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Critical Infrastructure

AI Act Compliance for Energy & Telecom

Smart grids, network management and critical infrastructure — high-risk under the AI Act

Practical guidelines for energy companies, network operators and telecom providers to comply with the EU AI Act.

View the compliance checklist

Why Take Action Now?

The AI Act has major impact on energy and telecom

August 2025

First obligations for high-risk AI systems in critical infrastructure come into effect

Critical Infrastructure = High-risk

AI in energy and telecom networks automatically falls under the strictest AI Act rules (Annex III)

Fines up to €35 million

Or 7% of global annual turnover — ACM and sector regulators will enforce

Safety Components

AI as safety component in networks requires conformity assessment and CE marking

High-risk AI in Energy & Telecom

These AI applications fall under strict AI Act requirements (Annex III)

Smart Grid Management

AI systems managing energy networks, distributing load and predicting grid congestion — essential for supply security.

Grid congestion predictionLoad balancing AIEnergy distribution optimizationOutage prediction

Predictive Maintenance Critical Infra

Systems predicting maintenance for power plants, transformer stations and telecom towers — outage can have societal impact.

Turbine monitoring AITransformer diagnosticsCable degradation detectionTower inspection AI

Network Monitoring & Cybersecurity

AI for detecting cyber threats and anomalies in energy and telecom networks — crucial for national security.

Anomaly detectionThreat intelligence AISCADA monitoringDDoS prevention

Energy Pricing & Customer Decisions

Algorithms determining energy prices, assessing customers or applying dynamic tariffs — direct impact on consumers.

Dynamic pricingCustomer profile scoringEnergy poverty detectionConsumption prediction

Specific Challenges for Energy & Telecom

The AI Act brings unique compliance questions for the sector

NIS2 and AI Act Overlap

How to combine NIS2 cybersecurity obligations with AI Act requirements? Where do they overlap and where do they conflict?

Real-time Decisions

Energy networks require millisecond decisions. How to comply with human oversight without compromising network stability?

Safety Component Classification

When is AI a safety component under the Machinery Regulation? And what does that mean for CE marking?

Legacy SCADA & OT Systems

Much operational technology is decades old. How to integrate AI Act compliance into existing industrial systems?

Supply Chain Complexity

Energy and telecom chains are complex. Who is provider, who is deployer in integrated AI solutions?

Sector-specific Supervision

ACM, RDI and State Supervision of Mines — how do these regulators interpret the AI Act for the sector?

AI Act Compliance Roadmap

Practical steps for energy and telecom companies

1

AI Inventory

2-4 weeks

Map all AI systems. Which systems manage critical infrastructure or make customer decisions?

2

Risk Classification

1-2 weeks

Determine per system if it is high-risk due to critical infrastructure, safety component or consumer decision.

3

Gap Analysis

3-6 weeks

Compare current documentation with AI Act, NIS2 and sector-specific requirements.

4

Remediation

3-12 months

Implement technical documentation, risk management, human oversight and cybersecurity measures.

5

Ongoing Monitoring

Ongoing

Set up processes for continuous monitoring, incident reporting and periodic review.

What Makes Energy & Telecom AI Different?

Sector-specific considerations

Critical Infrastructure Status

Energy and telecom AI falls under both AI Act and NIS2 cybersecurity directive

Real-time Requirements

Networks require uninterrupted AI decisions — human oversight must be implemented differently

Societal Impact

Energy or telecom outage affects millions of people — reliability requirements are extremely high

Converging Regulation

AI Act, NIS2, Machinery Regulation and sector legislation require an integrated compliance approach

Need Help with AI Act Compliance?

We help energy and telecom companies with practical implementation

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