AI rollout exposes UK factories’ ageing cyber defences

UK manufacturers face rising cyber risks as they roll out artificial intelligence on ageing operational technology networks, according to security firm IDS-INDATA.

The company warned that more than half of industrial OT environments still run on legacy systems. It said these systems were not built for AI-driven automation or internet-connected operations.

IDS-INDATA reported a 20% year-on-year increase in supply-chain cyberattacks. It said legacy infrastructure was especially exposed to these attacks.

The National Cyber Security Centre has also warned that AI is likely to make some cyber intrusions more effective and more efficient. It said attackers can use the technology to improve reconnaissance and automate parts of their operations.

"AI is now both an operational advantage and a potential adversary," said Ian Humber, Head of Sales, IDS-INDATA.

Humber said manufacturers that update networks early are more likely to gain productivity benefits from AI. He said those firms are also more likely to reduce the risk of cyber incidents and compliance failures.

Legacy exposure

Operational technology covers the systems that control and monitor industrial processes. Many of these systems were installed before current cyber threats and AI tools emerged.

A survey by TXOne of 550 OT and industrial control system decision-makers found that more than half still rely on legacy platforms. These systems often lack modern security controls or full support from vendors.

Separate research cited by IDS-INDATA found that nearly 70,000 OT devices worldwide are directly exposed to the public internet. Many of these devices run outdated firmware with known vulnerabilities. Attackers can scan for these systems and target them.

IDS-INDATA said UK manufacturers are now deploying AI for production planning, predictive maintenance and supply-chain optimisation. It said these projects often run on top of old network architectures. It said this creates a gap between digital ambitions and security readiness.

Humber said companies that modernise network design and introduce clear security controls are better placed to use AI safely. He said they can then scale AI across plants without adding unmanaged risk.

Four priorities

The firm set out four urgent priorities for manufacturers that plan to use AI in OT environments. These are asset visibility, embedded IT and OT security, strong governance, and resilience against AI-enabled threats.

The first area is complete asset visibility and data integrity. IDS-INDATA said AI models need an accurate picture of all connected devices and data flows. It said gaps in this view can cause errors, downtime and cascading failures in production lines.

The company recommended comprehensive OT and IT asset discovery. It also called for real-time system monitoring and strict controls over data quality and validation.

The second priority is embedding security across IT and OT networks. Many industrial networks were never designed for large numbers of connected devices or autonomous systems.

IDS-INDATA said manufacturers should introduce network segmentation and secure remote access. It also highlighted continuous threat detection and ongoing vulnerability management as core tasks.

Industry research from Info-Tech has stated that legacy factories were not built with connectivity or cybersecurity in mind. This has created wide gaps in protection as more equipment comes online.

The third focus area is governance, compliance and AI auditability. AI systems process large volumes of operational data and can influence safety-critical decisions.

IDS-INDATA said manufacturers must create structured AI governance and audit logging. It said they should ensure model traceability and use formal approvals for any changes. It also called for compliance frameworks aligned with sector standards and regulations such as NIS2 and data protection law.

UK guidance on AI regulation has said there must be a clear line of accountability across the AI life cycle. Regulators expect companies to understand and document how systems behave.

The fourth priority is resilience against emerging AI-enabled cyber threats. Attackers are using AI tools to speed up scanning, phishing and intrusion efforts.

IDS-INDATA said industrial firms need incident response plans and protected backups. It said micro-segmentation and anomaly detection reduce the spread of attacks. It also stressed the importance of rapid isolation of compromised systems to maintain uptime.

The NCSC has warned that AI is making reconnaissance more effective and harder to detect. It expects attackers to refine these methods over the coming years.

Network modernisation

IDS-INDATA said many of the risks sit in ageing networks rather than in AI itself. It argued that upgrades, monitoring and executive oversight create a more stable base for new digital tools.

"Manufacturers shouldn't see this as a barrier to AI adoption. With the right network foundations, visibility, embedded security, and strong governance, AI can deliver huge gains safely. Most issues stem from legacy networks, not AI itself," said Humber.

The company said manufacturers that are already reassessing their OT security, including segmentation and continuous monitoring, are better positioned for AI deployment across their operations.