The relationships between artificial intelligence, clean-energy market performance, and green innovation are not well understood
Research gap analysis derived from 4 economics papers in our local library.
The gap
The relationships between artificial intelligence, clean-energy market performance, and green innovation are not well understood. Prior work has not fully captured the nonlinear and heterogeneous associations between these variables. There is a need for policies that align artificial-intelligence growth with the sustained development of green innovation.
Evidence profile
Sourced from the future-work section and stated research gap of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 49 times in total.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 4 representative gaps
- Cost-Benefit, Energy Sustainability and Technological Assessment of Artificial Intelligence Adoption in Nigeria’s Agricultural and Waste-to-Energy Systems (2026) · Journal of Technology Innovations and Energy · doi
Future studies can investigate the technical challenges associated with AI adoption in Nigeria's agricultural and waste-to-energy systems. Further research can explore the potential of AI-enabled technologies to support smart energy conversion, precision agriculture, renewable energy optimisation, and efficient waste valuation in other developing economies.
generalfuture-work sectionevidence 5/5Keywords: future studies investigate technical challenges associated adoption nigeria - Building a Sustainable Future: The Nexus Between Artificial Intelligence, Renewable Energy, Green Human Capital, Geopolitical Risk, and Carbon Emissions Through the Moderating Role of Institutional Quality (2025) · Sustainability · cited 49× · doi
The study identifies a knowledge gap in understanding the complex interplay between artificial intelligence, green human capital, REC, natural resource rents, geopolitical risk, ICT, institutional quality, and carbon emissions. Previous research has often inspected these components individually, but this study comprehensively analyzes their combined impact.
generalstated research gapevidence 5/5Keywords: study identifies knowledge gap understanding complex interplay between - Artificial Intelligence, Green Innovation, and the Clean-Energy Market: A Quantile-Based Analysis (2026) · Energies · doi
The relationships between artificial intelligence, clean-energy market performance, and green innovation are not well understood. Prior work has not fully captured the nonlinear and heterogeneous associations between these variables. There is a need for policies that align artificial-intelligence growth with the sustained development of green innovation.
generalstated research gapevidence 5/5Keywords: relationships between artificial intelligence clean-energy market performance green - The Potential of Artificial Intelligence in Enhancing Recycling Processes and Reducing Environmental Pollution: A Critical Review and Framework for an Emerging-Market Context (2026) · Sustainability · doi
the evidence on the potential of artificial intelligence in enhancing recycling processes and reducing environmental pollution is fragmented. technical studies show what AI can do, while management studies examine AI capability and green outcomes elsewhere, but rarely meet around recycling in a resource-constrained setting. there is a need for a framework that integrates these literatures and provides a structured basis for turning AI adoption into environmental gains.
generalstated research gapevidence 5/5Keywords: evidence potential artificial intelligence enhancing recycling processes reducing
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