From constraint to competitive advantage: AI compliance gives new shapes to compliance attitude

Maria Cristina Michelini, Legal Counsel at The Palace Company Europe S.r.l in Italy explores how AI regulation is reshaping corporate compliance – from a reactive control function into a strategic governance framework that enables responsible innovation and long-term competitive advantage.

Traditionally, corporate compliance has been perceived as a constraint: a necessary cost aimed at mitigating legal risk, ensuring regulatory adherence and avoiding sanctions. Too often, compliance frameworks are reduced to sets of documents, procedures and policies that only partially reflect how business operations actually function.

This disconnect produces two effects. First, compliance frameworks fail to mirror real business processes. Second, business activities are forced to adapt to abstract compliance models that exist primarily “on paper”. The result is an artificial regulatory construct that struggles to integrate with operational reality and is therefore difficult to implement effectively.

In fast-moving technological environments, this dynamic risks framing compliance as an obstacle to innovation rather than a functional enabler.

Artificial intelligence challenges this traditional paradigm. The EU AI Act itself reflects this tension. During its legislative process, EU institutions debated between two opposing approaches: on the one hand, rigid and highly prescriptive rules; on the other, an extremely flexible framework based almost exclusively on high-level principles. The final text adopts an intermediate solution, combining clear definitions and obligations with annexes and instruments designed to preserve adaptability and practical effectiveness.

This structure mirrors the evolution of compliance itself. As AI systems increasingly permeate core business functions – from automated decision-making to customer interaction and data analytics – compliance can no longer operate as a reactive or peripheral function. Instead, it must evolve into a strategic lever capable of supporting responsible innovation, enhancing trust and generating long-term competitive advantage.

The AI Act and the emergence of a governance-based model

The EU AI Act marks a significant shift in the regulation of emerging technologies. Rather than focusing primarily on ex post liability, it introduces an ex ante governance model based on risk classification, accountability and lifecycle management of AI systems.

Transparency, human oversight and risk mitigation are no longer abstract ethical principles: they become operational requirements. For companies active in the European market, this creates a dual challenge. On the one hand, complex regulatory obligations must be translated into workable internal processes. On the other hand, innovation speed must be reconciled with governance discipline.

Corporate compliance reimagined: from reactive to embedded

Within this framework, corporate compliance undergoes a structural transformation. Traditional compliance models – siloed, document-driven and reactive – are ill-suited to the dynamic and evolving nature of AI systems.

Effective AI governance requires a shift:

• from formalistic “check-the-box” compliance to risk-based governance;
• from isolated legal oversight to cross-functional collaboration among legal, IT, data, HR and business teams;
• from downstream control to upstream integration into system design, deployment and monitoring.

The effectiveness of AI compliance ultimately depends on its capacity to reflect how a business actually operates, rather than imposing abstract regulatory models disconnected from operational reality.

Operationalising AI compliance: tools and responsibilities

A mature AI compliance framework relies on concrete instruments and clearly defined responsibilities.

Risk assessment and classification

Consistent with the AI Act’s risk-based approach, companies should implement structured and continuous risk assessment processes covering legal, ethical and operational dimensions throughout the AI lifecycle.

Human oversight and accountability

Clear allocation of responsibility is essential. Human oversight mechanisms ensure that accountability does not dissolve into technical opacity or automated decision chains.

Policies, training and organisational culture

Internal policies, codes of conduct and targeted training initiatives translate regulatory expectations into daily operational practice, fostering awareness and shared responsibility across the organisation.

In this ecosystem, General Counsels and compliance professionals occupy a strategic position. Situated at the intersection of law, risk and business strategy, they are uniquely placed to align regulatory requirements with operational needs.

Conclusions

Effective AI compliance is not merely a matter of controls and documentation. It is fundamentally a matter of corporate culture.

An AI-ready organisation embraces transparency, interdisciplinary dialogue and shared accountability. Companies should begin by clearly identifying the AI systems and use cases they intend to deploy, assessing data quality and governance, and designing internal structures capable of overseeing compliance throughout the AI lifecycle.

In this context, so-called “soft law” instruments – including codes of practice – play a crucial role. While not constituting conclusive evidence of compliance, they provide practical guidance for implementing AI Act obligations in a manner that is both operationally feasible and legally robust.

Given the inherently multi-layered nature of AI systems, compliance cannot rely on static or generic solutions. It must be tailored to specific business models, data practices and organisational structures. Companies that actively engage in shaping workable governance frameworks – rather than passively replicating regulatory text – will be best positioned to navigate the evolving AI regulatory landscape.

Ultimately, compliance should function not as a brake on innovation, but as a compass guiding sustainable and responsible technological development.

Related Publications