The Complementary Roles of AI and Human Intelligence (HI) in Business Knowledge Management

Abstract This chapter describes professional experiences gleaned from about 50 business-related knowledge management projects, where artificial intelligence (AI)-based processes were successfully used to complement and augment human intelligence (HI). These projects covered a broad swathe of business activities, including risk management, marketing (e.g. branding, supply chain, competitive intelligence), external partnerships, change management, legal/compliance and finance, corporate business strategy, R&D, new ventures and organizational restructuring. Data from five of these projects are presented (coded and without attribution) in a deconstructed manner, to draw out key learnings on how AI was deployed and to offer practical suggestions for designing AI business applications. Projects in related areas are mentioned. The knowledge architecture of each project was provided by the Cynefin Framework (Snowden & Goh, 2020) for problem-solving and decision-making. The critical role of this framework was to help position knowledge elements within each of the four framework domains – Clear, Complicated, Complex and Chaos, as each domain requires a different management response. The approach was therefore knowledge rather than technology-led as is commonly the case with many other papers on the subject. Based on the empirical data, it argues for a pragmatic, knowledge-driven way of deploying AI in business that takes into account that knowledge needs are not static but can evolve over time. As a consequence, it concludes that a fresh focus for future research in AI may be needed.