The appeal to business leaders and HR executives is convincing: shifting from the traditional annual review to a real-time, data-driven feedback system for employee growth.

When implemented properly, AI can boost engagement, reduce bias, and cut down on unnecessary bureaucracy.

However, new legal risks and responsibilities arise as this technology quickly advances.

When your company considers adopting AI-based tools, proceed carefully and adopt a strategic legal approach. Threats like algorithmic bias, data privacy violations, and lack of transparency require proactive and careful management.

The Advantages of AI-driven Performance Feedback

AI offers significant improvements over traditional performance management methods.

Continuous, Real-Time Feedback

Instead of outdated, annual reviews, AI systems can offer ongoing feedback by analyzing performance data from various sources like project management software, collaboration tools, and time-tracking data. This enables employees to make adjustments immediately and feel more engaged.

Less Bias Because of Factual Data

AI can help reduce human prejudices, like recency bias (ignoring past events) or affinity bias (favoring the “in-group”). AI allows for more objective and fair decisions by focusing on measurable terms and spotting biased language in comments.

Motivated Employees Improve Performance

Personalized, data-driven feedback can greatly increase staff satisfaction and motivation. Research shows that employees who get regular, individual feedback are more motivated than those who only receive annual reviews.

Increased Productivity

AI can assist managers with bureaucratic tasks like data collection and report writing for performance reviews, allowing them to focus on more meaningful, people-centered conversations with their team members.

Navigating the Legal Landscape and Managing Risk

While the benefits are evident, the legal risks of using AI for employment decisions are equally important. The U.S. Equal Employment Opportunity Commission (EEOC) and other government agencies closely oversee AI in HR to ensure adherence to civil rights laws. 

Primary legal considerations and strategies to reduce risk include the following:

1. Limit Algorithmic Bias

• Use representative and inclusive data. Algorithms are only as good as the training data they receive. Ensure your AI models are trained on diverse and representative datasets to prevent reinforcing historical biases.

• Conduct regular audits of your AI system’s output to detect bias. Make sure the AI isn’t unfairly affecting a specific protected group, and modify the model as needed.

• Augment with human oversight. Keep in mind, AI is meant to assist, not replace, human judgment. Checks and balances controlled by humans are essential to ensure fairness and avoid over-reliance on potentially biased AI suggestions.

2. Safeguard Data Confidentiality and Compliance

• Be transparent with employees. With data privacy laws in place that give employees in some states the right to know what personal data is collected and how it’s used, review your employee handbook and policies to clearly specify AI use in performance management.

• Limit data processing. Adhere to the “data minimization” principle and only process the data necessary for the AI’s specific purpose.

• Conduct a data protection impact assessment. Before deploying a new AI system, carry out a comprehensive risk evaluation to identify potential privacy risks and ensure compliance with relevant laws.

3. Have Transparency and Explainability

• Clearly define the purpose of AI. Be open with your team about how AI assists in the performance review process. Explain what data is used and how the AI delivers feedback.

• Provide a clear explanation. The “black box” nature of some AI systems can make decisions seem as if they are random. Organizations must be prepared to clearly explain how an AI system reached a particular conclusion, especially if an employee questions a decision.

Actionable Steps for the Implementation of AI into Your Performance Management Process

To effectively and legally incorporate AI into your performance management process, follow these steps:

1. Set your goals. Before choosing a vendor, determine what you want AI to achieve. Do you want AI to automate administrative tasks, offer more consistent feedback, or reduce bias?
2. Thoroughly evaluate AI tools. Investigate potential AI vendors and review their features, integration options, data security measures, and compliance standards.
3. Create a clear AI policy. Develop a company policy for the ethical use of AI across HR. The policy should address data privacy and include human oversight.
4. Invest in manager training. Train managers to become proficient in using AI tools and interpreting AI-based insights. Manager training should also include delivering feedback with emotional intelligence, understanding context, and maintaining a caring touch in performance conversations.
5. Create a feedback loop. Develop a continuous process where employees can share their comments on the new AI system. This will help you monitor its effectiveness and foster employee trust.

Conclusion

AI-enabled performance management creates a better, more unbiased, and engaging work environment. However, the process involves legal and business challenges.

By taking the lead on addressing bias, privacy, and transparency, and using AI to support — not replace — human judgment, organizations can unlock their workforce’s full potential while developing a strong, compliant talent management strategy.

Disclaimer: This client alert is for informational purposes only and is not legal advice. Please consult your attorney for specific guidance regarding your company’s use of AI tools.