When Does AI Capability Convert to Advantage? A Complementarity-Gated Framework for Startups in Resource-Constrained Economies
| dc.contributor.author | Wanyancha, Mwita | |
| dc.contributor.author | Mollel, Moureen | |
| dc.date.accessioned | 2026-09-07T05:06:47Z | |
| dc.date.issued | 2026-07-31 | |
| dc.description | SDG 9: Industry, Innovation and Infrastructure | |
| dc.description.abstract | Purpose: This paper develops a conceptual framework linking artificial intelligence (AI) capability, competitive advantage, and startup performance in emerging economies, addressing the limited and fragmented understanding of how AI capability translates into venture outcomes in resource-constrained contexts. Design/methodology/approach: The paper employs a structured review of empirical and theoretical literature, grounded in the resource-based view (RBV) and the dynamic capabilities perspective. It synthesizes evidence across studies to identify points of convergence, divergence, and unresolved tension, and on this basis derives a set of testable propositions. Findings: The review shows that AI capability is a multidimensional construct whose translation into competitive advantage is conditional rather than automatic: it depends on complementary resources such as digital skills, infrastructure, organizational and absorptive capacity, and strategic alignment that are systematically scarce in emerging-economy startups. The paper advances a framework in which competitive advantage mediates the AI capability–performance relationship, but in which that mediating pathway is itself gated by the availability of complementary resources, making the capability–advantage link contingent on context rather than a general regularity. Originality: The paper's contribution is not that AI capability requires complements, a point established in prior literature, but that it formalises where complementarity binds: not on the path from advantage to performance, where most mediation literature locates contingency, but on the prior path from capability to advantage itself. It specifies this as three concrete, measurable gating conditions: digital infrastructure, founder AI literacy, and ecosystem support, rather than treating resource scarcity as unmodelled context. This repositions AI capability from a resource assumed to convert into advantage into one whose conversion is itself the object of theoretical and empirical explanation, with the moderated pathway as the paper's central, testable claim. | |
| dc.identifier.uri | https://doi.org/10.70715/jitcai.2026.v3.i4.091 | |
| dc.identifier.uri | https://dspace.nm-aist.ac.tz/handle/123456789/3958 | |
| dc.language.iso | en | |
| dc.publisher | Journal of Information Technology, Cybersecurity, and Artificial Intelligence | |
| dc.subject | Artificial intelligence capability | |
| dc.subject | Emerging economies | |
| dc.subject | Competitive Advantage | |
| dc.subject | Startup performance | |
| dc.title | When Does AI Capability Convert to Advantage? A Complementarity-Gated Framework for Startups in Resource-Constrained Economies | |
| dc.type | Article |