As the Generative AI (GenAI) hype continues, we’re seeing an uptick of real-world, enterprise-grade solutions in industries from healthcare and finance, to retail and media. As the technology matures, we’re also learning more about its potential, shortcomings, and barriers to entry—ethical considerations, accuracy, hallucinations, and more. But beyond industry, however, there are factors that play into the success or failure of Generative AI projects.
One of those lesser talked about factors is company size. A recently conducted survey by Gradient Flow explores the state of GenAI in healthcare, an industry that’s been on the pulse of the technology since inception. Among other findings, the results show clear discrepancies in the way companies of differing sizes approach adoption, implementation, and priorities of AI.
From budget allocations to model preferences and testing methodologies, the survey unearths the areas that matter most to large, medium, and small companies, respectively. Understanding these nuances can lead to more targeted solutions, higher adoption rates, and less false hope around the transformative power of GenAI.
