Cyber Security· Premium
AI-Era Cyber Threats to UK Energy Infrastructure
How generative and agentic AI reshape the threat landscape for UK electricity networks, data centres and industrial control systems.
Published 30 May 202658 pagesVersion v1.0
Executive summary
What this report covers
AI meaningfully lowers the cost of reconnaissance and phishing against energy operators. NCSC-aligned defensive baselines still hold, but detection windows are shortening. Boards should reassess incident response readiness annually.
Key findings
Headline conclusions
- AI cuts attacker reconnaissance cost by an order of magnitude.
- Phishing pretexts now bypass legacy user training.
- Deepfake voice attacks on control room staff are now credible.
- NCSC baselines remain effective but require continuous updating.
Who should read this
Intended audience
- CISOs at UK energy operators and DNOs
- Data centre security leadership
- Board audit and risk committees
- Government cyber policy teams
Table of contents
Inside the 58-page report
- 011. Threat landscape 2026
- 022. Attack surface: grid, DCs, ICS
- 033. Offensive AI capability review
- 044. Defensive baselines and gaps
- 055. Board-level questions
Preview
Sample pages
Frequently asked questions
Is this NCSC aligned?+
Yes — baselines and terminology follow current NCSC guidance for CNI operators.
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