Your Patent portfolio is cash under the mattress – AI can put it to work
On an average more than 250,000 patents get filed every year in US alone. Every company, especially in hi-tech, is notorious about protecting their intellectual property. They hire teams of lawyers to make sure no one steals or copies their ideas; even if these patents never make it to a shipped product.
Run the actual cost-benefit analysis on the portfolio and most CxOs would find it eye-popping.
Fear-of-being-locked-out is what drives this patent hoarding mentality. What if we introduce a click feature in our product and someone else has already patented the ‘Click’ button? Most of the time, these patents become like cash under the mattress; depreciating asset with no returns. While the patent office can address this issue in a very simple way, AI can help organizations unlock the unrealized potential from dust gathering patents.
In fact, AI models should become an integral part of innovation harvesting framework and identify the ideas that are worth patenting. Multi-variate hypothesis can – 1) Create probabilistic models for predicting product success; 2) Identify an innovation that creates a differentiator for an existing product; 3) New product proposals by collating various ideas / patents from the company’s knowledge repository.
During my tenure with Intel, I managed multiple initiatives for knowledge and ideas harvesting. My experience tells me that structured innovation produces far better results than unstructured innovation. Looking from the outside, that’s what appears to be the key difference between Amazon and Google’s approach to innovation and new ideas.
If your patent portfolio is bigger than your product roadmap, that gap is what the innovation-harvesting model will help close.