Best practices for your AI governance framework
Posted on September 2, 2025 by Dan May
Organisations increasingly rely on AI to automate tasks and optimise workflows.
A clear AI governance framework needs to be established so that these systems are reliable, compliant with institutional and governmental regulations, and used in an ethically responsible manner.
This article outlines AI best practices, defining the role of AI and who is accountable for output, managing data and the risk associated with using AI models while meeting regulatory requirements.
What is an AI governance framework?
AI governance is the framework of policies and processes that guide how artificial intelligence is developed and used. The aim is to make sure it’s used safely and ethically, in a way that benefits people, reducing the risk of harm and misuse. This begins with a human-centred mindset. AI should serve to enhance human wellbeing, preserve dignity, and protect fundamental rights. An effective framework ensures that AI supports people first, never replaces the need for human values and empathy.
It usually covers:
- Ethics and principles – Defining the values AI should respect (fairness, transparency, accountability, privacy, human oversight).
- Policies and standards – Setting internal rules, legal compliance, and industry guidelines for how AI is built and used.
- Risk management – Identifying and guarding against the potentially damaging aspects of AI (bias, security vulnerabilities, misuse).
- Accountability structures – Assigning responsibility for AI decisions, from developers, all the way up to leadership.
- Transparency & clarity – Ensuring AI decisions can be understood and challenged.
- Monitoring & auditing – Continuously checking that AI systems behave as intended and remain compliant over time.
In practice, an AI governance framework can mean anything from a company’s own ethics policies and bodies to complying with laws and regulatory standards like the EU Artificial Intelligence Act.
The goal is to make sure AI is beneficial and trustworthy rather than becoming a potentially damaging power acting without protection and oversight.
What makes AI governance so challenging?
AI governance is difficult because it sits at the crossroads of technology, ethics, law, and business strategy, and all of these areas are evolving at high speed because of AI. Beyond the technical and legal hurdles, organisations must also consider AI’s broader societal consequences, from economic disruption to misinformation and environmental impact. Responsible governance means thinking not just about internal compliance, but about how AI systems influence the world around us.
Unlike traditional IT systems, AI models learn and adapt, which means their outputs can change over time – sometimes in a way that’s hard to predict. This means every time your business uses AI, it risks crossing the lines around bias, transparency, and accountability.
Other challenges when creating a reliable AI governance framework include:
- Regulatory uncertainty – Laws on AI are still emerging and differ widely by region. For example, the EU AI Act has different compliance requirements than the US executive orders .
- Complexity of AI systems – Many models operate as “black boxes,” — AI models that have complex algorithms but struggle to explain how it obtains certain answers — making it hard to explain decisions or detect errors.
- Data quality and provenance – Poor or incomplete data can produce flawed results, while tracking data sources to ensure they’re correct and verified is extremely challenging.
- Organisational silos – AI projects often span multiple departments, each with a different goal. This can hugely complicate how AI systems are aligned with the business as a whole.
What are the benefits of an AI governance framework?
When done well, AI governance isn’t just about risk mitigation — it’s a driver of business success. It sets the framework for reducing manual tasks and improving cost efficiently in a way that’s ethical and profitable.
Here’s why businesses should develop their own AI governance framework:
- Trust and reputation – Businesses need to cater to many people, whether it be stakeholders, customers, regulators and governments. Having an AI governance framework in place means all parties are more likely to trust you as you’re taking steps to show compliance.
- Regulatory readiness – As AI governance frameworks adapt and catch up, being ahead of the game demonstrates you are an effective and ethical user of AI – no matter what sector your business is in.
- Better decision-making – By ensuring AI systems are transparent and fair, you improve the quality of AI decisions and can therefore justify them more effectively should you need to.
- Innovation with confidence – Strong governance enables you to scale AI use across the business without losing control, unlocking new efficiencies and products.
- Competitive advantage – Responsible AI can differentiate your brand in crowded markets.
What are the key principles of an AI governance framework?
While every organisation’s approach will vary, the most effective AI governance frameworks are based on a few core principles:
- Transparency – Ensures AI decisions can be explained in clear, accessible terms.
- Fairness and non-discrimination – Designs and monitors systems to avoid bias against individuals or groups.
- Accountability – Defines clear roles and responsibilities for AI outcomes, from developers to business leaders.
- Privacy and security – Protects personal data in line with laws and best practice, and secure models against tampering.
- Human oversight – Keeps people in the loop and provides oversight for high-impact or high-risk decisions.
- Continuous monitoring – Regularly reviews AI systems for accuracy, fairness, and compliance over their lifecycle.
What are the best practices for your AI governance framework?
If you’re building or refining your AI governance model, consider the following best practices:
- Start with a risk assessment – Identify where AI is used (or planned) and rank use cases by potential impact. This lets you decide where and what you can use AI for and find the areas and sectors that are more in need of regulation.
- Create a governance board – Business experts are always best positioned to understand the impact of AI in their line of work. When establishing a governance board, include representatives from legal, compliance, and IT, as well as other departments like marketing and senior leadership. To ensure your framework is inclusive and avoids systemic bias, it’s important to involve diverse voices in your governance structure, across gender, race, lived experience, and function. This broader representation helps uncover blind spots and build systems that better serve all people.
- Develop clear policies and documentation – Business processes need to be documented – not only to help employees follow protocol, but as evidence for regulators and officials as rules change. This should cover AI development, deployment, monitoring, and retirement processes.
- Invest in explainability tools – AI outputs and their justifications are inherently complicated. It may be worth investing in technology that can make AI outputs interpretable to non-technical stakeholders, customers and employees.
- Train your teams – Ensure staff understand the risks, benefits, and responsibilities of working with AI.
- Plan for audits – As AI legislation changes, so does the process for establishing compliance. Businesses that regularly use AI – or are gearing up to integrate it into their workflows – should conduct regular internal and external reviews to test compliance and performance.
Responsible AI is not just about managing risks, but about ensuring that AI serves humanity equitably. By embedding inclusive values and societal impact assessments into your AI governance framework, organisations can make sure that AI truly supports wellbeing across communities. This is the foundation of the Global Council for Responsible AI’s mission, and we believe it’s where good governance begins.
Can ramsac help your business develop an AI governance framework?
At ramsac, we have many years of invaluable experience supporting customers get ready for AI regulation.
Our team also offers AI readiness assessments as well as consulting and training solutions to help your business navigate changing times.
Contact us today to find out how our solutions can protect your organisation from changing AI regulations and stay compliant.
