Artificial intelligence is increasingly finding its way into HR, offering employers new ways to analyze workplace complaints, identify employee relations trends, and streamline administrative tasks. But when AI enters sensitive areas such as disciplinary decisions, workplace investigations, and employee monitoring, the technology can create as many legal risks as operational benefits.
For HR professionals, the challenge is determining where AI can improve efficiency without compromising fairness, employee rights, or compliance with labor and employment laws. AI, in fact, can be particularly valuable in managing large volumes of employee relations information, provided employers maintain meaningful human oversight.
This article mentions using AI for Policy Drafting and Updates as well as for Classification and Triage of Employee Relations Cases. Discover 137 other AI use cases by visiting SHRM’s AI Field Manual for Employers: 138 Use Cases for AI at Work.
Where AI Can Help HR Teams
One of AI’s most promising applications is identifying patterns in workplace complaints and employee feedback that might otherwise go unnoticed.
“AI is most useful for high-volume, pattern-based work that humans then review,” said David Pryzbylski, an attorney with Barnes & Thornburg LLP in Indianapolis.
Potential applications include sorting employee complaints, analyzing exit interviews and engagement surveys, summarizing investigation files, and preparing preliminary disciplinary documentation.
For example, an employer receiving hundreds of hotline complaints across multiple locations could use AI to identify recurring concerns involving particular managers, departments, or workplace policies. Such insights could help HR teams address emerging problems before they escalate into formal grievances or litigation. AI can also assist with workplace investigations by organizing evidence, summarizing interviews, and preparing initial reports.
However, Pryzbylski emphasized that these functions should remain supportive rather than determinative. “Employers can use it responsibly to analyze complaints and support grievance investigations if it organizes the information while trained HR or labor relations staff make the judgments,” he said.
AI-generated documents also require careful review for factual accuracy, consistency with company policies and collective bargaining agreements, and potential attorney-client privilege concerns.
The Legal Risks of AI-Driven Decisions
Despite these advantages, employers face significant legal exposure when AI influences disciplinary actions, terminations, or workplace investigations. One major concern is employment discrimination, particularly when AI systems rely on historical workplace data that may reflect existing biases.
“The main risk likely is disparate impact discrimination under Title VII, the ADEA, and the ADA, plus state law,” Pryzbylski said.
For example, an AI system trained on past disciplinary decisions could perpetuate discriminatory patterns if certain employee groups historically received harsher penalties for comparable misconduct.
Meanwhile, employers cannot necessarily avoid liability by outsourcing the technology to a third-party vendor.
Retaliation presents yet another concern. AI systems that flag employees based on prior complaints, accommodation requests, protected leave, or other legally protected activities could expose employers to claims that subsequent adverse employment decisions were retaliatory.
Employers also face an evidentiary challenge if they cannot explain how an AI system reached its recommendation. An opaque algorithm may undermine an employer’s ability to demonstrate a legitimate, nondiscriminatory reason for its decision.
Additional obligations may arise under state and local AI regulations, including New York City's automated employment decision tool law and California’s employment discrimination regulations addressing automated decision systems.
Employee Monitoring and the National Labor Relations Act
AI-powered surveillance presents another particularly sensitive area, especially when employers use sentiment analysis or productivity monitoring to evaluate workplace communications.
Under section 7 of the National Labor Relations Act (NLRA), employees generally have the right to engage in protected concerted activity concerning wages, working conditions, and other employment matters. Section 8(a)(1) prohibits employers from interfering with those rights, including through unlawful surveillance or conduct creating the impression of surveillance.
“Sentiment analysis that flags discussions of pay, working conditions, ‘union,’ or group complaints is high-risk, because it effectively targets protected concerted activity,” Pryzbylski said. Such protections apply in unionized and nonunionized workplaces alike.
Employers could also face legal challenges if monitoring increases during union organizing campaigns or if AI-generated alerts lead to discipline for protected activity.
Further, in unionized workplaces, introducing new monitoring technologies may additionally trigger collective bargaining obligations.
Why Human Oversight Remains Essential
Perhaps the most important safeguard is ensuring AI never becomes the final decision-maker in sensitive employee relations matters.
“Human oversight should be real, informed, and documented: The reviewer must be able to question and override the AI’s output, not simply approve it,” Pryzbylski said.
That distinction is especially important when assessing employee credibility, investigating harassment or discrimination allegations, deciding disciplinary measures, or responding to accommodation requests. Such decisions require consideration of individual circumstances and context that automated systems may not adequately capture.
As Pryzbylski said, “AI may inform the process, but an accountable person must make and own every adverse decision.”
Building Safeguards Before Deployment
Employers considering AI for employee relations should establish governance procedures before deploying these tools. Pryzbylski recommends written policies identifying permitted and prohibited AI uses, confidentiality safeguards for sensitive employee information, and legal review of applicable state and local requirements.
Employers should also evaluate vendors, provide required employee disclosures, document the reasoning behind AI-assisted decisions, and establish appropriate record-retention procedures.
Regular discrimination-impact audits and reviews of employee monitoring practices can help identify emerging compliance concerns.
Ultimately, AI’s greatest value in employee relations may lie not in replacing HR professionals’ judgment, but in giving them better information to exercise it. Employers that treat the technology as an analytical assistant rather than an automated decision-maker will be better positioned to capture its benefits while limiting legal exposure.
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