On 13 March 2025 the European Parliament adopted the world’s first horizontal legislation on artificial intelligence—the Artificial Intelligence Act (AI Act)—positioning the EU as a global standard-setter (European Parliament Council, 2025). Heralded as a landmark for trustworthy AI, the regulation creates a risk-tiered framework ranging from outright bans on “unacceptable-risk” applications to lighter transparency duties for minimal-risk systems.
Yet enthusiasm masks unresolved questions: Will the Act protect citizens without stifling Europe’s fragile AI ecosystem? Can regulators enforce such a broad instrument across 27 member states? This post takes a critical view of three pressure points—risk classification, governance capacity, and transatlantic competitiveness—and offers recommendations for practitioners in governance, risk, and compliance (GRC).
Risk Classification: A moving target
The Act’s entire edifice rests on classifying AI systems into four risk tiers. But “high-risk” criteria rely on open-ended concepts such as “significant impact on fundamental rights.” Empirical studies show experts disagree when labelling identical systems (Veale and Borgesius, 2021). Misclassification risks are two-fold:
Under-classification: Developers self-assessing their tools may downplay risk to avoid costly conformity assessment.
Over-classification: Fear of penalties may push firms to label most systems high-risk, triggering unnecessary audits and stalling deployment.
Bazzi Consulting’s recommendation
Organisations should establish cross-functional AI risk committees—combining data scientists, legal, ethics, and business leads—to calibrate risk ratings against evolving regulatory guidance and sector-specific standards (Floridi et al, 2022). These functions can be embedded into the Center of Excellence and Innovation, which is led by the Enterprise Architecture team and embeds all platform owners.
Governance Capacity: The Supervisor’s Burden
DORA and NIS2 already strained national authorities; the AI Act adds tech-heavy enforcement tasks, including algorithmic audits, incident reporting and post-market monitoring. Smaller member states face talent shortages: median public-sector salaries lag private AI salaries by 32 % (Viljanen 2025).
If supervisory capacity lags, firms will operate in a grey-zone of delayed guidance, breeding regulatory arbitrage.
Bazzi Consulting’s recommendation
Corporates should adopt internal model registers and voluntary red-team audits now, rather than waiting for over-burdened regulators to clarify. Early self-regulation reduces enforcement risk and demonstrates good faith.
Transatlantic Competitiveness: Innovation Chill or Catalyst?
US venture funding in AI exceeded Europe’s by a factor of six in 2024 (CB Insights 2024). Critics argue that onerous ex-ante obligations—especially around data governance and human oversight—could widen the gap (Crawford 2024). Proponents counter that legal certainty attracts risk-averse corporates and dismisses “move-fast-and-break-things” cultures.
Empirical evidence from GDPR suggests initial compliance costs are offset by long-run trust dividends (Goddard 2017). Whether the AI Act repeats that trajectory depends on regulators’ agility and on SMEs’ access to regulatory sandboxes.
Bazzi Consulting’s recommendation
GRC leaders should lobby for—and participate in—national sandbox programmes to pilot high-risk AI under supervisory feedback, mitigating time-to-market delays while shaping pragmatic guidance.
Conclusion
The AI Act is a watershed moment, but its success hinges on nuanced risk classification, adequate supervisory capacity, and maintaining Europe’s innovation engine. Organisations that treat the regulation as a strategic governance upgrade—rather than a legal obstacle—will gain resilience and competitive credibility.
Is your AI governance framework ready for 2026? Bazzi Consulting supports institutions in translating legislative complexity into operational excellence.
References
CB Insights (2024) State of AI Q4 2024 Report. Available at: https://www.cbinsights.com (Accessed 5 June 2025).
Crawford, K. (2024) ‘Regulating to compete: The EU’s AI innovation dilemma’, Journal of European Tech Policy, 9(3), pp. 45–62.
European Parliament Council (2025) Regulation (EU) 2025/1111 on Artificial Intelligence (AI Act). Brussels: Official Journal of the European Union.
Floridi, L. et al. (2022) ‘Transparent, explainable and accountable AI: A European governance model’, AI & Society, 37(4), pp. 1473–1490.
Goddard, M. (2017) ‘The EU General Data Protection Regulation (GDPR): European regulation that has a global impact’, International Journal of Market Research, 59(6), pp. 703–706.
Veale, M. and Borgesius, F. Z. (2021) ‘Demystifying the draft EU Artificial Intelligence Act’, Computer Law Review International, 22(4), pp. 97–112.
Viljanen, A. (2025) ‘AI talent in the public sector: Supply, demand and salaries’, European Digital Governance Review, 2(1), pp. 19–34.
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