As artificial intelligence continues its rapid integration into nearly every corner of our professional lives, it’s no surprise that AI tools are now being pitched as solutions for one of the more sensitive and complex functions in schools and workplaces: investigations.
Whether it’s a Title IX inquiry at a university, a harassment claim in a work setting, or a student-on-student misconduct report, investigations require precision, neutrality, and discretion. AI promises to streamline these processes, but does it really help – or does it risk doing more harm than good?
This article explores the emerging role of AI in workplace and school investigations, highlighting both its potential and its perils.
The Upside of AI
Large Language Model
A large language model (LLM) is a type of artificial intelligence trained on massive amounts of text data to recognize patterns in language and generate human-like responses. One key advantage of incorporating AI—particularly large language models—into workplace and school investigations is the ability to communicate with the technology in plain English. Unlike traditional software tools that require complex queries or programming knowledge, AI-powered systems understand and respond to natural language prompts. This means investigators can ask nuanced questions, generate interview outlines, analyze witness statements, or synthesize case law using everyday language. By streamlining processes, AI tools can enhance investigators’ efficiency. Instead of acting as an obstacle, the technology becomes an extension of the investigator’s analytical toolkit, enabling them to focus more on critical thinking and decision-making.
Interview Preparation
AI can also be a powerful tool in helping investigators prepare for interviews by facilitating the development of tailored and focused questions. By analyzing a variety of available case materials—such as complaint narratives, prior statements, emails, and policies—AI can assist in identifying key themes, detecting inconsistencies, and highlighting areas that warrant further clarification. Investigators can use this analysis to generate precise and targeted interview questions, organized by topic or timeline, and tailored to each witness or subject. This level of preparation not only improves the quality and focus of interviews but also helps ensure that critical issues are addressed efficiently and thoroughly, reducing the risk of overlooking important details.
Organizing Information
Another significant advantage of using AI in workplace and school investigations is its ability to extract relevant information from raw, unstructured notes and organize it into a coherent and chronological narrative. Investigators often work with scattered data— digital notes, emails, interview transcripts—and manually analyzing this data and piecing together timelines can be time-consuming and prone to omission. AI tools can quickly sift through large volumes of text; identify key dates, events, and individuals; and arrange the information in a logical sequence. This not only saves time but also enhances clarity, helping investigators spot patterns, gaps, or inconsistencies in the record that might otherwise be missed.
Drafting Reports
AI also offers a valuable advantage in the drafting and revision stages of investigative work by helping refine and rewrite sentences and paragraphs with speed and precision. Whether preparing interview summaries, articulating findings, or composing sensitive communications, investigators often face the challenge of expressing complex or nuanced information in a clear and professional manner. AI-powered writing tools can suggest alternative phrasings, improve grammar and tone, and tailor content to the fit the intended audience—all while preserving the original intent and meaning of the message. This support not only enhances the quality and readability of written work but also helps reduce drafting time, allowing investigators to focus more on analysis and decision-making.
Potential Perils of AI
Hallucinations
One of the most serious downsides of using AI in investigations is the risk of AI-generated “hallucinations,” where the technology generates outputs that sound confident but are actually false or misleading. Large language models occasionally produce information that appears credible but is factually inaccurate or entirely fabricated. In the context of workplace and school investigations, where decisions can have significant legal and reputational consequences, relying on inaccurate information can undermine the integrity of the process and lead to faulty conclusions with potentially severe consequences. Investigators must remain vigilant, verifying all AI-generated content against original sources and treating AI as a tool to support, not replace, professional judgment and critical analysis.
Algorithmic Bias and Training Data Issues
Another significant concern when integrating AI into workplace and school investigations is the risk of algorithmic bias, which can skew outcomes and perpetuate existing inequalities. This issue arises because AI systems are trained on historical data that may reflect societal prejudices—such as biases related to race, gender, or socioeconomic status—and can inadvertently replicate these patterns in their analyses.
For instance, facial recognition technologies have demonstrated higher error rates when identifying individuals with darker skin tones, particularly women, due to underrepresentation in training datasets. Similarly, AI tools used in hiring or disciplinary contexts can favor people from certain educational backgrounds or geographic regions, unintentionally disadvantaging others.
In investigative settings, such biases can lead to unfair treatment of witnesses or subjects, misinterpretation of evidence, and flawed conclusions. To counteract these risks, investigators must critically evaluate AI outputs, ensure diverse and representative training data, and apply consistent human oversight to mitigate the risk of discrimination and maintain the integrity of the investigative process.
Time-Saving Illusion
While AI can be a valuable tool in streamlining aspects of workplace and school investigations, its time-saving benefits are not always straightforward. Since AI-generated materials, such as summaries, analysis, or drafted questions, often require thorough review and double-checking, the time spent on these tasks may negate some of the efficiency gains. Investigators must carefully validate the accuracy, relevance, and tone of AI-generated content, especially considering the risk of errors or misinterpretations. In some cases, this added layer of oversight could actually slow down the process, as investigators balance using AI to assist with tasks while still maintaining their role as the final decision-makers and quality controllers. While AI can support investigative work, it doesn’t fully replace the need for careful human review and critical thinking.
Lack of Transparency in Privacy Policies
Finally, another consideration when adopting AI into an investigations practice is that privacy policies surrounding these tools are often not fully transparent. Many AI platforms collect vast amounts of data, but the details of how this data is stored, shared, or used are sometimes unclear. This lack of transparency can pose significant risks, especially when handling sensitive, privileged, or confidential information in workplace and school investigations. Investigators must carefully scrutinize whether the AI provider’s privacy practices align with legal and ethical standards, as well as assess the potential for data breaches or misuse. Without a clear understanding of privacy policies, investigators may inadvertently expose sensitive data to third parties, jeopardizing the trust and integrity of the investigative process.
Best Practices for Using AI in Investigations
- Use AI as a triage or support tool, not as a decision-maker. AI can help you find the needle in the haystack but shouldn’t determine what the needle means.
- Maintain human oversight. A trained investigator should review all AI-generated outputs, double check them for errors, and interpret them in the context of policy and the law.
- Vet vendors carefully. Ask about bias testing, data provenance, audit logs, and compliance with applicable privacy laws.
- Disclose use of AI tools when appropriate. Transparency with complainants, respondents, and counsel can help avoid due process or procedural fairness concerns.
Conclusion: AI is a Tool, Not a Trained Professional
Artificial intelligence offers promising tools to enhance the efficiency and consistency of investigations in workplaces and educational institutions. But it cannot—and should not—replace the nuanced judgment of trained professionals. The stakes in school and workplace investigations are too high to leave to opaque algorithms.
As regulators, courts, and watchdogs begin scrutinizing the use of AI in employment and education, legal professionals must take the lead in developing policies that harness the benefits of AI while mitigating its risks. While AI can support investigators, it is the human element—an understanding of context, empathy, and ethical judgment—that must remain at the heart of any fair process.
