AI-Driven Innovation: Towards a Conceptual Framework

Sergey Yablonsky

Chapter 6 in Artificial Intelligence and Innovation Management, 2022, pp 97-116 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The main purpose of this chapter is to discuss AI-driven innovations. Generally, the links between AI technology, AI usage, and organizational performance remain unclear. To improve the efficiency of artificial intelligence implementation, reduce costs and shape new business opportunities, firms should understand the features, capabilities, and the impact of these innovations on business models, business processes and employees. This area however is very little studied. To address this gap, an AI-driven value chain framework is proposed, which makes it possible to create a reference model (taxonomy) of AI-driven innovation processes and innovation types. Finally, an AI organization maturity model and an AI-driven maturity framework are discussed.

Keywords: Artificial Intelligence; Innovation Management; Knowledge-Based Perspective; Decision Making; Entrepreneurial Opportunity; Ai-Driven Innovation; Automation; Research Process Disruption; Value Proposition; Business Scaling; Fair; Inclusive and Anticipatory Leadership; Social Impact of AI; Living Labs; Public Procurement of AI (search for similar items in EconPapers)
JEL-codes: O3 O31 O36 (search for similar items in EconPapers)
Date: 2022
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