With six years of history behind it, GDPR has transformed compliance from an important, yet niche topic to its current role, where data protection issues regularly make major national headlines.
Based on a group of core principles, ranging from lawfulness, fairness and transparency to data accuracy, integrity, confidentiality and accountability, it has positively impacted consumer privacy. Organisations failing to comply run the risk of enforcement action, with many – but not all – taking their responsibilities seriously, not least because of the reputational damage a breach can cause.
For those organisations subject to GDPR regulation, however, the rapid deployment of AI technologies is already adding a further layer of complexity and risk. Indeed, without effective processes in place, it’s likely that the development and use of AI systems will quickly become another major compliance headache.
For example, any organisation with an EU customer base using consumer data to train AI applications must have their consent, and as a result, it’s extremely important to prioritise legal compliance over speed of deployment. A mindful approach should be central to building an AI strategy where compliance is included from the outset, rather than bolted on as an afterthought or as a knee-jerk reaction to a breach.
Organisations must also be careful that the security and privacy issues associated with ‘shadow SaaS’ aren’t repeated as employees use an increasing variety of AI-powered applications. In particular, users creating accounts outside of standard procurement processes can easily undermine security, compliance and data integrity standards. In this context, the use of AI apps is no different from any other SaaS solution. Once data is shared, the organisation no longer has control over its eventual destination, and lacking that control, the possibility of a GDPR breach grows.
The importance of effective technical controls
So, where does that leave organisations that are looking to balance the huge potential of AI with the additional GDPR responsibilities and risks it creates? One of the core issues to address is putting the right data security controls in place, and there are a number of measures that can significantly increase the scope for ongoing compliance.
Ideally, all GDPR data should be encrypted to build a strong layer of security and privacy. The approach is even more effective when implemented end-to-end, so data is protected by encryption, irrespective of whether it is at rest or in transit. This can significantly reduce the risks associated with data leaks or exfiltration at the hands of threat actors and, by definition, helps address GDPR compliance. At the very least, all sensitive data should be encrypted as standard.
It should also be processed to remove personally identifiable information (PII) to minimise the chances of losing personal data. This process, known as data masking or pseudonymisation, replaces PII information with artificial identifiers to break the connection between data elements and a specific data subject.
Next, Identity and Access Management (IAM) gives organisations control over who can interact with their data. It sets out access privileges to ensure only authorised are given access to information, based on pre-defined limitations.
Effective DLP solutions will deliver a range of capabilities, such as coaching employees on sensitive data handling, ensuring data is encrypted, and preventing transmission or unauthorised access to specific files. As such, they can help minimise the risks of malicious data breaches or accidental handling errors—either of which can lead to a failure of GDPR compliance.
In addition, Data Loss Prevention (DLP) provides a framework for enforcing data handling policies. These set out specific rules for how data can be used, accessed, and shared and are defined to address the objectives and data resources unique to every organisation.
It is critical to demonstrate to an auditor or post-breach investigation team that rigorous data security controls are in place to mitigate data exposure risk and proactively protect sensitive data.
Wrapped around the entire GDPR compliance strategy are cybersecurity monitoring and threat detection processes and technologies. These enable organisations to ensure a high level of vigilance against the risks posed by existing and emerging vulnerabilities and the tactics employed by threat actors. How well these capabilities are delivered is fundamental to whether GDPR compliance can be maintained.
With these capabilities embedded within organisational infrastructure, processes and culture, GDPR compliance can be transformed from a nebulous objective into a powerful and continuous routine. This will remain essential in an environment where, despite its many compelling advantages, AI is bringing a further layer of complexity and risk.
