AI, Call Recording and GDPR: What Businesses Need to Know

AI, call recording, and GDPR are reshaping the way businesses handle customer interactions. Advances in AI now allow companies to transcribe calls, analyse sentiment, and identify patterns at scale, which provides valuable insights for improving service and operations.

However, these capabilities also increase responsibility. Recording and analysing calls involves processing personal data, which means businesses must carefully navigate GDPR requirements. This blog explains what counts as call recording, how AI is changing the data protection landscape, and the steps businesses need to take to stay compliant.

What counts as call recording under GDPR?

Call recording is defined broadly under GDPR. It’s not just limited to traditional audio recordings of phone calls. Any capture, storage, or processing of information from a call that can identify an individual is classed as personal data processing. This includes full or partial audio recordings, call transcripts, voicemail messages, and live monitoring where data is captured or analysed in real time. If AI tools are used to transcribe calls, analyse sentiment, identify keywords, or score performance, this also falls within the scope of call recording under GDPR.

Importantly, GDPR applies whether the recording is stored permanently or temporarily. Even short-term buffering, automated analysis without human listening, or anonymisation that can be reversed, can still count as processing personal data.

Call recording under GDPR can include:

• inbound and outbound business calls
• internal calls where individuals can be identified
• voice recordings linked to customer records or CRM systems
• AI-generated insights derived from call content, not just the audio itself

If a call contains information that identifies a person directly, such as a name or account number, or indirectly, such as a voice pattern, role, or situation, GDPR obligations apply. Businesses should therefore treat any recorded or analysed call as personal data unless it has been fully and irreversibly anonymised.

How is AI changing the data protection landscape?

AI is transforming call recording from a passive activity into an active form of data processing. Instead of simply storing audio, businesses can now automatically transcribe calls, identify behavioural patterns, and generate insights at scale. This significantly increases both the volume of personal data processed and the potential privacy risks.

One of the biggest changes is the shift from human-led review to automated analysis. GDPR places additional obligations on processing that is systematic, large-scale, or involves profiling, which many AI-driven analytics tools fall under. Even if no one listens to the calls, the automated extraction of meaning, intent, or performance data is still classed as personal data processing.

AI also blurs the line between raw data and derived data. Insights such as sentiment scores, risk flags, or performance ratings are often treated as outputs rather than personal data, but under GDPR they are still linked to identifiable individuals and must be handled accordingly.

There is also greater emphasis on transparency and explainability. Businesses must be able to explain, in clear terms, how AI tools work, what data they analyse, and how decisions or insights are generated. Black-box systems with limited oversight increase compliance risk.

AI also increases the importance of governance and accountability. Regular reviews, data protection impact assessments, and robust controls around third-party AI providers are becoming essential. As AI capabilities grow, so does regulatory scrutiny, which is making data protection a central consideration for businesses.

What are the rules around call recording and GDPR?

Call recording is permitted under GDPR, but only if clear rules are followed. Businesses must be able to justify why calls are being recorded and how the data is used, particularly when AI is involved. Failure to follow these rules can result in regulatory action, fines, and reputational damage, so compliance should be a critical part of any call recording strategy.

A lawful basis is required

Every recorded call must have a lawful basis under GDPR. Common options include legitimate interests, where recording is necessary for purposes such as quality monitoring or fraud prevention, or consent, which must be freely given, informed, and easy to withdraw. Businesses are not able to rely on consent if callers have no genuine alternative.

Transparency is mandatory

Individuals must be clearly informed that calls are being recorded or analysed. This includes explaining the purpose of recording, whether AI tools are used, how long the data is kept, and who it may be shared with. It is not sufficient to give a vague or generic message – it must be clear and precise.

Purpose limitation and data minimisation

Calls should only be recorded and analysed for specific, stated purposes. Businesses must avoid collecting more data than necessary and should limit AI analytics to what is genuinely required to meet those purposes.

Retention and security requirements

Recorded calls and transcripts can’t be kept indefinitely. Retention periods should be defined, documented, and enforced. Appropriate technical and organisational measures must be in place to protect recordings from unauthorised access or breaches.

Respecting individual rights

Recorded individuals have the right to access their data, request erasure, object to processing, and raise concerns about automated analysis. Businesses must have processes in place to respond to these requests within GDPR timeframes.

Accountability and documentation

Organisations must be able to demonstrate compliance. This includes maintaining records of processing, carrying out data protection impact assessments where AI analytics pose higher risks, and ensuring third-party providers meet GDPR requirements.

How to balance insight with responsibility

Automated Analytics makes it simple for businesses to harness the power of call data safely and effectively. By combining AI-driven analysis with built-in GDPR compliance, we can transform customer interactions into actionable insights without the worry of regulatory risk.

With Automated Analytics, companies can improve service, boost efficiency, and make smarter decisions, all while maintaining transparency and protecting personal data.

Contact us today for more information or book a free demo.