Year: 2026
Type: article
Abstract: Research Summary Blending insights from GenAI, strategic reasoning, and empirical grounding in five illustrative ventures, we contribute a theoretical framework for effective strategies of new GenAI firms. They face bifurcated uncertainty (i.e., high uncertainty of a nascent market, moderate uncertainty of a somewhat predictable technology trajectory) such that two complementary strategic logics —Process Perspective (PP) and Resource‐based View (RBV)—are relevant. Second, we identify process‐based (i.e., well‐designed business model and product innovation process) and resource‐based (i.e., superior data, efficient orchestration, complementary resources) advantages. Some relate to GenAI, some generalize. Third, we address what is unique about GenAI entrepreneurship, including strategic implications of GenAI, technology strategy when there is upstream technical dominance and many downstream firms, and a cross‐technology comparison with technologies like software and predictive AI. Managerial Summary The rapid trajectory of GenAI is stunning. Yet many new GenAI firms are simply thin wrappers around well‐known LLMs. Drawing on five illustrative ventures, we contribute a framework for effective strategies for new GenAI firms. These firms face bifurcated uncertainty (i.e., high uncertainty of a nascent market, moderate uncertainty of a somewhat predictable technology trajectory). This calls for creating advantage by navigating high uncertainty markets to accomplish key strategic tasks and relying on foresight to build strategically valuable resources. Specifically, we identify process‐based (well‐designed business model and product innovation process) and resource‐based (i.e., superior data, efficient orchestration, complementary resources) advantages. We also address what is unique about GenAI entrepreneurship, including strategic implications of GenAI and a cross‐technology comparison with technologies like software, predictive AI, and quantum.
DOI: 10.1002/sej.70056
Authors: Kathleen M. Eisenhardt, Xilan Zhang
Institution: Stanford University
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7221523285