From compliance to strategy: artificial intelligence as a knowledge translation infrastructure in business ecosystems

Purpose This paper aims to examine how artificial intelligence (AI) can facilitate knowledge translation (KT) within the accountant–small and medium-sized enterprises (SMEs) business ecosystem, addressing the widening gap resulting from the decline in compliance-based accounting services and SMEs’ growing need for accessible strategic advisory support. Design/methodology/approach This study uses an interventionist research approach to examine the development and implementation of the Strategy Revolution platform as an AI-enabled KT system. The platform incorporates the Strategic Footprint methodology, mapping firms across 71 strategic variables, supported by AI-driven analytics and a professional community. Empirical evidence is gathered from pilot implementations involving accountants and SMEs, combining qualitative data (interviews, observations and questionnaires) with quantitative platform-generated data. Findings The findings of this study show AI supports KT by reducing cognitive load, validating with science, encouraging peer learning and creating feedback loops for improvement. The platform fosters ongoing knowledge sharing, shifts accountants from compliance to strategic advisors and boosts collective competitiveness. As a qualitative and exploratory study, these results are interpretive and do not confirm economic or performance benefits. Originality/value This paper enhances knowledge management by framing AI-enabled platforms as ecosystem-level infrastructures for knowledge sharing. It introduces algorithmic mediation in KT processes and shows how AI can change professional roles and bridge knowledge gaps among actors. While much literature on generative AI in knowledge work views AI as a productivity aid, this study uniquely theorizes AI as a KT infrastructure at the inter-organizational ecosystem level. Algorithmic mediation is seen as a fourth translation mode, complementing Carlile’s (2004) syntactic, semantic and pragmatic types.