Abstract
The demand for sustainable and resilient energy systems in healthcare educational environments has intensified interest in data informed design approaches. In Nigeria, persistent grid instability and rising operational costs sabotage institutional reliability. Renewable energy systems provide viable alternatives, but their success depends on informed early stage design decisions. Artificial Intelligence (AI) offers a decision support tool capable of synthesising environmental, energy, and operational data to guide architectural planning. This study evaluates AI as a decision support tool for renewable energy driven design in healthcare educational environments, using Nigerian institutions and Caleb University as contextual considerations. A qualitative approach was utilised, including documentary review, analysis of international and local precedents, and assessment of AI-supported design workflows. The study focuses on how AI informed insights can enhance professional judgement rather than replace it. Findings indicate that, although awareness of AI and renewable technologies is increasing, their implementation remains fragmented and reactive. Renewable systems are typically introduced after major architectural decisions, limiting optimisation. The study concludes that the key barrier is not the availability of technology, but rather the absence of structured frameworks that embed AI into early design and institutional planning. Strategic integration of AI at the conceptual stage is therefore essential to improve sustainability, resilience, and long term energy performance in healthcare educational environments.