Addressing AI Traps: Realizing the Potential of AI for Innovation Trend Spotting, Monitoring and Decision-Making

Amber Geurts

Chapter 4 in Artificial Intelligence and Innovation Management, 2022, pp 63-74 from World Scientific Publishing Co. Pte. Ltd.

Abstract: This chapter focuses on the utilization of AI to identify and monitor innovation and technology trends to support decision making. There are high expectations from the advances in AI to provide better, more timely and more complete information and insights on innovation and technology trends to support decision making. There is, however, less discussion of what it takes to develop such AI-supported monitoring of innovation, and how such new ways are introduced and affect decision-making processes. We pay specific attention to the challenges of moving towards the adoption of such AI-supported innovation monitoring capabilities. We refer to these challenges as “AI traps.” Addressing such traps is important in the evaluation of the promise of AI for innovation trend spotting, as well as in preventing any disappointments with its potential outcomes. The insights developed in this chapter are therefore meant to help innovation managers realize the full potential of AI for innovation trend spotting, monitoring and, ultimately, decision-making.

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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