Beyond Algorithms: The Hidden Motives Behind AI Success and Failure

Huy Quy; Vuori Natalia; Wee Jean

Product #:IN-2190

Supplier:INSEAD

Discipline:Strategy

Details:Case (PDF) • 16 pages • 2026-01-30

Subjects:

Strategy

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TechCo was founded in 2000 with a headcount of five and an office in Northern Europe. By 2019 it was a market leader in designing, developing and implementing digital and AI solutions for clients – with a workforce of 650. Having initially relied on employees’ internal networks for staffing, coordination and knowledge transfer, TechCo introduced AI-Tool to boost organizational learning and the company’s digital transformation. Its primary purpose was to foster knowledge sharing and management by accelerating how staff found information and experts in various technologies and software. An embedded algorithm collected and analyzed internal data from the “digital footprint” of every member of the organization (with the exception of their social media accounts) and from this generated a map that pinpointed where specific expertise and skills lay, so that people knew who to go to. However, it did not work as well as expected. The first version in 2018 drew negative reactions from staff. A revamped version in 2019 initially attracted more frequent use, but that rate declined over time and the tool was discontinued as of 2021.

Learning Objectives

The case is suited to courses on digital transformation, AI adoption, and change management in the era of AI. The rich narrative inspires discussion of the interplay between trust, technology adoption, and organizational behavior, offering valuable insights for managers looking to implement AI tools in their own companies. It is targeted at master’s level, as well as executive education and customized programmes on change management and digital transformation. The main learning objectives include: 1. Understanding the multidimensional nature of trust (in AI) such as cognitive and emotion-based trust. 2. How organizational members behave differently under different configurations of trust, and how that behaviour impacts the performance of AI in a real-life corporate setting. 3. The implications of different forms of trust on AI adoption and the risk of generating a “vicious cycle” of AI usage that undermines its performance. 4. Strategies to enable managers and/or change agents to foster different forms of trust that are critical for successful AI adoption by employees.