A lack of understanding of the intersection of regulatory requirements and technological innovation in AI-driven building management

The gap

Evidence profile

Sourced from the inline gaps and stated research gap and stated challenges of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 4 journals. Those papers have been cited 368 times in total.

Supporting evidence — 7 representative gaps

• AI-driven approaches for optimizing power consumption: a comprehensive survey (2024) · Discover Artificial Intelligence · cited 93× · doi

  3 Future challenges and scopes Adopting AI in the smart energy industry faces a variety of bottleneck hurdles, including hazards, lack of data, poor data quality, tuning AI network parameters, inadequate technological infrastructure, shortage of skilled experts, integration difficulties, and legal and regulatory concerns. Various studies acknowledge that among the primary obstacles confronting energy systems are data insecurity and insufficient information [55]).

  generalinline gapsevidence 5/5
  Keywords: energy future challenges scopes adopting smart industry faces variety bottleneck hurdles including hazards lack poor
• AI ‐driven circular economy optimization in waste management: A review of current evidence (2026) · Environmental Progress & Sustainable Energy · cited 3× · doi

  The need for standardized datasets and explainable AI frameworks is a significant research gap. The lack of large-scale industrial deployment and measurable energy savings is another major gap. The requirement for efficient human-AI cooperation and the need to address ethical concerns related to job displacement and the environmental footprint of AI technologies are also significant gaps.

  generalstated research gapevidence 5/5
  Keywords: need standardized datasets explainable frameworks significant research gap
• Smart Grids and Sustainability: The Impact of Digital Technologies on the Energy Transition (2025) · Energies · cited 57× · doi

  The need to reduce greenhouse gas emissions and the growing focus on sustainability have created a gap in the current energy infrastructure. The increasing energy demand necessitates a radical transformation of energy infrastructures. The study aims to address this gap by analyzing the main research trends related to SG, energy efficiency, and the role of Artificial Intelligence (AI) and the Internet of Things (IoT) in smart energy management.

  generalstated research gapevidence 5/5
  Keywords: need reduce greenhouse gas emissions growing focus sustainability
• Internet of Things Applications for Energy Management in Buildings Using Artificial Intelligence—A Case Study (2025) · Energies · cited 61× · doi

  The lack of universal standards for IoT devices and AI algorithms leads to integration challenges and reduced system efficiency. The rapid growth of AI-based IoT applications has outpaced regulatory frameworks, leading to uncertainty around compliance and ethical accountability. Most AI-based IoT energy management research focuses on short-term benefits, with insufficient data on long-term performance, reliability, and economic viability.

  generalstated research gapevidence 5/5
  Keywords: lack universal standards iot devices algorithms leads integration
• Internet of Things Applications for Energy Management in Buildings Using Artificial Intelligence—A Case Study (2025) · Energies · cited 61× · doi

  The lack of universal standards for IoT devices and AI algorithms leads to integration challenges and reduced system efficiency. User trust and acceptance issues arise from the skepticism of building occupants and managers towards AI-based automation. Ethical AI governance is a challenge due to the lack of a governance framework to ensure transparency, fairness, and accountability of AI in energy management.

  generalstated challengesevidence 5/5
  Keywords: lack universal standards iot devices algorithms leads integration
• A Comprehensive Review of Solar PV Integration with Smart-Grids: Challenges, Standards, and Grid Codes (2025) · Energies · cited 80× · doi

  The lack of updated grid codes and policies that guarantee system stability and the effective functioning of renewable energy systems. The need for thorough solutions that harmonize technological advancements with ecological sustainability and social equity. The requirement for advanced technologies like AI, IoT, and blockchain to optimize energy management, predictive maintenance, and secure energy transactions.

  generalstated research gapevidence 5/5
  Keywords: lack updated grid codes policies guarantee system stability
• Impact of EU Laws on the Adoption of AI and IoT in Advanced Building Energy Management Systems: A Review of Regulatory Barriers, Technological Challenges, and Economic Opportunities (2025) · Buildings · cited 13× · doi

  a lack of understanding of the intersection of regulatory requirements and technological innovation in AI-driven building management - a need to examine the legal, technological, and economic implications of EU regulations on AI- and IoT-driven building energy management systems - a gap in identifying legal and regulatory barriers, technological challenges, and economic opportunities

  generalstated research gapevidence 5/5
  Keywords: lack understanding intersection regulatory requirements technological innovation ai-driven

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