Conceptual Framework for Sustainable Development Projects in a BANI Environment Using AI Tools

2025

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DOI 10.1016/j.procs.2025.10.240
Data confidence 70 medium
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Abstract

This paper proposes a conceptual framework for managing sustainable development projects within the challenging Brittle, Anxious, Non-linear, and Incomprehensible (BANI) environment, leveraging Artificial Intelligence (AI) tools. The framework integrates an Input Layer (project objectives, BANI analysis, data collection, stakeholder engagement), AI-Driven Processes (risk assessment, resource optimisation, decision-support systems, predictive analytics, monitoring, and evaluation), and an Output Layer (enhanced resilience, increased efficiency, improved decision-making, stakeholder satisfaction, and sustainability goal achievement). A mathematical model is presented to formalise the optimisation of project sustainability by quantifying AI’s contributions to risk reduction, nonlinearity management, data interpretation, and resource efficiency. The practical application and effectiveness of this framework are demonstrated through a case study of IT University’s AI-driven sustainable education program, which successfully addressed BANI challenges in curriculum flexibility, stakeholder concerns, unpredictable outcomes, and interdisciplinary content, leading to measurable improvements in carbon emissions, student anxiety, community trust, and e-waste recycling. The findings underscore the transformative potential of AI in fostering agile, resilient, and impactful sustainable development initiatives that can thrive in complex and uncertain global conditions.