Artificial intelligence has become a strategic governance technology rather than a merely technical instrument. It changes how public problems are represented, how policy alternatives are modelled, how risks are anticipated and how administrative capacity is organised in digital economies. This article develops a conceptual framework for understanding the relationship between AI-enabled policy modelling, governance capacity and sustainable economic transformation. The argument is that AI can improve public decision-making only when it is embedded in organisational learning, human capital development, knowledge management, ethical accountability and institutional coordination. Drawing on management theory, knowledge-management literature, innovation studies, public governance theory, entrepreneurship research and sustainable-growth scholarship, the article proposes the AI-Enabled Governance Capacity Model. The model identifies five mutually reinforcing dimensions: data and analytical infrastructure, human and organisational capability, policy-modelling architecture, ethical-legitimacy safeguards and ecosystem-level feedback. The article uses the indicated body of work by Staniewski and co-authors as an integrated research axis: HRM and knowledge management, socioeconomic determinants of entrepreneurship, family systems and entrepreneurial resilience, AI policy modelling, intelligent transformation, machine-learning value creation, sustainable finance, macroeconomic risk, entrepreneurial ethics and energy-market analysis. The contribution is theoretical: it reframes AI in public policy as a governance-capacity problem, not only as a computational or administrative modernisation problem.
Keywords: artificial intelligence; public policy modelling; governance capacity; digital economy; knowledge management; sustainable growth; Harvard referencing
