As with all work, prioritising AI-related tasks is essential to ensure you focus your time where it is most needed. Even knowing this, the constant overflow of to-dos can be overwhelming – especially when every task is accompanied by a request to complete it yesterday. In this D&I Quarterly series, Iiris Kivikari, our Head of IP, Media and AI, gives you a peek into what is taking up space on our team members’ (virtual) desks in order to help you figure out what AI work you might want to be focusing on right now.
Identifying Beneficial Use Cases
One of the typical first steps in responsibly integrating AI into a business, particularly in regulated fields such as finance and healthcare, is to map out potential use cases where AI could provide significant benefits.
Our clients often start by conducting a comprehensive review of their operations to identify areas where AI can enhance efficiency, accuracy, and innovation. This process involves collaboration between various departments, including business units and administrative functions, to ensure a holistic view of the potential applications of AI.
For instance, in the healthcare sector, AI can be used to improve diagnostic accuracy, streamline administrative processes, and personalize patient care. In finance, AI can enhance fraud detection and improve customer service through chatbots. Not to even mention the fact that most office workers, regardless of their area of business, could use a helping hand in sifting through and responding to emails.
“After mapping out these use cases, companies can then prioritize which AI projects to pursue based on their potential impact and feasibility.”
Conducting an In-Depth Legal Analysis
Once you have identified which use case you want to give a try, each one should undergo a thorough legal analysis to ensure compliance with relevant regulations and standards. This step is especially crucial in regulated industries where the misuse of AI can lead to significant legal and reputational risks. Nevertheless, if you read part 1 of our AI Prep List series, you know that even situations where AI is harnessed for the benefit of employees themselves can have their own pitfalls – which you can avoid if you do your due diligence and know where to look.
“By conducting a use case-specific legal analysis, organisations can establish clear guidelines and prerequisites for the compliant use of AI in each identified use case. This is often imperative, because – as we all know – the fact that AI is technically capable of something, does not necessarily mean we are allowed to use it for that purpose.”
Our team works closely with clients to analyse the legal implications of each use case, considering factors such as data protection, privacy, intellectual property, communications laws, liability, (business) area specific regulations, cyber security, ethical considerations and, of course, the AI Act. In healthcare, AI systems must adhere to, for example, the AI Act, general and patient data protection laws, data security laws, medical device regulations, and even provisions on the quality of the output text – just to name a few. By conducting a use case-specific legal analysis, organisations can establish clear guidelines and prerequisites for the compliant use of AI in each identified use case. This is often imperative, because – as we all know – the fact that AI is technically capable of something, does not necessarily mean we are allowed to use it for that purpose.
Establishing a Framework for Compliance
After mapping and analyzing use cases, the next step is to establish a framework for ongoing compliance. This involves creating the necessary policies and procedures that govern the development, procurement, deployment and monitoring of AI systems, and the use of the AI outputs. For example, many of our clients are implementing cross-functional AI governance committees to oversee the implementation of new use cases and ensure that the use of AI is duly considered in internal processes and policies.
“As always, change is also easier to bring about if the top management is committed and involved in getting things done.”
Key components of this framework include the continuous monitoring of AI systems, and training programmes for employees on AI-related issues (i.e. working towards AI literacy). As always, change is also easier to bring about if the top management is committed and involved in getting things done.
By establishing a comprehensive compliance framework, companies can mitigate risks and ensure that their use of AI remains responsible and aligned with regulatory requirements. This is not to say that (all) AI processes and policies need to be separate from pre-existing ones; on the contrary, they can and often even should be integrated. Especially your existing structures related to data protection, intellectual property, data security and IT may form a brilliant foundation for AI work too. If so, all that is needed is tweaking these existing organizational structures to encompass the quirks that are inherent to AI.
Read also D&I’s AI Prep List for Lawyers – Vol 1. AI and Communications
