In the evolving digital economy, the integration of artificial intelligence has become an operational necessity for companies seeking to transform into AI-driven businesses. As organisations across the globe embed AI into their core processes, a new form of accountability is taking shape. The European Union’s Artificial Intelligence Act is the first legal framework of its kind, and it represents a watershed moment for global business. With penalties for non-compliance reaching up to 7% of global annual turnover, the question for leadership is no longer if the AI Act will impact your operations, but how you will strategically prepare for its inevitable reach.

This article was written by Mourad Seghir ([email protected]), Lorena Velo ([email protected]), and Marius Ungureanu ([email protected]). Lorena, Marius & Mourad are consultants with RSM Netherlands Business Consulting, focusing on International Trade & Business Strategy.

This is not a regulation confined to European borders or the technology sector alone. Its horizontal, risk-based approach has an extraterritorial scope, meaning any organisation whose AI-driven services or products touch the EU market is directly affected.  

Are you using AI to screen job applicants, assess creditworthiness, or personalize customer services? Are you deploying AI in your manufacturing processes or to monitor critical infrastructure? If so, the AI Act applies to you.

It establishes a new global standard for trust, transparency, and safety, compelling businesses to look beyond the immediate performance of their algorithms and fundamentally reassess their governance, risk, and compliance frameworks. The time for theoretical discussion is over; the era of mandatory, demonstrable AI accountability has begun.

Understanding the timeline: a two-wave approach to enforcement

The EU AI Act uses a phased approach to implementation, giving organizations time to adjust based on the type and risk level of their AI systems. Enforcement starts with systems that could cause the most immediate societal harm and gradually includes foundational technologies such as general-purpose AI (GPAI) and high-risk, sector-specific applications. Each deadline marks a change in regulatory expectations and introduces a new compliance requirement for providers, developers, deployers, and integrators.

Compliance countdown: key EU AI Act deadlines 

Navigating the new regulatory landscape: the core pillars of compliance

Complying with the AI Act is not a simple checklist exercise; it requires embedding new principles into your organisation's very DNA. General-purpose AI (GPAI) models are subject to a series of foundational obligations designed to ensure end-to-end accountability. Providers must maintain exhaustive technical documentation for each model, detailing its architecture, training methodology, evaluation metrics, and identified lifecycle risks. They are also required to publish clear, accessible summaries of the data sets used during training, regardless of whether the model is opensource or proprietary, so that downstream developers and regulators can understand its provenance. In addition, every provider must implement and publicly disclose a copyrightcompliance policy that explains how training data adheres to EU copyright law and accommodates opt-out requests under Article 4(3) of the Copyright Directive. To facilitate responsible integration, providers must supply downstream AI system developers with actionable guidance and documentation that supports their own compliance efforts.  

Beginning on August 2, 2026, all high-risk AI systems, such as those used in recruitment, healthcare diagnostics, credit scoring, and law enforcement, must comply with a much more detailed set of requirements. These include thorough conformity assessments, data governance measures, formal human oversight mechanisms, and the creation of cross-functional governance frameworks. Although this deadline is still several months away, the complexity and scope of the obligations mean organizations should start preparing now. Legal, technical, and operational teams will need to work closely to audit existing systems, develop new policies and procedures, and incorporate these controls into their AI development and deployment processes.

The High-Risk AI Compliance Checklist

Strategic roadmap to AI Act readiness

Waiting for the deadlines to loom closer is a high-risk strategy. Leading organisations are acting now, building the capabilities required to navigate this new terrain. A proactive approach should be structured around four key actions: 

Forward thinking

The EU AI Act is more than just a regulatory hurdle; it acts as a catalyst for innovation and differentiation across the AI value chain. Major GPAI providers that proactively publish comprehensive documentation, transparent training data summaries, and strong copyright policies will foster greater trust with enterprise customers and regulators. Startups and SMEs refining open-source models can use early compliance as a market signal, demonstrating responsible fine-tuning practices and systematic risk assessments to attract partnerships and investment. Distributors and integrators who incorporate strict data governance protocols and human oversight mechanisms into their platforms will stand out by providing "compliance-ready" AI toolkits to downstream developers.

For high-risk system deployers in healthcare, finance, or public services, adopting the AI Act’s detailed risk management, logging, and security standards early will reduce project delays, liability exposure, and remediation costs. Ultimately, organizations that prioritize transparency, accountability, and human-centric controls today will not only ensure legal compliance but also position themselves as trusted leaders, unlocking new business opportunities in a rapidly evolving AI landscape.

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