AI-empowered knowledge management (KM) processes: what effects on decision-making?

Nowadays, organizations’ capability of identifying, organizing, storing, and disseminating knowledge (i.e., knowledge management processes) is deeply affected by the massive amount of available data, potentially negatively influencing decision-making. In this vein, (generative) artificial intelligence (AI) seems to be quite helpful in ameliorating KM processes and, thus, organizational decision-making.

According to the above, we – together with other colleagues – have conducted research¹, trying to answer the following main questions:

1. How is (generative) AI adopted within KM processes in organizations?
2. What factors influence the adoption of AI in these processes, either facilitating or inhibiting it?
3. How does AI adoption in KM processes affect organizational decision-making?

The explorative investigation has been conducted through semi-structured interviews with 52 experts from a worldwide sample of organizations.

The results have been synthesized in an original framework (Figure 1), which related the investigated concepts according to both a linear and retroactive relationship. Moreover, 20 factors affecting AI adoption within KM processes have been identified.

According to the framework, AI, KM, and decision-making are interconnected and mutually influence each other. In particular, based on the influencing factors, the organization chooses ad hoc AI tool(s) and within which KMP adopts it; this generates a specific decision (i.e., automated or augmented or supported), according to the complexity of the problems that need to be solved, which will lead to (positive/negative) results. At the same time, these results will retroactively influence all the other elements of the framework, shaping future AI adoption and decisions.

Managerially speaking, organizations are called to adopt a more holistic approach when addressing AI, KM processes, and decision-making to ensure that the linear and retroactive relationships existing between them are advantageous. In this vein, the six steps of the rational decision-making model² need to be revised to allow managers to fully grasp and exploit how AI can effectively support the decision-making process by enhancing KM processes.

To conclude, AI adoption is crucial for KM processes within organizations as it can help improve their decision-making. At the same time, we reiterate the need for individuals and organizations to “keep their guard up” in the face of excessive enthusiasm and optimism on AI-related practices.

Biographies:

Luna Leoni is an Associate Professor in Management at the Tor Vergata University of Rome (Italy). At the same university, she is a Professor of “Management of Creative Firms” and “Knowledge Management Foundations” as well as Vice Coordinator of the “Master in Economics and Management of Cultural and Tourist Activities”. Her main research interests are creativity, knowledge management, servitization, and tourism. Moreover, she is a Council Member of the European Association for Research on Services (RESER) and Editor in Chief of the International Journal of Information and Operations Management Education (IJIOME). Luna’s research findings have appeared in top-tier business, management, and tourism journals..

Ginetta Gueli is a seasoned knowledge manager and project manager with concrete field experiences gained in national and international organizations such as IOM | United Nations, Boston Consulting Group, Valore D | Diversity & Inclusion, Chetcuti Cauchi Law Firm, Hudson Holding/Nike, InfoCert, etc. Ginetta is part of KM4Dev Core Group and a member of the SIKM Leaders and SIKM Leaders Boston. She was also the KMLobby Executive Producer of Pioneer Knowledge Services which goal was providing KM talk shows and podcasts. Last but not less important, she cooperated with the University of Rome Tor Vergata and the University of Brescia regarding the relationship between KM & AI.

See also our previous article: Interested in AI to improve your manufacturers’ performance and resilience? KM processes are what you need! 

Article source: AI-empowered KM processes for decision-making: empirical evidence from worldwide organisations by Luna Leoni, Ginetta Gueli, Marco Ardolino, Mateus Panizzon, and Shivam Gupta.

Header image source: Created by Bruce Boyes with Microsoft Designer Image Creator.

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