Why Academia’s AI Breakthroughs Fail to Reach Market
“Innovation doesn’t stop at discovery—it stops when we fail to translate.”
A recent blog post from Dr. Jean Njoroge, Senior Licensing Manager, explores why so many university AI breakthroughs never make it to market—despite their enormous potential. The article highlights… (Read more.) how academic AI systems are often treated like traditional software, even though they function very differently, leading to major commercialization barriers.
For example, one university-developed AI system could reduce data center energy costs by up to $2 billion annually, yet remains in the lab because it lacks access to real-world testing environments. This story exemplifies a larger issue: less than 5% of university AI innovations ever reach commercial deployment, resulting in billions in untapped economic and societal value.
The post explains that bridging this gap requires AI-native commercialization models—frameworks that recognize AI’s need for continuous learning, real-world data access, and adaptive licensing approaches that go beyond static software paradigms.
Stay tuned for Part 2 of this three-part series, where she’ll explore actionable strategies to help universities accelerate AI innovation from the lab to the marketplace.
Read the full article: The University AI Commercialization Gap – Part 1: Why Academia’s AI Breakthroughs Fail to Reach Market
