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Cited by 31Impact of AI and Big Data on Business and SocietyBig Data and Business IntelligenceGreen IT and Sustainability

Artificial Intelligence-Driven Business Intelligence for Strategic Energy and ESG Management: A Systematic Review of Economic and Policy Implications

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Khaddam, Amineh A., Alzghoul, Amro·2025·International Journal of Energy Economics and Policy
DOI 10.32479/ijeep.19820
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Abstract

This literature review examines how artificial intelligence (AI)-powered business intelligence (BI) platforms are being leveraged to advance energy management and sustainability (ESG) goals in corporations. A systematic search of recent studies from Scopus, IEEE, Web of Science, and other databases yielded ~65 relevant peer-reviewed sources. We synthesized findings into five thematic areas: (1) AI applications in ESG reporting and automation, (2) BI systems for energy data visualization and monitoring, (3) predictive analytics for carbon and utility forecasting, (4) real-time dashboards for corporate sustainability decision-making, and (5) risks, biases, and ethical considerations of ESG technology. The review finds that AI-driven BI tools are streamlining sustainability reporting and assurance, enabling real-time energy monitoring and analytics, and improving forecasting of carbon footprints and energy consumption. These technologies have helped organizations identify efficiency opportunities and inform strategic sustainability decisions, with reported energy savings and emissions reductions in various cases. However, challenges persist, including data integration issues, algorithmic biases, and the need for ethical frameworks to govern AI in ESG. We identify critical research gaps such as (under-studied sectors and the social and governance dimensions of ESG tech) and propose directions for future investigation.

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  • AI-driven business intelligence systems shift corporate energy and ESG management from retrospective, compliance-based reporting toward continuous, predictive, and strategically embedded decision-making.

    “Khaddam and Alzghoul [44], based on a systematic review of 65 peer-reviewed studies, find that AI-driven business intelligence (BI) systems are shifting corporate energy and ESG management from retrospective, compliance-based reporting toward continuous, predictive, and strategically embedded decision-making.”

    From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [44]

    The ESG reporting section says AI is moving reporting from a yearly retrospective exercise to a continuous, data-driven process. The Conclusion describes real-time monitoring, predictive analytics, and their use in strategic planning. Those passages support the claimed shift, but the non-abstract passages found do not establish that the review covered 65 peer-reviewed studies. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Real-time dashboards are associated with typical energy savings of 5-15%, and AI-integrated building energy management systems report up to 37% HVAC energy reductions.

    “In operational energy management, real-time dashboards are associated with typical energy savings of 5-15%, while AI-integrated building energy management systems report up to 37% HVAC (heating, ventilation, and air conditioning) energy reductions, demonstrating measurable efficiency gains.”

    From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [44]

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Authors
Khaddam, A. A., & Alzghoul, A.
Affiliations
Amman Arab University (JO)
ORCID
Venue
International Journal of Energy Economics and Policy
Publisher
EconJournals
Published
2025-06-25
Volume
15
Issue
4
Pages
635-650
ISSN
2146-4553 (ISSN-L)
DOI
10.32479/ijeep.19820
OpenAlex
W4411616880
Cited by
31
References
0
Citations by year
2026: 26 · 2025: 5
FWCI
5.14
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • International Journal of Energy Economics and Policy (publishedVersion, cc-by-nc-nd)
  • International Journal of Energy Economics and Policy (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (acceptedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Green IT and Sustainability
Keywords
artificial intelligence, business intelligence, energy management, ESG management, sustainability reporting, energy data visualization, energy consumption monitoring, load forecasting, real-time dashboard, algorithmic bias, AI ethics, energy conservation, emission reduction

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