AI technology is rapidly being adopted across various industries, but it also comes with potential compliance implications. Some of the most significant compliance implications of AI include legal, ethical, operational and financial compliance.

When it comes to legal compliance, AI systems must comply with legal and regulatory frameworks to avoid legal penalties and other issues. For instance, the General Data Protection Regulation (GDPR) requires companies to ensure data privacy and provide transparency in AI decision-making.

Furthermore, AI systems must be ethically responsible to avoid unethical outcomes such as bias, discrimination, and unintended consequences. Ethical compliance ensures that AI systems make decisions that align with core human values. 

Speaking of operational compliance, AI systems must comply with operational standards to ensure reliability, accuracy, and consistency. Operators must evaluate the performance of the AI system regularly, and establish guidelines that ensure its ongoing maintenance, monitoring, and follow up.

Finally, AI systems must comply with financial regulations, such as the Anti-Money Laundering [AML] regulations, to prevent financial crimes.

AI systems are continuously evolving and updating, which makes it essential to keep monitoring and updating their compliance guidelines to match the changing environment.

GDPR is a comprehensive data protection regulation that sets out strict rules for the collection, processing, and storage of personal data of individuals within the European Union. It aims to protect the privacy and data rights of citizens by defining clear responsibilities and obligations for organizations that process personal data. AI systems that process personal data must comply with the strict data protection rules set out in the GDPR. Therefore, organizations developing AI systems need to ensure that their systems adhere to GDPR principles, and they must seek informed consent from data subjects whose data the AI system uses.

Being clear with individuals about how and why their data is being processed is a cornerstone of GDPR. Where businesses rely on AI for profiling and automated decision-making, they must explain that this is taking place, as well as the logic involved in any such decision-making, including the significance and consequences for the individual. This can be very challenging when the underlying processing relies on highly complex and ever-changing AI tools and various distinct data pools. Businesses need to achieve the right balance between being comprehensive while also remaining understandable for the average individual. Transparency is also an ongoing obligation and so businesses must ensure privacy notices are kept under review and updated when processing changes.

Algorithms need to be fed data to learn and further develop. While many businesses hold valuable user and customer data already, they must ensure that before using data to improve their AI, they can do so in compliance with GDPR. For example, if a business wants to use its existing customer data to train its AI, it needs to ensure it has a legal basis for the processing, like relying on its legitimate interests. The business must also ensure that it has informed those affected of this intended use. GDPR obligations also apply to any data received from third parties or public sources once it relates to an identifiable individual. While aggregation and deidentification are privacy protective measures, businesses should ensure robust assessments are carried out before concluding aggregated or anonymised data actually fall outside the scope of the GDPR.

As algorithms develop and learn, they will inevitably create opportunities for new and additional uses of data. Before businesses start deploying their technology in this way, they should ensure the data can be used in compliance with GDPR. Key issues to consider are whether individuals have been informed of this intended use, would expect it, and whether there is a valid legal basis for processing. For example, whether any previously obtained consent is sufficiently broad enough to cover the new processing.