As the European Union’s landmark AI Act enters the second year of its phased 24-month rollout, businesses across the continent are bracing for sweeping changes in how they develop, deploy, and monitor artificial intelligence. The legislation categorizes AI systems by risk and sets strict obligations for transparency, governance, and accountability.
For Cordell Robinson, CEO of Brownstone Consulting Firm (BCF), the stakes could not be higher. “If you don’t adopt AI governance and you’re implementing AI into your environments in the EU, you’re allowing sensitive data on the internet without any guardrails,” Robinson warns. “That data could be reused for malicious purposes, and many organizations aren’t thinking about those consequences. They just see AI as a way to make things faster and more efficient. But governance has to come first.”
According to Robinson, European firms face three immediate pressure points as the Act unfolds.
The first one being interpreting risk classifications. The Act’s four-tier framework: unacceptable, high, limited, and minimal risk, will require organizations to map their AI systems accurately. “The challenge,” Robinson notes, “is that many AI systems are multi-purpose or evolve dynamically. Misclassification could mean huge fines. Companies must get this right early.”
Robinson further emphasizes the importance of building governance infrastructure. High-risk AI applications will demand governance processes that few European companies currently have: risk assessments, documentation of training data, human oversight, and incident reporting. “Standing up compliance teams and workflows in under a year is not realistic for most firms,” Robinson says. “But they can’t afford to delay.”
Perhaps the most visible change will be data transparency requirements. Companies will have to disclose where training data came from and how it is safeguarded. Robinson sees this as a positive development rather than a burden. “Transparency protects both the client and the consumer. If something goes wrong, everyone knows what data was used, and they can respond appropriately. Without it, you’re left in the dark.”
The broader challenge, Robinson argues, is cultural. Europe is trying to regulate without stifling innovation. “The key is to be proactive rather than reactive,” he explains. “Bake security and compliance into AI from the very beginning, just like the software development lifecycle. That way, when the regulatory requirements hit, you’re already ahead instead of scrambling to retrofit compliance.”
Robinson believes the EU can learn from U.S. frameworks such as NIST’s AI Risk Management Framework, FISMA, and HIPAA. These have supported U.S. organizations with structured baselines for cybersecurity and data protection. “Using frameworks like NIST gives companies a starting point,” Robinson says. “You’re not starting from zero. You have a barometer to build from, which makes governance far more achievable.”
But he also cautions against the critical mistake Europe should avoid: failing to train its workforce. “One of the biggest gaps I’ve seen is the implementation of proper training of staff on the safe use of AI,” he stresses. “Policies and frameworks are meaningless if your teams don’t understand how to implement them. Europe should heed that warning and prioritize training now.”
The EU AI Act represents a bold step toward trustworthy AI, but Robinson underscores that success will hinge on execution. Companies that wait to act risk falling behind both in compliance and competitiveness. “AI is moving at breakneck speed,” he says. “European firms that integrate governance, transparency, and training now will not only avoid regulatory pitfalls but also position themselves as leaders in responsible innovation.”
For Robinson, the message is clear: proactivity is protection: for businesses, for consumers, and for the future of AI in Europe.
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