AI Performance Management: Fair Reviews, Goals & Feedback

This course contains the use of artificial intelligence.

Artificial intelligence is changing how organizations set performance goals, prepare employee reviews, analyze workplace information, give feedback, and plan employee development. This course helps managers, leaders, supervisors, and human resources professionals use AI in performance management while preserving the fairness, privacy, context, and human judgment that consequential employee decisions require.

Rather than treating AI as an automated evaluator, you will learn how to integrate generative AI into performance management as a practical assistant for preparation, organization, analysis, feedback, and development—while recognizing where people must remain responsible for interpretation, judgment, and final decisions.

Build a Fair, Responsible and Practical Approach to AI Performance Management

By the end of this course, you will be able to:

• Use AI to improve performance goals and clarify employee expectations

• Prepare stronger, more evidence-based performance reviews with AI assistance

• Separate workplace observations and documented evidence from interpretations and unsupported assumptions

• Use AI to identify skills and employee development needs without allowing AI to determine an employee's potential

• Give clearer performance feedback that opens productive conversations

• Recognize bias and unsupported conclusions in AI-generated performance information

• Protect sensitive employee and workplace information when using generative AI

• Evaluate when workplace performance data is useful and when employee monitoring may become disproportionate surveillance

• Apply human judgment to consequential performance-management decisions

• Build a responsible human-AI workflow that keeps accountability and decision authority with people

Performance Management With AI Requires More Than Automation

AI can make parts of performance management faster. But faster analysis is not necessarily better judgment.

A well-written AI response can still contain assumptions. A performance metric can look objective while missing important context. Employee activity data can be available without being appropriate evidence. And an AI-generated performance review can sound confident without having enough information to support its conclusions.

That is why this course goes beyond teaching you how to generate goals, feedback, or performance-review language with AI.

You will examine the more important question: How should AI be used when the information may affect another person's performance, development, opportunities, or career?

Throughout the course, you will learn how to use generative AI while maintaining a balanced and unbiased approach to performance management. We will address ethical AI use, fairness, employee privacy, evidence quality, bias, verification, accountability, and the appropriate limits of automated analysis.

Learn AI-Assisted Goal Setting, Reviews, Feedback and Employee Development

We begin by looking at where AI belongs in performance management and where human judgment must lead.

You will then explore how clearer performance expectations and success measures create the foundation for fair evaluation, and how AI can help managers identify ambiguity, missing assumptions, possible measures, dependencies, and milestones before employees are held accountable for results.

From there, the course moves into performance evidence and feedback. You will learn why an observation, an interpretation, and an assumption are not the same thing—and why that distinction matters when reviewing employee performance.

You will also see how AI can support performance-review preparation, employee skills analysis, development planning, and more useful feedback conversations without becoming the evaluator.

Address AI Bias, Employee Privacy and Performance Monitoring

Responsible AI in performance management also requires knowing when not to use information simply because technology makes it available.

You will examine bias and unsupported AI conclusions, sensitive employee information, appropriate data minimization, and the increasingly important boundary between useful workplace performance information and employee surveillance.

The goal is not to avoid workplace data or AI. It is to use both proportionately, fairly, and with enough context to support responsible decisions.

Includes the Responsible AI Performance Management Toolkit

Your enrollment also includes the Responsible AI Performance Management Toolkit, courtesy of Pursuing Wisdom Academy and Crystal Hutchinson.

This practical downloadable resource is designed to help you move from learning to application. It includes manager-focused tools for evaluating performance evidence, preparing AI-assisted performance work, planning employee conversations, protecting sensitive information, and determining when human review and decision authority are required.

The toolkit also introduces the CLEAR Performance AI Check, a practical framework for considering context, legitimate evidence, employee data, appropriate AI assistance, and human responsibility before acting on AI-supported performance information.

It is designed to remain useful after you finish the course as a reference for real performance-management situations.

Designed for Managers, Leaders and Human Resources Professionals

This course is appropriate for:

• Managers responsible for employee performance

• Supervisors and frontline leaders

• Team leaders and people managers

• Human resources managers and professionals

• Department and operations leaders

• Learning and development and talent professionals

• Leaders responsible for introducing AI into people-management processes

• Professionals interested in responsible AI use in the workplace

You do not need a technical background, programming knowledge, or advanced AI experience. The course is designed for all levels and focuses on practical management decisions rather than technical AI development.

Learn From Pursuing Wisdom Academy

I am Crystal Hutchinson, founder of Pursuing Wisdom Academy.

Since launching Pursuing Wisdom Academy in 2018, I have had the privilege of teaching more than 100,000 students. My approach to AI education focuses not simply on what technology can do, but on how professionals can use it thoughtfully when human judgment, responsibility, and real-world consequences matter.

That perspective is especially important in performance management, where an efficient process is not enough. Employees deserve decisions based on relevant evidence, appropriate context, fair evaluation, and accountable human judgment.

Use AI to Strengthen Performance Management Without Surrendering Human Judgment

By the end of this course, you will have a practical framework for deciding where generative AI can improve performance management, where its outputs require verification, where privacy and fairness require additional care, and where the final decision must remain human.

If you are responsible for setting expectations, reviewing performance, giving feedback, developing employees, or deciding how AI should be incorporated into people-management processes, this course was designed for you.

Enroll now and learn how to use AI to make performance management more effective without allowing faster analysis to become a substitute for better judgment.