AI legitimacy in energy: A model to improve corporate narratives on sustainability and responsibility

Abstract

CONTEXT: The integration of artificial intelligence (AI) in the energy sector is pivotal for achieving Sustainable Development Goal 7 (SDG7). Within the European Union, the regulatory landscape, particularly the proposed AI Act, influences how organisations navigate responsible AI (RAI) adoption while addressing societal expectations, creating a critical need to examine how they communicate their commitment to RAI and sustainability. OBJECTIVE: This study uncovers how narratives employed in the public communications of EU energy stakeholders legitimise corporate efforts and signal alignment with RAI principles. METHOD: A grey literature search of website pages, whitepapers, and reports was conducted. Thematic analysis, using inductive and deductive coding, was employed to identify emerging themes and evaluate how organisations frame their initiatives in response to regulatory and societal pressures. RESULT: Analysis of 28 reports reveals that EU energy stakeholders predominantly frame AI as an inevitable technological advancement while lacking concrete strategies for RAI implementation. Communications focus on aspirational commitments rather than measurable actions. To address these gaps, this study develops the Responsible AI (RAI) Communication Model. This framework guides stakeholders in structuring their communication around three core pillars: (1) aligning AI initiatives with measurable sustainability goals and governance, (2) developing trustworthy and accountable narratives backed by concrete evidence, and (3) establishing organisational legitimacy through active stakeholder engagement. CONCLUSION: By adopting this model, energy stakeholders can move beyond rhetorical narratives towards sharing demonstrable practices. This fosters greater trust, ensures effective communication of priorities like transparency and accountability, and promotes regulatory alignment.

Publication DOI: https://doi.org/10.1016/j.techfore.2025.124378
Divisions: College of Business and Social Sciences > Aston Business School > Cyber Security Innovation (CSI) Research Centre
College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences
Funding Information: This work was funded by the International NEC Energy Transition Grant (202202001ETG); and by Aston University and University Tenaga Nasional (UNITEN) under the Responsible AI for a Secure and Trustworthy Energy Transition (RISE) project.
Additional Information: Copyright © 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: Responsible artificial intelligence,Corporate social responsibility,Energy transition,Signalling theory,Legitimacy theory,Communication
Publication ISSN: 1873-5509
Last Modified: 20 Oct 2025 07:21
Date Deposited: 17 Oct 2025 14:53
Full Text Link:
Related URLs: https://linking ... 040162525004093 (Publisher URL)
PURE Output Type: Article
Published Date: 2026-01-01
Published Online Date: 2025-10-16
Accepted Date: 2025-10-07
Authors: Di Chiacchio, Laura (ORCID Profile 0000-0002-2421-6098)
Al-Khateeb, Haider (ORCID Profile 0000-0001-8944-123X)
Butt, Usman
Yussof, Salman

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