Artificial Intelligence in Blockchain-Based Energy Markets: Regulatory and Technological Perspectives

The move to phase out fossil fuels has become a global priority, driven by the pressing need to address climate change and promote sustainable development. This shift is transforming energy systems from traditional centralised models into dynamic peer-to-peer (P2P) marketplaces. In these new ecosystems, prosumers emerge as active participants who autonomously trade energy while leveraging distributed energy resources, fundamentally changing how we produce and consume power. At the forefront of this shift is the powerful combination of artificial intelligence (AI) and blockchain technology in P2P energy trading. Together, these innovations are reshaping decentralised energy systems, creating more scalable and resilient energy networks that grow from the ground up. This raises a crucial question: Can AI in blockchain-enabled peer-to-peer energy trading systems bring revolutionary transformation in decarbonising energy landscapes? As we explore this possibility, we uncover the remarkable potential of these technologies to fundamentally alter the energy sector while acknowledging both their promise and their challenges. The rapid progress of AI in this field presents a modern version of the tortoise and hare paradox. While technological innovation races ahead at breakneck speed, regulatory frameworks struggle to keep pace, creating growing gaps between what is technically possible and what is legally permitted.

Publication Details

Journal
Asian Journal of Law and Policy
Published
2025-12-01
DOI
https://doi.org/10.33093/ajlp.2025.18
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence in Blockchain-Based Energy Markets: Regulatory and Technological Perspectives

Asian Journal of Law and Policy
Blockchain Technology Applications and Security
article

Artificial Intelligence in Blockchain-Based Energy Markets: Regulatory and Technological Perspectives

article en

Abstract

The move to phase out fossil fuels has become a global priority, driven by the pressing need to address climate change and promote sustainable development. This shift is transforming energy systems from traditional centralised models into dynamic peer-to-peer (P2P) marketplaces. In these new ecosystems, prosumers emerge as active participants who autonomously trade energy while leveraging distributed energy resources, fundamentally changing how we produce and consume power. At the forefront of this shift is the powerful combination of artificial intelligence (AI) and blockchain technology in P2P energy trading. Together, these innovations are reshaping decentralised energy systems, creating more scalable and resilient energy networks that grow from the ground up. This raises a crucial question: Can AI in blockchain-enabled peer-to-peer energy trading systems bring revolutionary transformation in decarbonising energy landscapes? As we explore this possibility, we uncover the remarkable potential of these technologies to fundamentally alter the energy sector while acknowledging both their promise and their challenges. The rapid progress of AI in this field presents a modern version of the tortoise and hare paradox. While technological innovation races ahead at breakneck speed, regulatory frameworks struggle to keep pace, creating growing gaps between what is technically possible and what is legally permitted.

Asian Journal of Law and PolicyVol. 5(3)
Openalex Percentile: Top 50%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.