Artificial Intelligence for Business Analytics and Entrepreneurial Innovation: A Comprehensive Framework and Policy Roadmap for Underdeveloped Economies

Abstract

Artificial intelligence (AI) is reshaping the foundations of global entrepreneurship, yet its diffusion remains heavily asymmetric, with underdeveloped economies lagging significantly behind. This paper develops a comprehensive and policy-oriented conceptual framework explaining how AI-driven business analytics can catalyze entrepreneurial innovation in low-income countries while addressing systemic barriers rooted in infrastructure, skills deficits, institutional weaknesses, and fragmented innovation ecosystems. Drawing from global evidence, established theoretical traditions, and contemporary policy analyses, the study synthesizes insights from resource-based theory, dynamic capabilities, national innovation systems, digital divide scholarship, and developmental economics to articulate why AI adoption remains uneven and how targeted interventions can redress these disparities. A multi-layered framework is presented, highlighting technological enablers, organizational readiness, regulatory arrangements, and social acceptance dynamics. Empirical patterns from OECD, World Bank, and UNCTAD surveys illustrate the widening AI-readiness gap between advanced and underdeveloped economies, underscoring the urgency for coherent action. The paper provides a detailed set of policy recommendations tailored for governments and local communities, including digital infrastructure expansion, AI-skilling initiatives, public–private innovation centers, local data ecosystems, adaptive regulatory sandboxes, and community-led entrepreneurial support systems. A structured policy implementation table outlines step-by-step operational strategies for each actor. The paper concludes by arguing that underdeveloped economies can transition from technological dependency to inclusive innovation leadership if AI adoption is approached as a long-term developmental infrastructure rather than a short-term digital upgrade. This work contributes to global discussions on inclusive technological progress and offers actionable pathways for low-income nations to build equitable AI-enabled entrepreneurial futures.

Keywords: Artificial intelligence, Business analytics, Entrepreneurship, Underdeveloped economies, Innovation ecosystems, Digital transformation