[author: Rana Chatterjee]
Q1: How can businesses in your jurisdiction adopt AI and automation responsibly, and what guidance are you offering to ensure regulatory compliance?
In the UK, businesses are increasingly turning to AI and automation to improve efficiency, reduce costs and gain competitive advantage. But adopting these technologies responsibly means more than just meeting technical requirements, it involves thoughtful governance and alignment with legal and ethical standards.
There is currently no standalone AI law in the UK, but existing legal frameworks already place important obligations on businesses, particularly around data protection, human rights, and non-discrimination. Regulatory guidance encourages organisations to approach AI development and deployment in line with principles such as transparency, fairness, and accountability.
To support this, we help clients map how AI is being used in their organisation, assess legal implications, and build the right controls. This includes developing internal policies, reviewing contracts with suppliers, and ensuring that teams understand when legal duties, such as providing individuals with meaningful information about automated decisions, come into play.
One practical step is to bring different parts of the business, including legal, compliance, HR, and technical teams, into early-stage planning. This helps businesses identify potential issues before they arise and tailor their approach to risk in a way that fits their specific operations.
By embedding legal awareness and oversight from the outset, businesses can adopt AI in a way that is not only compliant but also aligned with wider ethical and commercial priorities.
Q2: What are the key risks of implementing AI, from data privacy to ethical concerns, and how can you help businesses in your jurisdiction navigate these complexities?
As AI becomes more powerful and accessible, the legal and ethical risks are becoming more visible. In the UK, businesses face growing scrutiny around how they use AI – particularly when it affects individuals’ rights, access to services, or employment prospects.
One major area of concern is data use. AI systems often depend on large volumes of data, including personal and sensitive information. If that data is flawed or handled without appropriate safeguards, businesses may face both regulatory and reputational consequences. The challenge is not only ensuring that data is accurate and lawfully processed, but also understanding how it influences AI-driven outcomes.
Another risk is lack of oversight. Many AI tools operate without full transparency, which can make it difficult for businesses to explain or justify decisions. This becomes especially problematic when systems are used in high-impact areas like recruitment, lending, or public services. Without clear visibility and controls, it’s harder to spot mistakes or correct unintended bias.
To navigate this complexity, we advise clients to adopt a structured approach to AI governance. This includes assessing where AI is used, evaluating potential impacts, and ensuring roles and responsibilities are clearly defined. We also work with businesses to design practical tools such as staff guidance, risk assessment templates, and escalation routes for concerns.
While the legal landscape is still evolving, the expectation is clear: AI should be used in a way that is fair, lawful, and accountable. [AE1] With the right support, businesses can meet those expectations while still achieving their innovation goals.
Q3: Are you seeing any trends in AI-driven disputes or liability concerns? How can firms assist clients in addressing potential AI-related litigation or regulatory scrutiny?
Although formal disputes involving AI are still emerging, we are seeing a clear rise in legal and regulatory challenges linked to AI use. These often stem from real-world issues: a flawed algorithm in recruitment, a misfiring automated decision in finance or healthcare, or confusion about liability when AI is supplied by a third party.
We’re also seeing increasing concern over whether AI tools meet existing legal standards, particularly around data protection and discrimination. Regulators such as the Information Commissioner’s Office are beginning to probe how AI decisions are made, whether they are explainable, and whether individuals’ rights are being respected.
A recurring issue is uncertainty over responsibility. When something goes wrong, the blame can be difficult to pinpoint, was it the business using the AI, the vendor who built it, or the team that implemented it without fully understanding its limitations? That’s why contract clarity and internal accountability are so important.
To help clients prepare, we focus on strengthening governance frameworks. This includes reviewing contracts to allocate risk appropriately, advising on auditability and transparency, and supporting clients with internal investigations or regulator engagement if things go wrong. We are also seeing more training being rolled internally out amongst our clients who are concerned about the use of AI in day-to-day business operations to help prevent future issues.
Looking ahead, we expect more scrutiny and potential disputes as AI becomes further embedded in business operations. The best defence is good preparation: building clear policies, maintaining strong documentation, and making sure systems are regularly reviewed and responsibly managed. With the right legal advice, businesses can respond effectively if challenges arise and reduce the likelihood of problems occurring in the first place.
Key Takeaways
- UK businesses adopting AI and automation must align deployment with legal and ethical standards, including transparency, fairness, and accountability. In the absence of a standalone AI law, existing regulations – particularly data protection and non-discrimination – require proactive governance, legal oversight, and early collaboration across legal, technical, and HR teams.
- Key risks include unlawful data use, lack of transparency, and algorithmic bias. Businesses are encouraged to implement structured AI governance frameworks, including mapping AI use, conducting impact assessments, and setting escalation mechanisms. Clear internal policies and staff training are essential to prevent regulatory and reputational risks.
- As regulators scrutinise AI more closely, businesses must be ready for disputes concerning flawed algorithms, opaque decisions, or vendor liabilities. Firms should review contracts to allocate risk, ensure auditability, and maintain strong documentation. Proactive compliance reduces litigation risks and enhances resilience.
