In today’s business environment, AI-driven transcription tools are becoming increasingly common in meetings. When implemented correctly, these tools offer significant benefits in terms of efficiency and accessibility. However, a new challenge has arisen: employees are often using unauthorized transcription tools without the consent of their companies or meeting participants, leading to various compliance, privacy, and legal risks.
This phenomenon, commonly known as shadow AI, poses serious governance issues for organizations striving to use AI responsibly. Companies must not only evaluate which tools are permitted but also address the risks associated with the use of unauthorized applications by employees.
A recent survey by the National Cybersecurity Alliance revealed that 43 percent of AI users admitted to sharing sensitive company information with AI tools without informing their employer.1 This statistic highlights that the use of shadow AI is a growing issue and is often taking place outside the purview of legal and compliance teams.
Understanding the Risk Landscape
The use of unapproved transcription tools can lead to numerous challenges for organizations. Key risk areas include state laws regarding recording consent, confidentiality obligations, governance controls, and record retention practices. If these issues are left unaddressed, they can result in significant legal and operational repercussions.
In jurisdictions that require “two-party” or “all-party” consent, every individual in a conversation must give their agreement prior to recording or transcribing the discussion.2 Employees who initiate transcription without consent may inadvertently violate these laws, which can carry criminal penalties or allow for civil lawsuits. In some cases, if company policies do not explicitly prohibit unauthorized transcription, employers might be held vicariously liable for actions carried out by employees within their job scope. Moreover, if employees secretly record meetings with external executives, the company could face corporate criminal liability.
Using unauthorized tools can also jeopardize confidentiality and legal privileges. When partnering with a vendor, companies can negotiate terms around data security, retention, and confidentiality. However, consumer-grade transcription tools often lack these essential safeguards. Data captured through such tools might enter large language models, risking the waiver of attorney-client privilege and trade-secret protections, as well as breaches of data privacy laws. Once data is in these systems, the company loses control over its dissemination and potential misuse.
From a governance standpoint, unauthorized transcription undermines an organization’s ability to strategically manage meeting recordings. Decisions about recording should be made collectively at the organizational level instead of by individual employees. This oversight ensures that the company can maintain control over its records and verify the accuracy and context of transcripts against official notes.
The risks escalate in legal and regulatory scenarios. Data stored outside formal retention policies can result in gaps during discovery processes or lead to civil sanctions, and even obstruction of justice charges may arise if the information pertains to a governmental investigation.3 Most consumer platforms have unclear retention guidelines, complicating compliance with established data management practices. Investigations may compel transcripts directly from employees, bypassing corporate legal supervision and creating inconsistencies that can undermine privilege and credibility.
In summary, shadow AI erodes a fundamental principle of good governance: a company should maintain control over what is recorded, how it is stored, and how long it is retained. Restoring this control is vital for safeguarding privilege, confidentiality, and compliance.
Taking Control of Shadow AI
To effectively manage shadow AI, organizations must start with a critical question: should employees be allowed to use transcription tools, and if so, under what conditions? This decision should be integrated into the company’s overarching AI governance strategy and involve legal, compliance, and IT-security departments.
If a company determines that transcription tools can provide value when used appropriately, legal advisors should bring transparency to AI usage. This begins by identifying the tools currently in use and the reasons behind their adoption. Often, employees utilize shadow AI for efficiency rather than policy evasion, and understanding this can inform a more effective response. Engaging directly with business teams will help pinpoint gaps in existing tools and allow the organization to adjust approved solutions to meet those needs.
Upon gaining insight into the situation, companies should choose secure, enterprise-grade transcription tools that comply with confidentiality, privilege, and record-keeping mandates and align with operational needs and regulatory landscapes. Approved vendors must define data ownership terms, specify retention and deletion rights, and provide secure environments that prevent unauthorized use of company data in AI training.
Company policies should clearly state when recordings are permissible and who is responsible for authorizing them. The decision to record should rest with designated personnel rather than individuals, and all employees must be educated that each recording qualifies as a corporate document, subject to consent and legal requirements.
Training and employee engagement play essential roles in this process. Legal and compliance teams should ensure that employees are aware of:
- The legal and reputational risks associated with unauthorized recordings or transcriptions;
- State consent regulations and the potential penalties for non-compliance;
- The ways in which privilege and confidentiality can be compromised through unapproved tools; and
- The processes for obtaining authorization for recording and managing related data.
Providing employees with effective, compliant tools that address their needs is equally important. When approved solutions are efficient and easy to use, the temptation to resort to shadow AI diminishes.
If a company decides against using transcription, this policy must be communicated clearly and reinforced through training sessions. Employees should understand the rationale: unauthorized recordings can lead to legal violations, breaches of confidentiality, and loss of privilege. Technical measures can support enforcement by detecting or blocking unauthorized applications, though consistent communication and visible backing from leadership typically yield better long-term compliance.
Looking ahead, organizations should accept that some shadow AI activity may persist. Robust governance is contingent upon visibility and accountability—identifying unapproved tools, limiting their use, and ensuring proper management of data from authorized channels. By incorporating AI oversight into existing compliance and information governance programs, companies can remain in control as technology and business practices continue to evolve.
