Anticipating the EU AI Act - What Every Business Should Ask Itself Today

13 March 2024
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The EU AI Act has arrived... EU Commissioner Thierry Breton might say it's a 'spearhead' for AI development, and who are we to argue? After all, we've seen how GDPR turned data governance from a 'nice-to-have' to a 'must-have' overnight. Will the EU AI Act do the same for AI governance? Too soon to answer this right away. Critics are already voicing concerns, fearing the Act could be the 'speed bump' on the AI innovation highway, especially as we're already playing catch-up with the US and China.

In essence, we're at a crossroads: do we wait for regulations to guide us, or do we start asking the hard questions now? We believe any organization can benefit from a dedicated AI strategy which will be the trigger for AI governance further down the road. In this blogpost we want to encourage management to act proactively on AI discussions.

The parallel with GDPR is not just coincidental but instructional. Remember the GDPR frenzy? It shifted data governance from the backrooms of IT departments to the forefront of global business strategy. We can anticipate a similar seismic shift with AI governance. The question isn't whether AI will influence your business; it's about how well-prepared you are to integrate it ethically, transparently, and effectively.

Why is AI Governance important?

In this new AI-governed world, ignorance isn't bliss – it's a liability. Think of AI governance as the compass guiding your AI initiatives through the choppy waters of ethical dilemmas, regulatory compliance, and public scrutiny. This oversight is crucial because if AI models are developed with inaccurate data or unethical principles, the consequences can be significant and detrimental. Is our AI transparent enough for us to explain its decisions in a courtroom, or is it a 'black box' even to our own teams? In essence, embracing AI governance is not just about compliance; it's about gaining a competitive edge and fostering trust with your stakeholders.

For instance, an AI system designed for (semi-)automated hiring, if trained on biased data, could perpetuate workplace discrimination, leading to unfair hiring practices and a lack of diversity, and ultimately lower financial performances. Conversely, when AI is developed with accuracy and ethical integrity, its impact can be profoundly positive.

AI Governance Prep: Key Questions to Consider

As we recognize the vital role of AI governance in steering the future of technology, it's crucial to first ponder key strategic questions that will shape our approach and ensure we're aligning with both ethical and business objectives. What are the key questions that management should ponder to ensure their AI strategies are not only compliant but also competitive and ethical?

The following questions serve as a beacon for navigating this uncharted territory, before diving into AI governance:

  • Purpose and Integration: “What role does AI play in our business?” This question is about understanding the depth of AI’s roots in your processes. It's not just about having AI; it's about how deeply it's woven into your operations, meeting customer needs, and impacting various components of the value chain.
  • Ethical Alignment: “Does our AI reflect the ethical baseline of our company?” Rethink AI not just as a technological tool, but as a reflection of your company's moral compass. It's essential to ensure that your AI initiatives don't just tick boxes for efficiency and innovation, but also resonate with the ethical standards and societal values your company upholds.
  • Financial Impact: “How much of our revenue is tied to AI, and what's the future potential?” This is about gauging the financial pulse of your AI initiatives. This demands an assessment of AI's role in your revenue streams, more importantly as the AI EU Act might impact up to 7% of your global revenue if there is non-compliance.
  • Practical Examples: “What are the existing and future AI solutions that are adding value to our organization?” If there are none, delve into why and what the barriers are. It’s about learning from the ground realities, celebrating successes, and understanding failures.

The answers to the above questions are prerequisites for building your AI governance framework, and ultimately trying to answer the question “Do we have a framework to address the issues of bias, security, transparency in our AI?” This is crucial in building 'trusted AI' – a system that earns the confidence of both internal stakeholders and the external world. If interested, detailed frameworks and tools can already be found online to give the nudge in the right directions (e.g.: The EU AI Act will give us similar types of frameworks in the near future.


In conclusion, the EU AI Act marks a pivotal moment for AI governance, akin to the transformation GDPR brought to data governance. However, we believe it's crucial for organizations to recognize the importance of proactive AI strategy development. Remember, in the fast-evolving landscape of AI, standing still is not an option; proactive engagement and continuous adaptation are key. This means not just waiting for regulations to set the path but starting to integrate AI ethically, transparently, and effectively into business practices now. The key lies in asking the right questions now: understanding the depth of AI integration in business processes, aligning AI initiatives with ethical standards, evaluating the financial impact, and understanding the (future) practical applications of AI within the organization.

In need of some additional advice on the matter, do not hesitate to contact our experts. In our next blog post, we'll delve into real-world AI governance use-cases we're developing with our clients. If you do not want to miss this one, you better sign up for our newsletter!