Bridging Research and Market Adoption in Artificial Intelligence: an Investment-Driven Framework for Commercializing AI Security Technologies
DOI:
https://doi.org/10.70393/616a736d.343232ARK:
https://n2t.net/ark:/40704/AJSM.v4n3a03Disciplines:
Management ScienceSubjects:
Decision AnalysisReferences:
30Keywords:
AI Security, Technology Commercialization, Venture Capital, Investment Framework, Market Adoption, CybersecurityAbstract
AI security has attracted growing attention from both researchers and investors. However, many technologies that perform well in research environments fail to achieve broad market adoption. This paper examines the development of CrowdStrike, Darktrace, Cybereason, and Qi Anxin, together with several emerging firms. Their experiences suggest that access to capital often affects growth as much as technological capability. In addition to product quality, factors such as market timing, customer demand, and regulation can influence commercial success. The study discusses how these factors interact during the commercialization process and what they may imply for future AI security ventures.
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