From Tool Availability to Adoption Depth: A Provider-Led Enablement Model for Responsible AI/MarTech Use in Emerging Markets

Abstract

In many Georgian and regional markets, AI/MarTech tools are increasingly available, yet client organizations often fail to convert 'tool access' into sustained, value-producing use. This study develops a theoretical model of the influence of provider-led enablement on adoption depth and them on the outcomes for AI/MarTech deployments, with two key boundary conditions: (1) responsible AI and governance maturity as a trust and risk-management mechanism shaping routinization; and (2) go-to-market context (B2B vs. B2C) as a structural condition influencing success metrics, stakeholder configurations, and value realization pathways. A three-stage mixed-method design is proposed: theory-building case study analysis, survey-based model testing via SEM/PLS-SEM, and a design-oriented pilot to translate results into an evidence-based enablement playbook and competency rubric. Key contributions include a formal conceptualization of enablement intensity and adoption depth, a provider-centered explanation of capability transfer, and theoretically grounded propositions for responsible, scalable adoption in emerging and small-market environments.