What you need to know
- AI adoption is outpacing governance, and industry voices say we’ve lost control.
- Responsible AI adoption depends on greater oversight and clear accountability.
- You can take control by establishing a ‘governing body’ for AI in your organization.
- Your AI ‘governing body’ should evaluate, direct, and monitor how AI gets used.
- Taking structured steps towards AI governance can help you signal your responsible AI use to your customers, partners, and regulators.
Do you have control of AI?
AI adoption is fast outpacing governance and industry voices are saying we’ve lost control. Today, most organizations still lack a formal AI governance programme. And regulators are trying to keep up with a rapidly evolving technology without stifling innovation. This leaves you to navigate new risks and compliance challenges.
As AI takes on a growing role, your responsibility to control its use becomes greater.
Why does AI governance matter for your organization?
AI is becoming more central to key business functions.
It affects how products and services get created and delivered. It handles sensitive data and informs key business decisions. Generative AI may also be supporting your teams in an unofficial and uncontrolled way. For example, where employees use tools like ChatGPT to assist with research and content creation.
All of this means your workforce plays a direct role in how AI is being used in your organization. As a result, you need greater oversight, accountability, and encourage more engagement with its management and control. As AI develops and embeds in your organization, it needs the same level of governance as your core functions. From top management down.
By acting now, you can put governance structures in place that help you take control of AI use.
Four practical steps to build effective AI governance
Good governance reduces the risk of costly mistakes, such as privacy breaches and legal non compliance. And it helps you demonstrate responsible AI adoption to stakeholders, customers, and regulators.
Building good, effective AI governance starts with a small set of practical actions:
1. Own
Clear ownership and oversight are the foundation of effective AI governance.
Consider setting up a ‘governing body’ for AI in your organization. This does not need to be a formal board. For many organizations, a committee or simple cross functional group is enough.
What matters is that accountability for AI is clear. This group should understand your internal and external context, including business needs, regulatory requirements, and stakeholder expectations. From there, it provides ongoing oversight of AI use by evaluating risks, setting direction, and monitoring outcomes as AI evolves.
2. Evaluate
Know where AI is used and what risks it introduces.
You need a clear view of how AI affects your business. Your ‘governing body’ should regularly assess both the risks and benefits of AI use. This includes existing and proposed use cases. Ask whether they’re ethical and lawful. Understand how they use data, where that data comes from, and whether its quality is fit for purpose.
3. Direct
Clear rules and accountability help teams use AI responsibly.
Once you understand the risks, you can set clear direction. Define what acceptable and unacceptable use of AI looks like for your organization. Set expectations with management teams and provide practical guidance on how AI related risks should be managed. This guidance should reach the whole organization and evolve as technology and regulations change.
4. Monitor
Continuous monitoring enables improvement and builds confidence in AI outcomes.
Governance does not stop once AI is in use. You need to track AI performance and ongoing risks, monitoring incidents and emerging issues. This, in turn, will support continuous improvement and assurance.
If you’re looking for guidance to help you take these steps, international and industry standards provide a useful starting point for best practice. The international standard for information technology ISO/IEC 38507 covers AI governance, including the need to manage AI risk. While the specific standard on AI risk management, ISO/IEC 23894, offers a practical framework for how those risks get managed.
How do you confirm the effectiveness of your AI governance?
BSI’s modular AI Foundation Framework helps you take control of your AI adoption and prove it to stakeholders with independent verification based on the above standards.
Starting with the AI Governance module helps you take your first structured steps into AI governance. Building your capabilities and maturity through training, self-assessment, and verification. Leading to a BSI Mark of Trust that signals your commitment and progress to your customers, partners, and regulators.
