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

  • Laura Di Chiacchio
  • , Haider Al-Khateeb
  • , Usman Butt
  • , Salman Yussof
  • Aston University
  • Universiti Tenaga Nasional

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.

Original languageEnglish
Article number124378
JournalTechnological Forecasting and Social Change
Volume222
DOIs
StatePublished - Jan 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  2. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions
  3. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Communication
  • Corporate social responsibility
  • Energy transition
  • Legitimacy theory
  • Responsible artificial intelligence
  • Signalling theory

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