Governance and Regulation 

This guide offers clear, practical advice to help SMEs in Scotland understand and prepare for AI regulation and governance. It's designed to help you meet compliance and ethical standards without losing focus on business growth and innovation.

The current landscape

AI regulation in the UK is still evolving. The Artificial Intelligence Bill, reintroduced in the House of Lords in March 2025, currently lacks government backing and is unlikely to pass in its current form. Meanwhile, the UK government has delayed formal discussions on AI legislation until mid-to-late 2025, suggesting it may align more closely with US regulatory approaches than the EU’s.

This guide outlines best practices based on the current environment, helping you stay one step ahead. As the regulatory picture develops, keeping up to date will be key to staying compliant.

1. Understanding the UK's approach to AI regulation

For the time being, the UK is taking a flexible, sector-led approach to regulating AI, applying existing laws rather than introducing new ones immediately. This could continue if the UK aligns more closely with the US model.

The current framework applies existing regulatory structures to AI, recognising that specific legislation will eventually be necessary, particularly for advanced AI systems.

Unlike the EU’s AI Act, which introduces centralised, risk-based rules, the UK assigns responsibility across existing regulators (such as the Financial Conduct Authority and the Information Commissioner's Office). This decentralised model gives businesses, especially SMEs, more room to adapt and innovate, while still promoting ethical AI use.

This approach is deliberately focused on outcomes, allowing businesses to remain agile and innovative while meeting core ethical requirements. It aims to position the UK as a safe, agile, and attractive place to develop and deploy AI.

2. The five core principles for AI governance

The UK government has outlined five core principles to guide responsible AI use across all sectors. These principles are already being used by regulators to shape expectations:

Safety, security and robustness

AI systems should operate reliably (as intended) while minimising harmful consequences. Your systems should anticipate potential threats like hacking and incorporate appropriate security measures. For SMEs, this means conducting regular testing and implementing cybersecurity best practices for any AI tools you deploy.

Appropriate transparency and explainability

You should be able to provide clear explanations of how your AI systems make decisions. This includes documenting development processes, capabilities, limitations, and actual performance. In practice, this means maintaining records of how AI tools work and being able to explain outcomes to customers or regulators when needed.

Fairness

Your AI systems must treat all individuals and groups impartially and without bias. This requires regular evaluation for potential bias and transparency around decision-making processes. For example, if you're using AI for customer service or recruitment, you should verify that it doesn't discriminate based on protected characteristics.

Accountability and governance

Your business remains responsible for the AI systems you implement and their impacts. This emphasises human oversight with appropriate governance measures to manage risks. You must assign clear responsibility for AI systems within your team and maintain oversight of automated processes throughout.

Contestability and redress

Individuals should be able to challenge automated decisions and access mechanisms to seek remedies when harm occurs. This means establishing clear processes for handling complaints about AI-driven decisions and providing alternatives when needed.

Regulators are expected to interpret and apply these 5 principles within their respective sectors, using existing laws and regulations to oversee AI development and use. For this reason, there will be differences in AI guidance, depending on who your principal regulator is.

3. Practical steps for strong AI governance

Whether you're just starting out or already using AI, these actions can help you implement responsible governance aligned with UK and international standards.

It's especially important to consider AI governance during the procurement phase as well as throughout its implementation, as these steps are closely linked and provide the necessary foundation for responsible governance.

Define a clear ethical framework

Start by identifying key ethical principles that reflect your business values, support your business goals and align with the UK’s five core principles. This doesn’t need to be complex, especially for smaller businesses.

 A good ethical framework should:

• Authentically reflect your core business values

• Address key risks and concerns (like data privacy or fairness)

• Be simple enough for everyone in your team to understand

• Adapt as your AI use grows and matures

Assign clear responsibilities

Addressing the complex nature of AI can often lead to recruiting new, skilled staff to better manage and oversee AI implementation and governance.

In smaller organisations, you don’t need a dedicated AI team, but you do need clarity. Appointing a data manager, an IT manager or another member of the senior team to oversee AI ethics and compliance helps keep accountability in-house, providing a single point of contact for any AI-related inquiries.

What matters is that they:

• Understand the risks and responsibilities

• Know who to report to

• Stay up to date on regulations and best practices

See our People and Culture guide for more information.

Keep track of regulatory changes

AI regulation is a moving target. To stay compliant:

• Follow updates to UK guidance and sector-specific rules (for example this regulatory tracker)

• Keep an eye on the EU AI Act and US developments, especially if you work across borders

• Subscribe to updates from your sector’s regulator

This consistent monitoring will help you stay in control of compliance requirements and to adapt your AI strategy accordingly.

Document what matters in a simple way

Well-organised records help with compliance, troubleshooting, and future audits. Keep straightforward, organised records of:

• What AI tools you use and how

• Where your data comes from

• When and how AI decisions are reviewed by humans

• When and how you test system performance

By maintaining clear records, you'll be better prepared to adapt to new regulations, troubleshoot issues and quickly demonstrate your compliance when needed.

Keeping this documentation also proves your commitment to responsible AI and prepares you for future requirements without creating unnecessary paperwork later down the line.

Check for bias regularly

Review your AI systems to spot and fix potential bias, especially if they interact with customers or make important decisions. You should:

• Test with diverse data that represents all of Scotland's population

• Review outcomes monthly for unexpected patterns

• Have a clear process for addressing problems

One of the most important steps is to examine how your AI systems perform across different demographic groups (looking for disparities in outcomes or error rates). Remember that biases can affect people across multiple categories.

Make AI decisions understandable

Make sure that your employees, customers and regulators can understand how your AI makes decisions. This means:

• Clearly explaining how and when AI is used in your business

• Providing ways for employees and customers to raise questions or complaints

• Offering alternatives for those who prefer not to use AI-driven services

This transparency is central to both current and future AI governance frameworks and builds trust with your customers and employees. 

Protect personal data

If your AI uses personal data, follow UK GDPR rules. Key practices include:

• Encrypting sensitive information

• Controlling who can access data

• Anonymising data where possible

• Keeping up with evolving privacy regulations

These measures help you comply with current regulations while preparing for expected, and more comprehensive, AI-specific data rules.

Review performance regularly

Set aside time each month or quarter to check how your AI systems are working.

• Are they still aligned with our values?

• Are there any unexpected results?

• Do they need adjustments to meet new standards?

Simple monitoring helps you stay compliant, adapting to new developments and improving system performance over time.

4. Support available for Scottish SMEs

Regulatory sandboxes

These are safe spaces where you can test AI tools with support from regulators. They offer:

• A controlled environment for testing

• Expert advice on compliance

• Temporary protection from penalties (if you follow the rules)

SMEs get priority access, making it easier to develop and use AI responsibly and manage regulatory risks. Some of them include: Responsible AI Sandbox from the Institute for the Future of Work, NayaOne for financial services institutions, Regulatory Sandbox developed by the ICO, AI Airlock for AI as a Medical Device products.

Collaboration and networking

Join Scotland's AI community through resources like the Scottish AI Playbook.

The AI Standards Hub – led by The Alan Turing Institute, BSI, and the National Physical Laboratory – also provides expert support and knowledge-sharing on AI standards, as well as practical tools and educational materials specifically designed for businesses.