and optimal discount rate was insightful") and one area for improvement (e.g., "The proposal could better address how to handle pricing for new products with limited historical data").
• Ask the candidate to spend 10 minutes refining their approach to address the improvement area.
• Evaluate their ability to quickly adapt their thinking and incorporate new perspectives into their analysis.

Activity #3: Contract Analysis Automation Implementation Plan

This exercise evaluates the candidate's ability to plan the technical implementation of an AI solution for contract analysis—a complex but high-value application of AI in Deal Desk operations. It tests technical knowledge, project planning skills, and understanding of change management considerations.

Directions for the Company:

• Provide sample contracts (3-5) of varying complexity that represent typical deals your organization processes.
• Include a brief description of your current contract review process, key stakeholders, and common bottlenecks.
• Outline basic technical infrastructure information (e.g., CRM system, document management system, existing integrations).
• Allow 45-60 minutes for the candidate to develop their implementation plan.
• Have a technical team member available to answer infrastructure questions if needed.

Directions for the Candidate:

• Review the sample contracts and current process information provided.
• Develop a phased implementation plan for an AI-powered contract analysis system that would:
• Automatically identify and extract key terms and obligations
• Flag non-standard language or high-risk clauses
• Compare proposed terms against approved standards
• Accelerate the review process while maintaining compliance
• Your plan should include:
• Technical requirements and potential solutions/vendors
• Data requirements for training the AI system
• Integration points with existing systems
• Implementation timeline with key milestones
• Success metrics and evaluation approach
• Be prepared to discuss technical considerations as well as change management strategies for user adoption.

Feedback Mechanism:

• After the candidate presents their implementation plan, provide feedback on one strong element (e.g., "Your approach to phased implementation reduces risk effectively") and one area needing improvement (e.g., "The plan doesn't adequately address how to handle the transition period while the AI is still learning").
• Give the candidate 15 minutes to revise the specific aspect of their plan that needs improvement.
• Evaluate their technical knowledge, adaptability, and practical approach to implementation challenges.

Activity #4: Cross-Functional AI Solution Communication

This exercise assesses the candidate's ability to communicate complex AI concepts to diverse stakeholders—a critical skill for driving adoption of AI Deal Desk solutions. It tests communication skills, stakeholder management, and the ability to translate technical capabilities into business benefits.

Directions for the Company:

• Create role cards for four stakeholders with different perspectives:

1. Sales Director (concerned about anything that might slow down deals)
2. Legal Counsel (focused on risk management and compliance)
3. Finance Leader (interested in margin protection and forecasting)
4. IT Manager (concerned about integration and security)

• Assign team members to play these roles during the exercise.
• Provide a one-page description of a fictional AI Deal Desk automation initiative that would affect all stakeholders.
• Allow 30 minutes for preparation and 20 minutes for the role-play meeting.

Directions for the Candidate:

• Review the AI initiative description provided.
• Prepare a brief presentation (5-7 minutes) explaining the initiative to the cross-functional team.
• Your presentation should:
• Clearly explain how the AI solution works in non-technical terms
• Address the specific concerns and benefits for each stakeholder
• Outline the implementation approach at a high level
• Propose a collaborative governance model for the solution
• After your presentation, facilitate a 15-minute discussion with the stakeholders, addressing their questions and concerns.
• Your goal is to build consensus and support for the initiative while acknowledging legitimate concerns.

Feedback Mechanism:

• After the role-play, provide feedback on one communication strength (e.g., "You effectively translated technical concepts into business benefits") and one area for improvement (e.g., "You could have better addressed the specific concerns of the Legal Counsel").
• Give the candidate 10 minutes to prepare a follow-up email to the stakeholder whose concerns were not adequately addressed.
• Evaluate their ability to tailor communication to specific audiences and address objections constructively.

Frequently Asked Questions

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

Each exercise requires approximately 60-90 minutes including preparation, execution, feedback, and revision time. We recommend selecting 1-2 exercises most relevant to your specific needs rather than attempting all four in a single interview cycle. The Contract Analysis Implementation Plan and Deal Approval Workflow exercises are particularly effective for candidates who will be directly implementing AI solutions.

Should we provide these exercises as take-home assignments or conduct them in person?

The Deal Approval Workflow and Pricing Optimization exercises can work well as take-home assignments with a follow-up presentation. However, the Cross-Functional Communication exercise is most effective when conducted in person or via video conference with role players. The Contract Analysis Implementation exercise can work either way, depending on your preference for observing the candidate's working process versus evaluating their final output.

How should we evaluate candidates who have strong business knowledge but limited AI experience?

Focus on their problem-solving approach and ability to conceptualize how AI could enhance existing processes. In the feedback portion, observe how quickly they grasp AI concepts when introduced. Strong candidates with business expertise but limited AI experience will demonstrate curiosity about the technology and ask insightful questions about capabilities and limitations.

What if our organization is just beginning to explore AI for Deal Desk operations?

These exercises are still valuable for identifying candidates who can grow with your AI initiatives. Focus on the Deal Approval Workflow and Cross-Functional Communication exercises, which test fundamental skills in process design and stakeholder management. Look for candidates who propose practical, incremental approaches rather than unrealistic transformations that require advanced AI capabilities your organization may not yet have.

How should we adapt these exercises for remote interviews?

For remote interviews, provide materials at least 24 hours in advance and use collaborative tools like Miro, Lucidchart, or Google Sheets to enable visual collaboration. For the Cross-Functional Communication exercise, ensure stakeholder role players have their cameras on and are introduced properly. Consider recording sessions (with permission) to allow multiple team members to evaluate the candidate's performance.

Can these exercises be scaled down for more junior positions?

Yes, for junior positions, simplify the exercises by providing more structure. For example, in the Deal Approval Workflow exercise, provide a template workflow and ask candidates to identify specific points where AI could be applied. For the Pricing Optimization exercise, narrow the dataset and provide more specific questions to guide their analysis.

The integration of AI into Deal Desk operations represents a significant opportunity for organizations to increase efficiency, improve decision-making, and enhance the overall sales process. By using these work samples to evaluate candidates, you can identify professionals who not only understand the technical aspects of AI implementation but also appreciate the business context and change management challenges involved in successful automation initiatives.

Finding the right talent to lead your AI Deal Desk transformation requires looking beyond traditional qualifications to assess practical skills in action. These exercises provide a window into how candidates think, solve problems, and communicate—all critical factors for success in this evolving field. By incorporating practical work samples into your hiring process, you'll build a team capable of delivering on the promise of AI-enhanced Deal Desk operations.

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