• • • AI • • •
AI ACT COMPLIANCE CHALLENGES The second condition is if the product in
question is required to undergo a third-party conformity assessment before it can be sold. This impacts:
BY IAIN BOWES,
HEAD OF MANAGEMENT SYSTEM ASSURANCE, TÜV SÜD BUSINESS
T
he EU’s AI Act is the world’s first comprehensive AI regulation, requiring organisations to integrate technical
safeguards with ethical and legal compliance across the entire AI lifecycle. The primary goal is to ensure the AI system is
trustworthy, transparent and secure. The manufacturing and electronics sectors are among the most heavily impacted by its high-risk classifications as it applies to embedded AI, for example where AI is a safety component of a physical product. The Act categorises businesses based on how
they interact with the AI system providers, deployers, importers or distributors. Providers are typically developers or manufacturers, while deployers are organisations that use AI in their operations, and importers must ensure that non-EU AI systems meet EU requirements before being sold. Distributors that sell or supply AI systems without modifying them have lighter but still important obligations. Even organisations that are indirectly regulated, for example cloud providers offering AI APIs that are accessible in the EU or evaluation labs, are still affected by the Act. Under Article 6(1), an AI system is automatically
classified as high-risk if it meets two conditions. The first condition is if it is a product (or a safety component of a product) covered by the EU’s existing product safety laws (listed in Annex I), totalling 20 specific pieces of legislation, including machinery radio equipment, medical devices and lifts.
• Industrial machinery - AI used to control robotic arms, automated assembly lines or safety sensors in factories, falling under the Machinery Regulation.
• Electronics and radio equipment - AI integrated into smart devices, telecommunications hardware or industrial IoT sensors, under the Radio Equipment Directive.
• Medical devices - AI-powered diagnostic hardware or robotic surgery tools.
• Lifts and pressure equipment - AI used to manage safety protocols in elevators or industrial boilers.
If a company manufactures smart machinery
or industrial IoT devices, they must follow both the AI Act and the relevant existing safety laws. This creates a double compliance burden as they must ensure the AI meets the AI Act’s data and transparency standards alongside the physical safety standards of the Machinery or Radio Equipment directives, for example. For such products or systems, a CE Mark cannot be applied unless the high-risk requirements of the AI Act have been fulfilled. Non-compliance may result in fines of up to
15 million Euro or up to three per cent of global annual revenue. The potential penalties have a three-tiered system based on the severity of the violation, according to whether that is considered unacceptable risk, non-compliance with obligations or misleading authorities. The EU has introduced specific caps to ensure that a single fine doesn’t instantly bankrupt a small business. The EU AI Act represents a seismic shift in
how business is conducted, moving AI from a tech-team project to a board-level compliance and
14 ELECTRICAL ENGINEERING • JULY/AUGUST 2026
ethics priority. For organisations navigating this transition, compliance is the floor not the ceiling. To truly succeed, businesses must bridge the gap between legal requirements and operational trust. To turn these regulatory hurdles into a
competitive advantage, organisations should adopt the core principles of the AI Essentials framework:
• Pillar 1 - Security and Data Integrity: Protecting against logic-based attacks and securing data pipelines.
• Pillar 2 - Transparency and Explainability: Ensuring stakeholders understand they are interacting with AI and can explain how decisions are made.
• Pillar 3 - Human-in-the-Loop and Accountability: Preventing irreversible AI decisions without human review.
• Pillar 4 - Fairness and Bias Mitigation: Ensuring AI does not discriminate or reinforce harmful stereotypes.
• Pillar 5 - Reliability and Hallucination Management: Using techniques like Retrieval- Augmented Generation (RAG) to ground the AI in factual data and mitigate fabrication.
• Pillar 6 - Societal, Ethical and Consequential Impact: Proactively assessing the broader effects of AI on the environment, workforce and society.
It is vital to remember that AI-enabled systems
should not be built for a regulator but for end users. By the time the August 2028 transition windows close, the businesses that thrive will be those that didn’t just tick the box of the EU AI Act, but those that implemented AI Essentials to create a transparent, resilient and human-centric AI ecosystem.
www.tuvsud.com
electricalengineeringmagazine.co.uk
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