The Rise of AI-Assisted Workplace Complaints: What HR Needs to Know

A new challenge has emerged for HR: Employees are filing internal workplace complaints that read like legal documents. 

Not long ago, such complaints were relatively straightforward: An employee raised a concern and expected HR to address it. Now, many employees use AI tools to research employment laws and workplace rights, then draft grievances that look more like legal filings than employee concerns.  

HR teams are already seeking guidance on how to respond to these types of complaints, says Matthew Gizzo, a shareholder in Ogletree Deakins’ New York and Dallas offices and co-chair of the firm’s Technology Practice Group. AI-assisted workplace complaints are prompting HR to rethink how they identify and manage potential legal risks.

AI-Assisted Workplace Complaints Are Reaching HR

While employees don’t always disclose that they used AI, HR is increasingly seeing complaints with structure and legal framing that suggest generative AI played a role in drafting them. For example, employees may cite statutes, outline detailed timelines or include specific demands for remedies instead of simply describing a workplace concern.

This shift is creating two practical risks for employers, Gizzo says.

First, workplace complaints are becoming harder to dispose of. AI tools give employees immediate drafting support, helping them produce more focused and credible claims, he points out. In some cases, facts may be embellished, making it more difficult for HR to separate fact from fiction, increasing the need for deeper investigation.

Second, employees may be exposing sensitive company information in the process. When drafting complaints, employees may input internal documents or details into public AI tools, creating potential confidentiality and privacy risks.

Together, these risks don’t just affect how workplace complaints are written. They change what it takes to respond to them. The risk is less the complaint itself and more the downstream burden: verification, documentation and legal exposure. Even thin allegations require follow-up.  

In some cases, AI‑assisted complaints signify that an employee may already be thinking beyond HR. The same AI tools make it easier to file lawsuits without hiring an attorney. 

Why This Legal Trend Is Emerging Now

As layoffs and reorganizations become more common, employees are increasingly on edge and scrutinizing how employers treat them. Economic uncertainty has many looking closely at pay, benefits and accommodations, sometimes spotting issues they might not have questioned before. 

At the same time, generative AI is putting powerful tools in everyone’s hands. As employees become more comfortable using AI at work, many are also applying those same skills to research workplace rights and shape how they raise concerns with HR. 

This combination – motivated employees plus AI access – is lowering the barrier for workers to write detailed workplace complaints and then pursue legal claims without hiring an attorney.   

AI doesn’t just provide information; it removes the intimidation barrier that historically kept employees from framing workplace complaints in legal terms. Employees can now sound like a lawyer without hiring one.

How AI Is Changing Pro Se Litigation

When individuals represent themselves in court rather than hiring an attorney, they’re known as “pro se litigants.” Traditional pro se filings often lacked formal legal structure or precise citations, even when lengthy. 

Gizzo notes that generative AI is already having a significant impact, with self‑represented employees using it to prepare more polished complaints. “We are definitely seeing better lawsuits and better ‘lawyering’ from pro se plaintiffs as a result of AI,” he said.

Courts are beginning to see pro se complaints that are unusually detailed for self‑represented filings, sometimes containing legal arguments built on fabricated or misapplied case citations. 

Research helps explain why: A 2024 Stanford study found large language models handling legal queries hallucinate 69% to 88% of the time and tend to reinforce incorrect legal assumptions without awareness of their errors.

Recent federal cases show how AI-assisted — or AI-influenced — filings are reshaping pro se litigation and increasing the burden to employers, even when claims fail.     

Retaliation Complaint Includes Nonexistent Case Law Citation

In Davis v. American Airlines, a pro se litigant filed a lawsuit alleging her employer retaliated against her for filing a previous EEOC charge. Moreover, she filed “at least four complaints,” requiring her employer to file repeated motions to dismiss. 

The employee used formal legal terminology and structured damage calculations more typical of attorney‑drafted complaints. For example, she alleged that her manager “falsif[ied] documentation on [her] record and more events past and current which will be available during discovery.” She also calculated that she was owed $269,000 in back pay and requested “[f]ront pay if reinstatement is not feasible.” But one court filing also included a nonexistent case law citation.

Over eight months, the employee filed “baseless” motions and was warned that she “was risking sanctions by ignoring court orders,” the court noted. 

On Feb. 17, the court granted American Airlines’ motion to dismiss and instructed the clerk of court to close the case.

Sexual Harassment Claim Relied on Hallucinated Citations

In Jones v. Target Corp., a pro se litigant filed a sexual harassment lawsuit against Target, alleging harassment occurred in an employee breakroom in 2023. Among other things, the employee refused to show up for in-person depositions, refused to be recorded during depositions due to his “personal spiritual beliefs,” and presented questionable medical documentation to excuse his unwillingness to cooperate with the court.

The case dragged on for more than two years, during which time the employee “filed baseless motions, withheld basic discovery and relied on ‘hallucinated’ case citations,” according to the court. 

Ultimately, Target filed a motion asking the court to terminate sanctions against the employee and dismiss the case.  

A federal magistrate judge recommended granting Target’s motion on Feb. 18.

Repeated Use of Hallucinated Case Citations in ERISA Dispute

In Dixon v. MultiCare Health System, a pro se litigant filed an ERISA lawsuit against his employer, asserting claims for recovery of “benefits due” and breach of fiduciary duty.

According to the employee, administrative errors at the time of his hiring prevented him from opting out of automatic enrollment in the employer’s 401(k) plan. His suit sought reimbursement of wages deposited to his 401(k) account, double damages and attorneys’ fees. 

While there is no formal rule against using generative AI to write court filings, parties are obligated “to certify that their ‘legal contentions are warranted by existing law,’” the court explained. It warned the employee that repeated use of hallucinated case citations may result in monetary sanctions.

On March 4, the court granted the employer’s motion to compel arbitration and stayed Dixon’s ERISA claims pending arbitration. The case continues.

AI‑Assisted Workplace Complaints: HR Takeaways

AI‑assisted workplace complaints make it easier for self‑represented employees to generate lengthy filings and submit repeated motions, forcing employers to respond through counsel each time. Even where claims lack merit, the volume, structure, and frequency of these filings can compel prolonged procedural responses.

For HR, the takeaway is to treat detailed, AI‑assisted internal complaints as potential previews of pro se litigation: Recognize them early, coordinate quickly with legal and shore up documentation so you aren’t blindsided if the employee files in court. 

Signs a Workplace Complaint May Escalate

Certain patterns in how a complaint is structured, revised or supported could signal that an employee is building a legal case, not just asking HR to fix a workplace issue. 

• Early legal framing in complaints
  Example: An employee emails HR, citing specific statutes like FMLA or FLSA instead of simply describing a workplace concern – a sign the issue could move quickly from internal complaint to legal claim. 
• Structured, detailed timelines
  Example: Submitting workplace complaints that include multi-page documents listing meetings, emails and workplace interactions over weeks or months, which may indicate an employee is organizing evidence for a potential claim.
• References to precedent or legal standards
  Example: Workplace complaints that cite established case law to argue that workplace decisions were unlawful.
• Repeated revisions expanding allegations
  Example: An initial complaint about one incident is followed by subsequent versions adding departments, managers, or related events, which can quickly expand the scope and complexity of the dispute.
• Formal, highly structured demands for remedies
  Example: Letters requesting back pay, reinstatement or policy changes, written like a legal demand letter rather than a workplace complaint.
• Requests for extensive employment records or documentation
  Example: Employees request all HR files, emails and policy documents, suggesting they’re gathering a complete record of events rather than just checking on one issue.

Policy and Governance Questions for HR

As this trend grows, think about how HR should manage AI-generated content in workplace complaints.  

• Define expectations for HR’s AI use. Set guardrails on whether HR may use AI to summarize or draft responses to employee complaints. Require human verification of any legal‑sounding content before it goes to employees. Consider the risk of losing attorney-client privilege when legal strategy is discussed with third-party AI tools.   
• Acknowledge and clarify AI use by employees. Make it clear that if employees use AI to draft workplace complaints, they’re responsible for ensuring all submissions are accurate and truly reflect their own experience. 
• Train HR to spot AI red flags. Prioritize verifiable inconsistencies over writing style, including nonexistent or misapplied legal citations, timelines that conflict with known records, repeated template-like phrasing, and requests (or demands) for remedies that don’t align with the alleged harm.   
• Coordinate on AI-generated content. Work with counsel to determine how HR will review and respond to workplace complaints that appear to include AI‑generated content.

HR Action Steps

Early Preventive Measures

• Ensure managers clearly document discipline, investigations and termination decisions.
• Review complaint-handling processes for consistency.
• Train HR staff to recognize workplace complaints that begin to reference statutes or legal standards.

Mid-Level Interventions

• Monitor repeated revisions of employee complaints or expanded allegations.
• Conduct internal fact-finding to clarify disputed events and maintain accurate records.
• Escalate internally when employee communications show legal framing or structured timelines.

High-Alert Interventions

• Promptly notify legal counsel when workplace complaints suggest potential claims or formal demand letters appear.
• Coordinate with legal counsel to respond to employee requests for records.
• Conduct follow-up and targeted mitigation to manage escalating disputes.

As AI makes it easier for employees to submit detailed complaints, the employers best positioned to respond will be the ones that spot the warning signs and treat internal workplace complaints as potential lawsuits from the start.