Will AI Help Solve IP Valuation Challenges?

Adopting AI Technology to Ascertain IP’s value

AI technologies can, in many aspects, facilitate finding the inherent values of IPs, and thus foster the IP pledge and patent securitization deals. AI supervised learning (a machine learning algorithm) can assist professional appraisers to determine the value of a patent more objectively and consistently. These improvements are increasing the confidence of parties in IP monetization deals which, in turn, increases deal flows in the financial system. With this new tool, an important trend is emerging in business ventures: leveraging AI applications in patent pledges and, more broadly, in IP monetization. About a dozen startups in China are now seeking to establish sustainable business models involving such new services.

In October 2019, Spring IP Group, a company dedicated to enterprise innovation through AI and data mining tools, conducted a survey on the top ten leading Chinese companies in this area.

The Current Players
The survey provided the following interesting results:

• Founders of these startups used to be in the business of appraisal, translation, legal research, or patent research. They used to be in the IP service industry, where they faced worsening price competition. As such, moving into a new AI business appeared to be a reasonable choice.
• Two out of the ten companies surveyed have overseas connections. To jump-start their business, these startups with overseas connections received AI technologies or investments from partnerships in more advanced countries. On the other hand, the remaining eight startups with no overseas connections appeared savvier in marketing strategies.
• The services they provided were at different stages of maturity. Three startups had already started building an AI/big data valuation module in their database. The rest were still using traditional IP search tools to manually determine the value of IP. The difference in efficiency and accuracy between these two groups may widen as the AI algorithm improves. The market will see that “the winner takes it all” and expects to see two or, at most, three startups survive to dominate the markets.

Limited Potential
Is such adoption of AI for IP valuation a potential business? Probably not. Our analysis in chapter 1 does not consider AI-enhanced IP search service to be one of the potential business models in the coming years. The ongoing development of this area in China is likely to help ease the difficulties in IP valuation, and thus facilitate IP monetization in this market, although, the potential of such AI ventures seems limited. Business norms suggest that the use scenarios, not the tool alone, will determine the value of a tool. Just like the individuals who sold shovels during the California Gold Rush — if they were not selling this particular item in that specific time and particular region, the sale of the shovels would have not been nearly as profitable, no matter how efficient or advanced they were. Likewise, the same applies to the profits made by miners in the recent bitcoin rush. The tools being sold need to be placed within a particular context where users have a burning need for it.

Similar to AlphaGo, Go Game’s current AI application does well in replacing human brain functions under a preset rule and in a limited area. AI-enhanced IP search service now well-supports a narrow technical function in the IP-related work of a company. However, for AI application to help with business decisions more generally, it will need to cover interactive rules and integrate information from multiple aspects that may impact business judgment.

Satisfying a Burning Need
Under the current economic circumstances, most companies have a burning need to upgrade and transform, to meet the new global economic orders. An AI-enhanced IP search tool could indeed save money and increase efficiency, but it still leaves gaps to meet that burning need, leaving the solution incomplete. The recent shutdown of a US$75 million LegalTech startup in March 2020 exemplifies this mismatch between the needs of the market and the products available.

A more complete solution calls for an exercise to integrate big data in market trends, IP strategies, and intelligence of the technology or industry supply chain. As such cross-border thinking and interdisciplinary training are required for this exercise, the startup teams aimed at this solution are still very rare in the market.

Dr. Jili Chung is currently working in Greater China. Jili is the founder of SpringIP Group, dedicated to foster enterprises’ innovation through AI and Big Data tools. Carlo Geremia at Nctm has contributed to this article.

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Originally published at https://www.ictiger2020.com.