Smart Technologies for a Changing World: A Multidomain Study of AI Driven Transformation

Abstract

Artificial Intelligence (AI) is emerging as a defining technological force reshaping industries, governance, and society at an unprecedented pace. While domain-specific AI applications have demonstrated remarkable success, a holistic understanding of AI's cross-domain transformation patterns, shared challenges, and transferable solutions remains fragmented across disciplinary silos. This paper presents a comprehensive multidomain study examining AI-driven transformation across six critical sectors: healthcare, manufacturing, finance, agriculture, education, and transportation. Through a mixed-methods approach combining systematic literature analysis of 850 publications (2020–2025), quantitative performance benchmarking across 42 AI deployment case studies, and a survey of 1,680 industry practitioners and policymakers across 28 countries, we develop the SMART-AI (Systematic Multidomain Assessment of Responsible Transformative AI) framework for evaluating AI readiness, adoption maturity, and societal impact. Our findings reveal that while finance leads in AI maturity (composite score: 82/100) and healthcare shows the highest efficiency gains (diagnostic accuracy improvement of +26%), agriculture and education lag significantly in deployment scale and workforce readiness. Cross-domain analysis identifies six universal barriers—data quality, regulatory uncertainty, talent shortage, legacy integration, ethical concerns, and implementation cost—with severity varying by sector. We propose a transferable best-practices framework demonstrating that lessons from AI-mature sectors can accelerate adoption in emerging domains, potentially contributing $15.7 trillion to the global economy by 2030. The paper concludes with evidence-based policy recommendations for governments, industry leaders, and educational institutions navigating the AI transformation.