Artificial intelligence is reshaping nearly every corner of the workplace, including workplace investigations.  Generative AI is one of the most significant industry disruptors in decades, and its influence will be increasingly felt in workplace investigations over the coming years. AI is poised to transform both the tools investigators use and the nature of the evidence they assess.

Evolution of Investigation Tools

Historically, workplace investigations occurred in person and investigators relied on basic tools: a notebook, a laptop, and occasionally a voice recorder or camcorder. As recording technology became more affordable and accessible, some interviews were recorded and digitized. The COVID-19 pandemic ushered in a shift toward virtual investigations, fundamentally changing how interviews and evidence are collected.

The next seismic shift is already underway, driven by AI-powered tools which are emerging to assist with many aspects of the investigative process. Modern tools can:

  • create instant interview transcriptions
  • analyze and summarize lengthy transcripts in seconds
  • organize thousands of emails or documents into clear chronologies in seconds
  • surface trends and identify inconsistencies between multiple witness accounts
  • determine whether exhibits are AI-generated
  • generate targeted interview questions
  • draft portions of investigation reports, extracting key quotes or facts automatically.

Used responsibly, these advances can save hours of manual review and help investigators focus on the aspects of the job where human skill matters most – judgment, credibility, and context.

Benefits and Risks of AI in Evidence Collection

AI-powered transcription tools built into platforms like Zoom and Microsoft Teams can now generate near-instant interview transcripts. These tools are fast and remarkably capable, but far from flawless.

Even a system that boasts 99% accuracy could make hundreds of mistakes during a three-hour interview. A “yes” could be captured as “no”; names with multiple spellings will often be recorded wrong. And the systems still have problems with accents they are unfamiliar with, which can lead to more transcription errors. Left unchecked, these small errors could alter the meaning of key testimony or embarrass investigators who later rely on inaccurate transcripts.

Investigators must remain vigilant as such mistakes can have substantial consequences.

The Limits of AI in Investigations

Despite these advancements, certain aspects of workplace investigations remain uniquely human. No matter how advanced AI becomes, it cannot replicate human empathy, intuition, or moral judgment. Workplace investigations are often stressful, personal, and emotionally charged. A computer cannot build rapport with a nervous witness or interpret tone and context the way a trained human can.

AI systems are also only as unbiased as the data they are trained on. Poorly trained models can inadvertently favour or discredit certain groups, compounding the very inequities that workplace investigations aim to correct. Investigators must therefore remain cautious and critically engaged when incorporating AI tools to ensure the technology enhances, rather than undermines, fairness and integrity.

The Challenge of Deepfakes and Synthetic Evidence

AI’s rapid development brings both remarkable capabilities and troubling risks.

Deepfake technology can now fabricate convincing videos, audio clips, and text messages with little more than a few seconds of someone’s voice or an image of their face. A determined bad actor can produce a video of an employee appearing to steal company property, or create an entirely fake text exchange between coworkers.

Even advanced investigators may find it difficult to distinguish real evidence from synthetic content. A recording that sounds authentic might have been generated using an employee’s voice sample; a WhatsApp message might be fabricated by a chatbot in seconds.

The result is a new kind of investigative challenge — one where verification is more critical than ever. Investigators must examine digital evidence with a skeptic’s eye:

  • Do timestamps or message icons look inconsistent?
  • Are there visual anomalies such as unnatural blurring or lighting shifts?
  • Does a video “jump” slightly or contain impossible movements?

Specialized detection tools can help identify AI-generated material, often by spotting hidden digital watermarks or inconsistencies in metadata. But these tools are imperfect and bad actors are continually evolving their methods. The responsibility for discernment still rests with the investigator.

Best Practices for Investigators

To address these challenges, investigators should:

  • Examine each piece of evidence for subtle inconsistencies or anomalies
  • Use available tools to verify the authenticity of digital evidence
  • Maintain skepticism and vigilance when reviewing materials
  • Present relevant evidence to the opposite party so they can respond to it, allowing them the opportunity to identify if they believe it’s inauthentic; this can prompt you (or your IT department) to review it further
  • Recognize that technology will continue to improve, making fakes harder to spot

Conclusion

Generative AI is transforming workplace investigations, offering powerful new tools but also introducing new risks. AI offers extraordinary potential to make workplace investigations more efficient, accurate, and data-driven. But with that potential comes the risk of overreliance, bias, or manipulation.

The best investigators of the future will be those who embrace AI as a tool, not a replacement. They will use it to automate the mechanical aspects of the job while preserving the human elements that machines cannot replicate such as empathy, reasoning, and ethical judgment.

AI will continue to evolve, and so must investigators. The key will be leveraging innovation without surrendering the human touch that remains at the heart of every fair and credible investigation.