Abstract
Artificial Intelligence (AI) is emerging as a transformative force in the global transition
to sustainable energy. This study presents a comprehensive review of current research
across three focal areas: technical implementation of AI, policy frameworks, and regional
applica- tions, particularly in low resource contexts. By integrating insights from a
technical review, a conceptual policy framework, and a country-specific case study, this
abstract outlines how AI can reshape energy systems to meet climate and development
goals.
Many researchers proposed a novel AI-enabled policy framework, addressing key stages
of the energy policy lifecycle—agenda setting, formulation, implementation, and
evaluation. This framework employs AI-driven decision-making, scenario modeling, and
multi-criteria analysis to ensure equity, transparency, and adaptability in energy
governance.
Further, AI’ based sustainable energy has potential in addressing energy poverty through
decentralized, AI-powered microgrids and peer-to-peer energy trading, while considering
challenges related to infrastructure, workforce skills, and data access.
The researchers point out, common challenges persist across all domains: lack of high-
quality and interoperable data, high computational costs, cybersecurity risks, and limited
regulatory maturity. Future success depends on interdisciplinary collaboration,
investment in data infrastructure, and the development of ethical, inclusive AI policies.
This abstract provides the importance of integrating AI into sustainable energy
transitions technically robust, socially inclusive, and policy informed paving the path
toward global decarbonization and energy justice.
Building on recent reviews, it is important to propose novel concept of an AI Readiness
Index for Sustainable Energy Systems, aimed at helping policymakers assess technical,
in- frastructural, and ethical preparedness for deploying AI in national energy strategies.
This framework fills a critical gap in current research, which focuses heavily on
implementation but rarely evaluates readiness or capacity for adoption—especially in
developing regions.
Keywords: Artificial Intelligence, Sustainable Energy, Machine Learning, Energy
Policy, Renewable Energy, Smart Grid, Energy Forecasting, Energy Equity