Rethinking the logic and practices of entrepreneurial support in the age of Artificial Intelligence: Toward an adaptive and Intelligence-Augmented accompaniment framework

Abstract

Entrepreneurial accompaniment systems, designed in a pre-digital informational environment, are increasingly misaligned with the cognitive heterogeneity, temporal dynamism, and ecosystem complexity that characterize contemporary venture creation. Yet, despite the rapid diffusion of artificial intelligence across organizational and institutional contexts, no integrative conceptual framework has been proposed to rethink the logic of support delivery through the lens of intelligent adaptive systems. This article addresses that gap by developing the Intelligence-Augmented Accompaniment Framework (CAAI), a multi-layer causal model that reconceptualizes entrepreneurial support as a continuous, data-driven, and ecosystem-embedded process. Building on a systematic literature review of 31 Scopus-indexed contributions spanning entrepreneurship theory, organizational learning, AI in management research, and responsible AI design, we identify three structural gaps as the absence of a continuous diagnostic layer. The treatment of ecosystem connectivity as a contextual backdrop rather than an active support variable, and the neglect of ethical governance in algorithmically mediated accompaniment relationships. The CAAI responds to these gaps by specifying causal mechanisms linking AI-driven profiling, adaptive mentoring pathways, ecosystem matching, and performance feedback within a governance-bounded architecture. Five empirically testable propositions are derived. Theoretical contributions to competency-based entrepreneurship theory and responsible AI governance are discussed alongside practical implications for support providers in emerging economy contexts.

JEL Classification : L26, M13, O32, O33

Type du papier: Theoretical Research