Opportunity Search in the Era of GenAI: Navigating Uncertainty in an Expanding Universe of Imaginable but Unknowable Futures

Stratos Ramoglou, Yanto Chandra and Qian Jin

Journal of Management Studies, 2026, vol. 63, issue 2, 695-721

Abstract: Entrepreneurship has often been viewed through a lens of scarcity of creativity. Yet, the arrival of generative artificial intelligence (GenAI) forces us to appreciate that the bottleneck of entrepreneurship is not the lack of creative ideas but Knightian Uncertainty. In an era of abundant entrepreneurial ideas, what matters is whether AI‐generated entrepreneurial futures are possible or figments of machine imagination. However, extant theory offers little guidance on navigating opportunity uncertainty – let alone amid an ever‐expanding universe of AI‐generated ideas that increases the risk of unsustainable venturing. Addressing what we theorize as a “grand epistemological challenge”, we develop a model of intelligent opportunity search. The architecture of the model is informed by Gerd Gigerenzer’s paradigm shift in decision‐making under uncertainty, centred on the use of heuristics that match the structure of the environment. Our model advances a symbiotic division of epistemic labour between machine and human intelligence guided by decision strategies attuned to the structure of the decision environment as reshaped in the GenAI era. The gist of the model is that machine creativity expands the ideation space through generative variation, while human judgment contracts it through a curation process geared towards the elimination of non‐opportunities. This structured opportunity detection process reflects a new ecology of entrepreneurial action, where successful opportunity search depends less on human creativity and imagination and more on eliminating what cannot be actualized. Besides advancing a novel perspective on the nature of human and machine symbiosis, this paper unpacks implications for opportunity theory and Knightian Uncertainty.

Date: 2026
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