Video conferencing platforms became critical infrastructure almost overnight. The security implications of that transition have been managed unevenly: most organizations addressed the obvious risks (unauthorized access, meeting bombing) early on, and then stopped auditing. The current threat model has moved significantly beyond meeting bombing, and most IT security reviews of video conferencing haven't kept pace.
This is a practical guide to what IT teams should be auditing at contract renewal time.
The current threat model
AI data pipelines. Most video conferencing platforms now include AI transcription, summary, and analysis features. The security question for each AI feature: is this AI processing handled by the platform's own infrastructure, or is it handled by a third-party subprocessor? If it's a subprocessor, what are their data handling terms, and are they covered by your existing data processing agreements?
For platforms that use third-party AI services (common among established platforms that added AI as an afterthought), meeting transcript data is transmitted to an external service. The implications depend on what data is in those meetings — PHI, PII, confidential business information, attorney-client communications — and what the third-party's terms permit.
Third-party meeting bots. The notetaker bot ecosystem — Otter, Fireflies, Grain, and many others — creates a parallel security perimeter problem. When a notetaker bot joins a meeting, it transmits the audio and transcript to a completely separate service with its own security posture, its own data retention policies, and its own terms of service. From a security perspective, this is equivalent to allowing an unknown third party to attend every meeting and take a copy of the transcript.
IT teams that have not explicitly approved notetaker bots as data processors, or have not determined whether they are permitted in their regulatory environment, have an unaddressed gap.
Meeting recording storage. Where are recordings stored? What are the access controls? What are the retention periods? Are recordings subject to the same data classification policies as other organizational data? Most organizations answer these questions for structured data (databases, CRM records) but have weaker controls for meeting recordings, which can contain highly sensitive information.
Authentication and access controls. Meeting links that are guessable, meeting rooms with no waiting room, and authenticated-user-only meeting settings are baseline controls. The question for a mature security review is whether these controls are consistently applied across all meeting types — not just the sensitive ones that IT designated as high-risk.
The audit checklist
Transcription and AI features:
- [ ] Which AI features are enabled by default vs. opt-in?
- [ ] Is transcription handled by the platform natively or by a third-party subprocessor?
- [ ] Is meeting transcript data used for model training? What is the opt-out mechanism?
- [ ] What are the access controls for meeting transcripts?
Third-party integrations:
- [ ] What third-party tools are authorized to access meeting data via API or bot?
- [ ] Has each authorized third party been assessed as a data processor?
- [ ] Is there a mechanism to detect unauthorized third-party bots joining meetings?
Recording storage:
- [ ] Where are recordings stored (jurisdiction, storage provider)?
- [ ] What are the default retention periods, and can they be configured?
- [ ] Who has access to recordings by default, and can this be restricted?
- [ ] Is there an audit log of recording access?
Authentication:
- [ ] What authentication is required to join a meeting (link only vs. authenticated)?
- [ ] Are waiting rooms enabled by default or configurable per meeting type?
- [ ] Is SSO available and enforced for organizational meetings?
- [ ] Is there a mechanism to remove participants from active meetings?
Incident response:
- [ ] What is the platform's incident response process for a data breach involving meeting content?
- [ ] What is the notification timeline and mechanism?
- [ ] Is there a data deletion capability on demand?
The first-party AI advantage
For organizations evaluating AI meeting features from a security perspective, the architecture of the AI matters as much as the feature set. Platforms like MeetOye handle AI transcription and recap natively — through Oya, which is part of MeetOye's own infrastructure, not a third-party service. This means:
- One data processor to assess, not two
- Transcript data stays within the platform's existing security controls
- No separate subprocessor agreement required for the AI function
For organizations with strict data processing requirements, this architectural difference is material to the vendor assessment.
Author bio:
The MeetOye Team builds AI-native video meeting software with a security-first architecture. MeetOye (meetoye.com) handles transcription and AI features natively, eliminating third-party AI data processors from the meeting security perimeter.
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