Your Patent portfolio is cash under the mattress – AI can put it to work
More than 250,000 patents get filed in the US every year, and every serious hi-tech company guards its IP with teams of lawyers, even for patents that never make it into a shipping product. Run the actual cost-benefit math on that portfolio and most CxOs would find it eye-opening.
The driver is fear of being locked out. What if a competitor patents the button you were about to build? That fear turns most patent portfolios into a depreciating asset sitting idle, cash under the mattress earning nothing, rather than a source of active advantage.
Here’s the innovation harvesting framework I’d apply; build AI into your innovation-harvesting process directly, not as an afterthought once legal has already filed. A multi-variate model can do three things at once; build probabilistic models for predicting which ideas actually succeed as products, identify which existing patents create a genuine differentiator worth defending, and surface new product proposals by collating ideas and patents already sitting in the company’s own knowledge repository, unused.
During my time at Intel, I ran several knowledge- and idea-harvesting initiatives, and the lesson held every time. Structured innovation consistently beats unstructured innovation. From the outside, that structural difference looks like a big part of what separates how Amazon and Google approach new ideas versus companies that leave innovation to chance.
If your patent portfolio is bigger than your product roadmap, that gap is exactly what an innovation-harvesting model is built to close. It is worth a look before the next filing cycle, not after it.