The legal ground beneath AI-powered products is moving faster than most UK founders have time to track. If your business embeds a third-party model, whether that’s OpenAI’s API, Google Gemini, Anthropic’s Claude, or any of the growing roster of specialised models, into a client-facing product, you are almost certainly carrying liability you have not fully mapped. That is not a scare tactic. It is what I keep hearing from solicitors, product leads, and compliance officers across the UK tech space in 2026, and the gap between commercial ambition and legal readiness is widening.
This piece is a practical briefing, not an academic survey. I want to give UK tech founders and product managers a working picture of where the AI liability framework stands right now, what the key bodies are doing, and which contractual clauses in your API agreements deserve a second look before your next product launch.
Why AI liability is different from ordinary software liability
Traditional software liability is reasonably well understood. A supplier provides a tool; if it fails to perform as specified, you pursue remedies under contract or, in consumer contexts, the Consumer Rights Act 2015. The chain of responsibility is traceable.
AI systems break that chain in ways the existing legal framework was not built to handle. A large language model does not execute deterministic logic. It generates outputs probabilistically, which means the same input can produce different results on different occasions, and neither you nor the model provider can fully predict every edge case. When a model gives a client inaccurate medical advice, fabricates a legal citation, or produces discriminatory output, who is responsible? The model developer? The business that embedded the API? The platform that hosts the end product? Right now, UK law does not give a clean answer to any of those questions.
What the Law Commission is actually working on
The Law Commission of England and Wales has been examining automated decision-making and the liability questions it generates for several years. Its work on AI and civil liability touches on whether existing tort law concepts, negligence, product liability under the Consumer Protection Act 1987, and contractual duty of care, are adequate for AI-generated harm.
The short answer from the Commission’s published scoping work is: not quite. The 1987 Act’s definition of “defective product” was written for physical goods. Software-as-a-service sits awkwardly within it, and a probabilistic AI model sits even more awkwardly. The Commission has flagged that a new statutory framework may ultimately be required for AI systems that cause harm, particularly in high-risk sectors such as healthcare, legal services, and financial advice. No final recommendations have been enacted as legislation yet, but the direction of travel is clear: UK regulators intend to assign clearer chains of accountability, and the businesses closest to the end user will face more scrutiny, not less.
Ofcom’s expanding remit and what it means for AI products
Ofcom’s role in this space is often misunderstood. Its primary mandate under the Online Safety Act 2023 centres on user-generated content and platform safety duties. But Ofcom has been explicit that AI-generated content falls within scope when it appears on regulated services, and its technical guidance increasingly references the risks posed by AI systems that surface harmful outputs to users.
If your product is a regulated service under the Online Safety Act, and many SaaS tools with user-facing content features are, then the AI outputs your system generates or facilitates are subject to the same safety duties as user-generated content. Ofcom’s enforcement powers include substantial fines, and the agency has made clear it will not accept “the model did it” as a defence. The business deploying the model to end users carries the compliance obligation. I’ve written previously about how FCA Consumer Duty obligations sit on the product designer, not just the financial institution behind it, the logic is exactly parallel here.
Reading the indemnity clauses in your API terms
This is the part most founders skip, and it is genuinely consequential. Every major AI model provider includes indemnity and liability limitation clauses in its API terms. The specific language varies, but the common pattern is worth understanding.
First, providers typically disclaim liability for model outputs. OpenAI’s terms, for instance, make clear that outputs may not always be accurate, and the developer using the API takes responsibility for how those outputs are deployed. Second, indemnity clauses usually flow one way: you indemnify the provider against claims arising from your use of the API, not the other way around. Third, most agreements cap the provider’s total liability at the fees you paid in the preceding twelve months. If your product causes £500,000 worth of harm to a client based on a flawed model output, the model provider’s contractual exposure might be capped at a few hundred pounds.
That exposure gap sits with you. Which means your own terms of service, your professional indemnity insurance, and your product liability framework need to close it, or explicitly exclude liability in ways your clients understand and agree to. For businesses in regulated sectors, that exclusion may not even be legally permissible under the Unfair Contract Terms Act 1977 or the Consumer Rights Act 2015.
I’d strongly suggest getting a technology solicitor to review your API agreement and your own downstream client terms together. The mismatch between the two is often where founders find the most uncomfortable surprises.
The public discourse question: who is tracking this?
One thing that struck me while researching this piece is that the conversation about AI accountability has moved well beyond specialist legal publications. General-interest outlets are increasingly covering the liability and accountability dimensions of AI deployment in plain language, which matters because your clients are reading those sources too. Sites like tazamo.co.uk are part of a growing ecosystem tracking public discourse around AI accountability outside the specialist press, and that means non-technical stakeholders, procurement leads, board members, end clients, are arriving at conversations with you already primed on the risks. That is a shift worth preparing for.
It is also worth noting that consumer expectations around AI outputs are hardening. The ONS has reported growing public concern about AI accuracy and data use, and that sentiment feeds directly into how clients will respond when something goes wrong with your product.
Practical steps to reduce your exposure now
Legislation will eventually catch up. In the meantime, here is what I’d prioritise if I were running a UK product team using third-party AI models today.
Conduct a liability audit of every API agreement you are party to. Note what the provider disclaims, what the liability cap is, and what indemnity obligations you have accepted. Map those gaps against your own client contracts. If your client terms offer guarantees that your API terms explicitly disclaim, you have a problem that needs fixing before you have a claim.
Review your professional indemnity and product liability insurance policies specifically for AI-related coverage. Many standard PI policies were written before AI outputs became a mainstream product feature, and some exclude losses caused by automated decision-making systems. An insurance broker with technology sector experience is the right person to help here.
Document your human oversight mechanisms. Both the emerging regulatory framework and existing negligence law favour organisations that can demonstrate they did not blindly relay AI outputs to end users. If your product includes a human review step, log it. If it does not, consider whether it should. This connects directly to how teams are already thinking about using AI assistants responsibly to augment professional judgement rather than replace it.
Keep an eye on the Law Commission’s forthcoming outputs and on any secondary legislation under the Online Safety Act that touches AI-generated content. The ICO has also published guidance on AI and data protection that intersects with liability questions, particularly around automated decision-making under UK GDPR Article 22.
None of this needs to slow your product development down significantly. But treating AI liability as a “later problem” is the kind of decision that tends to look very different in retrospect. The businesses that get ahead of this framework now will find the compliance conversation much easier when regulation firms up. And if you’re curious how parallel questions of lifestyle, culture, and commercial identity are playing out in entirely different sectors as the UK adapts to rapid change, the piece on how outdoor living trends are reshaping British consumer identity is a reminder that accountability and public discourse shift across every industry at once.
The legal framework for AI liability UK businesses operate within is incomplete but not invisible. The signals are there. Reading them now is the sensible move.