Your Business Guide to AI Compliance in 2026

In 2026, artificial intelligence no longer feels like a specialist technology issue reserved for innovation teams. For most businesses, it is at the centre of how decisions are made, customers are managed, risks are assessed and products are delivered. That shift is forcing regulators, courts and boards to confront the same question: how do you enable innovation at scale without losing control?

From a legal perspective, 2026 marks an inflection point. The debate has moved on from whether AI should be regulated to how businesses can operate lawfully and responsibly in an environment where the rules are developing at different speeds across jurisdictions. For organisations operating in the UK and EU, the challenge is not simply understanding individual laws, but navigating how they interact in practice.

We will explain what businesses should expect from AI regulation in 2026, where the legal risks are crystallising, and how organisations can approach compliance in a way that supports growth rather than stifles it.

Different Approaches to AI Regulation

AI regulation is developing in different ways around the world. Some countries are prioritising speed and innovation, while others are putting detailed legal frameworks in place to control how AI is built and used. For UK and EU businesses, the practical takeaway is straightforward, regardless of approach, regulatory scrutiny of AI is increasing and will continue to do so in 2026.

The EU has adopted the most structured model. Its AI regulatory framework is already in force, with requirements coming into effect in stages. While some of the detail is still being refined to ensure the rules are workable for businesses, the overall approach is settled. AI systems are assessed by reference to the level of risk they pose, and those considered higher risk are subject to stricter obligations. These include requirements around governance, transparency, data quality and human oversight. In practical terms, this means that using AI in the EU increasingly feels like bringing a regulated product to market, with an expectation of clear documentation, testing and senior accountability.

The UK has taken a more flexible route. Rather than introducing a single AI law, it continues to rely on existing regulation, with sector regulators applying those rules to AI use in their areas. Data protection, financial services, consumer law and competition rules are all being used to shape how AI can be deployed. While the government has indicated that AI-specific legislation may be introduced in future, it is unlikely to mirror the EU’s approach. Instead, businesses should expect clearer guidance from regulators, more consistency between them and a tougher response where AI causes real harm.

For organisations operating across borders, this creates a balancing exercise. Activities linked to the EU may need to meet detailed, formal requirements, while UK operations must still meet principles-based expectations that carry real enforcement risk if they are not taken seriously.

Intellectual Property: Uncertainty That Businesses Cannot Ignore

Intellectual property remains one of the most challenging legal issues in the AI space, and that uncertainty is set to continue into 2026. Much of the focus remains on copyright, particularly in relation to the data used to train AI systems and the status of AI-generated outputs.

In the UK, further guidance is expected on how copyright law applies to AI training and whether changes are needed to strike the right balance between rights holders and AI developers. There is also likely to be more clarity on whether AI-generated content attracts copyright protection at all, and who may be liable if that content infringes third-party rights. Ongoing litigation involving generative AI providers has brought these questions into sharp focus and underlines that the risks are very real.

Similar debates are taking place in the EU. Courts and policymakers are considering how rights can be reserved from text and data mining, and how existing copyright rules apply to large-scale AI systems. Decisions expected over the next year or two are likely to influence how AI models are trained, where that training takes place and how AI supply chains are structured.

For businesses, the key point is that IP risk cannot be outsourced away. Even where AI tools are purchased from third parties, organisations using them may still be exposed if outputs infringe copyright or if training practices are challenged. Clear contracts, sensible usage policies and proper due diligence will remain essential throughout 2026.

Data Protection: More Room to Innovate, Less Tolerance for Mistakes

Data protection law continues to play a key role in shaping how AI can be used. Regulators in both the UK and EU are keen to support innovation, but they are equally clear that AI systems must not operate in ways that unfairly or unlawfully affect individuals.

In the UK, changes to data protection law are expected to take effect in early 2026. These reforms are intended to give organisations more flexibility when using AI, particularly in relation to automated decision-making, while keeping strong safeguards in place for higher-risk uses. Alongside this, the Information Commissioner’s Office is updating its guidance and developing a dedicated AI code of practice, aimed at giving businesses clearer and more practical direction.

In the EU, data protection authorities are working to clarify how GDPR obligations sit alongside AI-specific regulation, particularly for higher-risk systems. While guidance is being developed, enforcement activity is also increasing. Regulators are focusing not only on AI developers, but on organisations that deploy AI in ways that affect individuals’ rights and freedoms.

As such, businesses using AI at scale should expect closer scrutiny, especially where systems are automated, difficult to explain or capable of producing biased or harmful outcomes.

Litigation Risk 

As AI becomes part of everyday business operations, the risk of disputes is growing. The same features that make AI powerful, speed, scale and autonomy can also amplify mistakes when things go wrong.

We are already seeing claims linked to inaccurate or misleading AI outputs, errors being replicated across large datasets and a lack of meaningful human oversight. Regulators are also paying close attention to how AI is described to customers and investors. Overstating what AI can do, or how it is being used, is increasingly seen as a compliance risk in its own right.

One of the most difficult issues remains responsibility. When an AI system causes harm, liability may sit with the developer, the business using the system, or both. Understanding why an AI system reached a particular decision can be technically complex, particularly where models operate as “black boxes” or change over time. As courts begin to deal with these cases, their decisions will shape how risk is shared across the AI ecosystem.

Until that clarity emerges, businesses should assume that using AI does not reduce their responsibility. In many cases, it increases expectations around governance, oversight and control.

Why AI Compliance Is Now a Board-Level Issue

By 2026, AI compliance can no longer be treated as a narrow legal or technical issue. For many organisations, it has become a core governance challenge. Boards are increasingly expected to understand where and how AI is used within the business, what risks it creates and how those risks are being managed.

A common issue we see is fragmented compliance. Data is spread across teams, risk information sits in silos, and AI tools are added to systems that were never designed to support them. In that environment, AI can undermine good decision-making rather than improve it.

Effective AI governance requires a more joined-up approach. Data, risk and compliance processes need to work together, with clear accountability and escalation routes. Just as importantly, boards and senior leaders need to stay engaged and informed. AI is evolving too quickly for static policies or one-off training to be enough.

How EU Initiatives Translate into Practical Compliance Steps 

For businesses operating in the EU, 2026 marks a stage where AI compliance is no longer abstract, the EU is providing concrete tools and support to make it achievable. The EU’s approach is built around two complementary goals: creating a culture of innovation and ensuring AI is safe, trustworthy, and aligned with societal values.

The AI Act remains the central regulatory framework, categorising AI systems by risk and setting clear obligations for developers, deployers, and users. In practice, this means that companies must identify which of their AI applications are high-risk, for example, tools affecting critical decisions in healthcare, finance, or public services, and implement governance measures accordingly. Transparency, human oversight, data quality, and risk assessment are no longer optional.

What makes compliance more manageable is the EU’s practical support ecosystem. Businesses can now access guidance through the AI Act Service Desk, which helps clarify obligations and provides answers to common operational questions. Codes of practice, sector-specific guidelines, and the emerging AI Observatory give companies insight into how AI is being regulated and applied across different industries. For those unsure how to begin, the EU encourages participation in sandbox programs, which allow companies to trial AI systems under regulator supervision.

Beyond regulation, the EU has launched initiatives aimed at helping businesses integrate AI responsibly. Programs such as the AI Continent Action Plan and the Apply AI Strategy focus on encouraging AI adoption in strategic sectors, particularly among small and medium-sized enterprises. These initiatives offer access to high-quality data, computing infrastructure, and collaborative innovation networks, meaning that compliance can be paired with practical business growth and efficiency improvements. Participating in initiatives like GenAI4EU, for example, allows businesses to develop generative AI solutions while aligning with EU standards from the outset.

From a practical perspective, EU businesses in 2026 should consider several concrete steps. First, map all AI applications and classify them according to the AI Act’s risk levels. Second, document governance measures for high-risk AI systems, including testing, validation, and human oversight processes. Third, take advantage of EU support services from the AI Act Service Desk to public-private collaborations and sector-specific sandbox programs to ensure that compliance measures are robust, realistic, and up to date. Finally, integrate compliance into broader operational planning, using AI adoption programs not just as regulatory boxes to tick but as tools to improve processes, products, and services.

In short, EU regulators have shifted from issuing abstract rules to offering practical support, making 2026 the year when businesses can realistically comply while also harnessing AI to create value. Those that take a structured approach, combining risk assessment, documentation, and participation in innovation programs, will be best positioned to operate safely, confidently, and competitively.

AI Compliance Predictions for 2026

It is becoming increasingly clear that AI is no longer a peripheral concern for businesses, it is a core compliance issue that boards and senior leadership must take seriously. Based on current regulatory trends and industry developments, several predictions can be made about what AI compliance will look like this year.

1. Stronger enforcement and clearer expectations

Both EU and UK regulators are shifting from guidance to active oversight. In the EU, the phased implementation of the AI Act, supported by the AI Continent Action Plan and initiatives like the AI Act Service Desk, means that businesses now have both clarity and accountability. High-risk AI systems will attract close scrutiny, and regulators will expect documented governance, testing, human oversight, and risk mitigation. In the UK, although regulation remains principles-based, the combined effect of the Data (Use and Access) Act, sector-specific guidance, and cross-regulator cooperation means that businesses will increasingly face targeted audits and enforcement action if AI use causes harm.

2. Integration of compliance into business operations

AI compliance in 2026 is not just a legal or technical exercise, it will be deeply operational. Organisations will need to integrate risk assessments, data governance, and audit trails directly into business processes. Fragmented data systems and siloed compliance functions will become unsustainable as AI adoption increases. Companies that embed compliance into core operations, using tools such as sandboxes, AI observatories, and internal governance frameworks, will be better positioned to both innovate and defend against regulatory scrutiny.

3. Intellectual property disputes will rise

AI-generated content and the use of copyrighted material for AI training remain legal grey areas. UK courts are expected to clarify ownership and liability for AI outputs in ongoing and upcoming cases, while the EU continues to refine rules around text and data mining rights. Businesses deploying AI must proactively manage IP risk through robust contracts, internal policies, and due diligence on third-party AI tools. Ignoring IP considerations will no longer be defensible in 2026.

4. Data protection will remain central

Data remains the lifeblood of AI systems, and regulators are focused on ensuring its responsible use. While reforms in the UK will allow greater flexibility for automated decision-making, and EU guidance will help align GDPR with AI-specific rules, regulators will continue to expect rigorous safeguards, particularly for high-impact AI applications. Organisations using personal data at scale must maintain transparency, document lawful bases for AI processing, and be prepared for potential audits or enforcement action.

5. Liability questions will persist

As AI becomes embedded in decision-making, questions of legal responsibility are coming to the forefront. Businesses will need to be prepared for disputes where AI systems produce inaccurate outputs, replicate errors at scale, or are misrepresented externally. Senior leaders should assume that liability may extend across developers, deployers, and even third-party suppliers, making governance, validation, and oversight more important than ever.

6. Compliance as a competitive advantage

Finally, 2026 is likely to see businesses that approach AI compliance strategically turning it into a source of competitive advantage. The EU’s Apply AI Strategy, GenAI4EU initiative, and supportive infrastructure for SMEs show that compliance and innovation can go hand in hand. Organisations that align with regulatory expectations while responsibly deploying AI will benefit from greater trust, stronger reputation, and more efficient, safe operations.

In short, AI compliance in 2026 will be defined by proactive governance, integrated operational processes, and senior accountability. It is clear that those who wait for rules to change or treat compliance as an afterthought will face not only legal and regulatory risk but reputational and operational consequences as well.

How Can Gerrish Legal Help?

Gerrish Legal is a dynamic digital law firm. We pride ourselves on giving high-quality and expert legal advice to our valued clients. We specialise in many aspects of digital law such as GDPR, data privacy, digital and technology law, commercial law, and intellectual property. 

We give companies the support they need to successfully and confidently run their businesses whilst complying with legal regulations without the burdens of keeping up with ever-changing digital requirements. 

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