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Six questions to ask before using GenAI for transcription

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Generative AI tools have made significant inroads into the workplace, offering time-saving solutions like automated transcription for meetings. If your company is using, or considering using, generative AI for transcription, there are critical questions to address to ensure the technology is implemented responsibly and effectively.

1. Retention Policies: How Long Should Transcriptions Be Stored?

Transcriptions can be a valuable resource, but storing them indefinitely creates significant risks.

Legal teams should ask:

  • What is the minimal useful life of a meeting transcript? Holding transcriptions unnecessarily increases exposure in litigation, where these records could be subpoenaed and scrutinized. Without retention limits, the volume of data could become unmanageable.

  • Do we have an auto-deletion policy? Evaluate the purpose of storing transcriptions. If they are rarely referenced after a week or two, consider a short retention period such as 15 or 30 days.

  • Are these policies consistent with data retention guidelines from regulators, such as the DOJ’s guidance on ephemeral messaging? Regulators like the DOJ recommend ephemeral messaging practices to limit the availability of sensitive data. Aligning transcription policies with this guidance ensures compliance and reduces risk.

By setting a clear retention policy, companies can minimize the risks associated with litigation and data breaches.

2. Scope of Transcriptions: Are All Meetings Equal?

Not all meetings should be transcribed. Sensitive discussions—such as those involving HR issues, legal strategies, or executive-level decisions—may pose significant risks if recorded.

Key questions include:

  • Are certain types of meetings exempt from transcription? Develop a high-risk rubric to identify sensitive meetings—such as those involving HR issues, legal strategies, or executive decisions—that should never be transcribed.

  • Do we place restrictions around who can transcribe? Restrict transcription permissions to hosts who are trained to evaluate when transcription is appropriate.

  • How do we balance productivity gains from transcriptions with the need for confidentiality? While transcription tools can improve accessibility and recordkeeping, they must not undermine privacy or chill open discussions during sensitive conversations.

Some companies are implementing policies where only designated hosts can enable transcription, limiting the scope to specific scenarios.

3. Privacy and Risk Management: Protecting Sensitive Information

Transcriptions often capture more than just notes—they can include sensitive personal information or trade secrets. To manage these risks, organizations should evaluate:

  • Are our transcriptions encrypted and stored securely? Ensure that all transcription data is encrypted, both in transit and at rest, to protect it from breaches.

  • Are there clear guidelines on sharing and access permissions? Define clear guidelines for who can view, share, or edit transcriptions. Limiting access prevents sensitive information from falling into the wrong hands.

  • How do we handle personal information or inadvertent data breaches within transcriptions? Establish a protocol for handling personal information or data breaches that arise from transcription usage. Having a response plan mitigates damage and ensures compliance with data privacy regulations.

Establishing robust security protocols is essential to protect both employee privacy and company data.

4. Governance: Do You Have the Right Policies in Place?

Governance frameworks ensure that AI tools are used responsibly. Companies should:

  • Define an AI use policy and require employees to acknowledge it. Draft AI use policies that outline acceptable uses, restrictions, and employee responsibilities. Include guidelines for handling sensitive data and securing transcription records.

  • Train employees on appropriate use, including how to avoid sharing sensitive information with AI tools. Provide targeted training on transcription tools, covering prompt design, privacy considerations, and compliance requirements. Employees should understand how to avoid common pitfalls like inputting sensitive information.

  • Monitor compliance with internal policies and audit transcription usage periodically. Form an AI governance committee with representatives from IT, legal, HR, risk management, and business units. This cross-functional team ensures decisions are well-informed and align with organizational goals.

5. Litigation Risks: Are You Prepared for Discovery?

Meeting transcriptions can become a double-edged sword during litigation or audits. Key considerations include:

  • Are you prepared to produce transcriptions as part of discovery in lawsuits or investigations? Courts may request meeting transcriptions during lawsuits, requiring companies to sift through large volumes of data. A lack of organization or retention policies can lead to costly and time-consuming responses.

  • How do you avoid situations where personal or sensitive data in transcriptions becomes a liability? Maintain an inventory of where transcription data is stored and who has access to it. This ensures that information can be retrieved efficiently without unnecessary sprawl.

  • Are audit logs maintained to track transcription access and use? Use audit logs to track who accessed transcriptions, when, and why. This provides an extra layer of accountability and reduces the chance of unauthorized use.

Without clear policies, transcription data can quickly become a costly and unmanageable risk.

6. Efficiency vs. Risk: Are You Getting the Balance Right?

AI transcription is meant to improve efficiency, but poorly managed implementations can backfire. Companies should assess:

  • Are employees leveraging transcription tools effectively, or are they spending excessive time reviewing and managing transcripts? Employees may spend excessive time reviewing full transcripts instead of focusing on actionable insights. Introduce alternatives like keyword highlights or summaries to reduce the cognitive load.

  • Are there better alternatives, such as summaries or keyword-based highlights, that deliver value without the risks of full transcriptions? Over-documentation of meetings can chill open communication, especially in distributed teams. Set clear expectations about when and how transcriptions will be used to foster transparency.

  • How do you ensure that employees understand the capabilities and limitations of the AI tools they’re using? Rapid adoption of AI tools without proper training or support can lead to frustration and inefficiency. Invest in training programs that teach employees how to use these tools effectively.

Training and change management are crucial to reaping the benefits of AI without creating new challenges.

Building a Framework for Responsible Use

Generative AI for transcription has the potential to transform workflows and enhance productivity. However, without thoughtful implementation, it can introduce significant risks.

Companies should:

  • Establish Clear Policies: Define retention periods, access permissions, and exemption criteria.
  • Focus on Training: Ensure employees understand how to use AI tools effectively and safely.
  • Engage Cross-Functional Teams: Involve stakeholders from legal, IT, HR, and risk management to create a balanced governance framework.
  • Monitor and Adjust: Regularly review transcription practices to adapt to new risks and opportunities.

By asking the right questions now, your company can harness the benefits of generative AI while minimizing its risks.