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Algorithms in the Realm of Fuzziness. How Generative Artificial Intelligence Is Changing the Front End of Innovation

Francesca Bellesia et al.

Creativity and Innovation Management2026https://doi.org/10.1111/caim.70048article
AJG 2ABDC B
Weight
0.50

Abstract

This study aims to explore how Generative Artificial Intelligence is reshaping human innovation practices at the front end of innovation. The front end of innovation encompasses opportunity identification and ideation activities and has always been considered a ‘human’ phase. For this reason, and due to its potential to generate novel content and propose innovative solutions, the use of Generative AI at the front end of innovation is likely to generate controversies. Building on theories of technology affordances and on 24 in‐depth interviews with innovators from various industries, this study unveils four roles Generative AI assumes in the three phases of the front end of innovation: nudge, sparring partner, accelerator and collaboration enhancer. It also reveals three constraints innovators face when interacting with Generative AI: Generative AI creates biases, levels creativity and diminishes their experience as human innovators. This study provides an empirical examination of how Generative AI is enacted in practice and highlights how users' perceptions drive such enactment. This study further illustrates the multifaceted nature of human‐AI interactions at the front end of innovation, highlighting not only the different Generative AI's uses in the different phases of the front end of innovation, but also their either supportive or constraining, relational or instrumental characteristics. The study further provides managerial insights on how to embed Generative AI at the early stages of innovation and how to manage emerging constraints.

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https://doi.org/https://doi.org/10.1111/caim.70048

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@article{francesca2026,
  title        = {{Algorithms in the Realm of Fuzziness. How Generative Artificial Intelligence Is Changing the Front End of Innovation}},
  author       = {Francesca Bellesia et al.},
  journal      = {Creativity and Innovation Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/caim.70048},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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