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FEATURE AI IN DESIGN & MANUFACTURING


While AI is opening up new possibilities


for optimising machine performance, its


deployment carries risks beyond


cybersecurity, as Chris Whyborn, head of


Cybersecurity Services (UK & Europe),


TÜV SÜD Business Assurance, explains


A


I is rapidly becoming a core part of product development and manufacturing. It can improve predictive maintenance and


accelerate product development cycles, and it can support generative design modelling, compliance documentation creation, and supply chain planning. For machine builders, AI-assisted control systems and digital twin technologies are opening new possibilities for optimising machine performance and reducing time to market. However, AI deployment carries multifaceted


risks beyond cybersecurity. When integrating AI into safety-critical machinery or embedded control systems, this includes violating laws such as data protection and equality, as well as upcoming AI-specific regulations, which may result in financial penalties or legal challenges. There are also ethical and societal risks associated with AI deployment, such as bias and discrimination, where a lack of transparency or accountability can erode trust and impact CE or UKCA marking obligations. Any organisation deploying AI within its


systems must integrate technical safeguards with ethical and legal compliance across the entire AI lifecycle, ensuring that any AI systems are trustworthy, fair and secure.


regulAtory consIderAtIons The EU AI Act requires a risk-based approach for compliance. High-risk systems will be subject to strict requirements and must meet comprehensive obligations for transparency, security and oversight. Non-compliance may result in fines of up to


€15 million or up to 3% of global annual revenue. While this does not apply to organisations based solely in the UK, it does apply if they operate in the EU. There is also the ‘Brussels Effect’ as the EU’s large market size often means its regulations become a global standard. Design engineers should therefore classify AI systems into the risk classes defined in the EU AI Act to understand applicable requirements, and whether it is affected by the regulation. The UK is taking a different approach, currently favouring a pro-innovation and


1 DESIGN SOLUTIONS JUNE 2026 8


AI deployment: gettIng It rIght


principles-based framework rather than the EU's prescriptive legislation. The UK’s framework is built around five core principles: 1. Safety, security and robustness – systems must operate reliably while remaining resilient.


2. Transparency and explainability – the logic behind an AI-driven decision should be documented and easily communicated to a non-technical audience.


3. Fairness – the system must not reinforce historical prejudices, while delivering equitable results across all demographic groups.


4. Accountability and governance – ensure clear ownership for the AI system and establish a formal structure for managing its impact within the organisation.


5. Contestability and Redress – provide a clear method for individuals who want to dispute AI-generated decisions, using a human-led review. The UK Government is currently relying on existing industry regulators to apply these


principles using current law, rather than introducing a single piece of legislation. However, it has indicated that targeted legislation is likely in the future, particularly for the most powerful AI models.


ethIcAl use Organisations must demonstrate that an AI system does not violate expected ethical principles. This includes ensuring that it will not cause harm and that it is aligned with the organisation’s values, proving that systems are fair, transparent and human-centric. Transparency and accountability must


therefore be prioritised by ensuring all automated decisions are explainable through clear audit trails, while maintaining human oversight for safety-critical systems and high-consequence activities. For example, when machine builders use AI to make real- time decisions that could affect operator safety or product quality. Data anonymisation must also be assured.


www.designsolutionsmag.co.uk


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