AI Governance: Strategic Imperative —Not a Tick-the-Box Exercise

In the last weeks, I’ve noticed a significant shift in mindset—there’s a real sense that the countdown to compliance with AI regulations has truly begun. This is not a surprise given that, according to Accenture, 95% of leaders believe their business will be impacted by regulations like the EU AI Act.

As a result, many organizations are evaluating AI governance platforms to perform their AI inventory and prepare for the upcoming obligations on prohibited systems, effective February 2025.

These platforms are a great way to streamline compliance processes, perform AI governance assessments (as we do with our AI Governance Readiness Tools at Safe AI Now), implement systematic controls, and monitor risks at the AI system level.

However, while AI governance platforms play a crucial role in streamlining and operationalizing controls, they should be implemented in parallel with foundational efforts such as aligning organizational strategy and defining risk management frameworks.

The groundwork for AI governance involves not only deploying these platforms but also building a clear governance structure, accountability framework, and ethical alignment. The combination of these prerequisites and the use of governance platforms will ensure a seamless integration of AI governance across the organization.

AI governance isn't just about checking off compliance boxes; it’s a strategic framework that impacts how you innovate, manage risks, and maintain accountability across your organization. Governance platforms are important for accelerating compliance, but they should go hand in hand with internal alignment and strategic decision-making.

During the initial phase of experimentation, many companies have started to identify and mitigate risks within individual AI systems. However, are these efforts consistent across the organization? Have we clearly defined who is accountable when things go wrong? Are we evaluating the long-term benefits, ROI, and risks of AI investments consistently across different business units?

Implementing controls within AI systems requires a comprehensive approach to scaling AI governance, making it an integral part of your organizational fabric. If not done properly, this can quickly become a bottleneck to innovation.

Here are a few key prerequisites to streamline AI governance effectively:

1. Speak the Same Language Across Departments: IT and legal teams need to align on a shared understanding of regulations before jumping into the implementation of controls. AI regulations, like the EU AI Act, are often principle-based, so context and interpretation matter.

2. Evaluate Accountability and Responsibility: Who is responsible for AI governance, and what are the escalation processes? You need a clear, organization-wide risk management structure in place before diving into operational controls.

3. Conduct an AI Governance Readiness Assessment: Tools like those developed by Safe AI Now can accelerate this process by helping you identify key risks and areas that need attention. But remember, the tool is only as good as the strategy behind it.

4. Establish a Risk Management System at Scale: AI governance isn’t about managing AI systems in isolation and providing a list of controls. It’s about embedding risk identification, reporting, and incident tracking throughout the lifecycle of your AI systems. By adopting a risk-based approach, you can ensure consistency across AI use cases while applying proportionality to focus your efforts on high-risk areas.

5. Align AI with Ethics and Corporate Strategy: While a platform can support compliance, it won't solve ethical challenges or ensure that AI aligns with your broader business goals.

Incorporating these steps alongside governance platforms will prevent your AI governance efforts from stifling innovation and ensure that your organization is fully prepared to meet both regulatory and ethical demands.

AI governance platforms are essential tools, but they must be paired with a broader strategic approach, including accountability, clear risk management and ethical alignment.

By managing both in parallel, you can build a governance framework that not only ensures compliance but also supports long-term success.