Record STMT-WECC0EBSoft law

Ethical AI use in the energy sector (version 2)

Guidelines State lawEurope · GBin force

This guidance document from Ofgem sets out good practices for the ethical, safe, secure, fair, and environmentally sustainable adoption of artificial intelligence within Great Britain's energy sector. It covers governance and policies, risk management, competencies, and sector-specific examples ranging from consumer interactions to cyber-physical systems. The guidance complements existing legal, regulatory, and licensing obligations without replacing them.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

Office of Gas and Electricity MarketsRegulator · GB

Lead issuer

Legal forceSoft law

Under whose authorityState law

Judged fromfull text

Who it governs

RegulatorsGeneral publicCompaniesAI developers and providersAI deployers and usersResearchers and academics

This guidance is for all stakeholders involved with AI in the energy sector, including licensees, market participants, operators of essential services, technology companies, developers, consumer groups, and government bodies.

Sectors

Energy and utilities · energy sector, gas and electricity networks, retail supply

What the document contains

What's covered

The document addresses the ethical adoption of artificial intelligence across Great Britain's energy sector. It establishes good practices for governance and policies, risk assessment, staff competencies, and sector-specific applications such as consumer service, forecasting, trading, and grid management. It also provides detailed appendices covering legal obligations, standards, supply chain management, data use, cyber security, and transparency and explainability.

What's missing

It does not create new binding statutory rules or replace existing legal and regulatory obligations, nor does it provide exhaustive technical specifications for individual software applications.

Key takeaways

Ofgem considers the existing energy regulatory framework appropriate to govern AI, supported by this non-binding good practice guidance.
The ethical approach focuses on four key outcomes: safety, security, fairness, and environmental sustainability.
Organizations deploying AI retain ultimate responsibility and accountability for safety, security, fairness, and sustainability, and cannot outsource these obligations.
Stakeholders must implement robust governance, clear risk management frameworks, and appropriate competencies across the AI life cycle.
The guidance highlights specific considerations for consumer interactions, vulnerability identification, forecasting, cyber-physical systems, pricing and trading, and data analytics.

Principles it states

SafetySecurityFairnessEnvironmental sustainability

Outline

· Foreword
· 1. Introduction
· 2. Our ethical approach
· 3. Governance and policies
· 4. Risk
· 5. Competencies
· 6. Sector-specific examples
· Glossary
· Send us your feedback
· Appendices

Issued13 May 2026

Length14,794 words

FormatNot recorded

Scopenational

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

4/5

Clear responsibility for AI outcomes

Stakeholders have appropriate policies, processes and procedures in place to ensure proportionate and effective governance including oversight of the supply chain and use of AI systems, with clear lines of accountability established across the AI life cycle.

3. Governance and policies

screening score · 2026-10-23

Fairness

4/5

Non-discrimination and equitable treatment

Stakeholders must ensure AI systems serve energy consumers fairly by implementing robust governance, systems and processes.

2. Our ethical approach

screening score · 2026-10-23

Human Dignity

2/5

Respect for the inherent worth of persons

Stakeholders are also required to comply with other areas of legislation that apply to the energy sector and AI use, including data protection, equality, human rights, and health and safety.

1. Introduction

screening score · 2026-10-23

Human Oversight

4/5

Humans remain in control of consequential decisions

As such, human oversight from the earliest stage is recommended as a risk control and mitigation measure. It is important to consider both overconfidence and a lack of trust in the AI components especially where human oversight is used as a risk control and mitigation measure.

4. Risk

screening score · 2026-10-23

Impact Assessment

4/5

Required assessment of an AI system's risks/impacts before or during use

undertaking a risk assessment that identifies the necessary control measures throughout the life cycle, ensuring that the AI system functions as defined, treats consumers fairly, and cyber-physical systems comply with health and safety legislation

6. Sector-specific examples

screening score · 2026-10-23

Topics

artificial_intelligence energy_sector ethical_ai risk_management transparency_and_explainability