For decades, Artificial Intelligence (AI) has been a promising technology. The ability to efficiently and quickly manipulate massive amounts of data, identifying trends and quickly analyzing the best solution, can be applied to thousands of day-to-day scenarios. However, it is poised to mature in the era of big data and real-time decisions, where AI can deliver solutions to age-old problems and challenges. 

Consider traffic management as an example. The very first traffic management system in London was a manually controlled, gas-lit traffic signal that exploded two months later. Since that unfortunate beginning, a complex system of traffic management systems, road closures, traffic lights, and pedestrian crossings has contributed to raising the complexity of travelling in the city. Despite the addition of numerous new systems to better manage the system, traffic is moving slower than ever. 

Artificial intelligence has the potential to change this. Accordingly, it can collect data on historical trends, traffic volumes, and current roadblocks to quickly calculate the best solution for London traffic. It is capable of doing so in near real time, constantly refining and managing flow to provide the best solution possible. 

As a result, AI is becoming the go-to technology for organizations looking to solve highly complex and data-intensive problems. AI-powered warehouse robots are being used by digital retailers. Utilities are using artificial intelligence to forecast electricity demand. AI is being used by mobile networks to manage the ever-increasing demand for data. We are on the verge of a new era of AI-powered technology. 

Another market where AI could have a significant impact is the Intellectual Property (IP) industry. Traditionally powered by paper, manual searches, and lengthy decision-making processes, artificial intelligence (AI) can be used to ease day-to-day tasks and produce increased insight from IP data. 

Increasing Efficiency and Lowering Risk 

IP administrative work is one of the most time-consuming and dangerous areas of IP. Law firms and corporate IP departments can cover thousands of distinct items of IP data across hundreds of jurisdictions and thousands of different products at any time. Historically, this was a very manual and time-consuming process. 

Consider a single patent for which a company has sought protection in multiple countries. A network of agents who are familiar with the particular processes required to obtain protection in specific countries will each assist the company in reaching their goal. Along the way, hundreds of pieces of paperwork in multiple languages will be generated, each with its own set of opportunities and challenges. 

Currently, all of this information is assessed manually and then entered into an IP management system. Naturally, this could easily lead to numerous data processing errors. Consider this in the context of multiple patents. The possibilities for error are nearly limitless. Nevertheless, for many businesses, intellectual property is their most valuable asset. A simple typo in entering a renewal date could cost a company millions of dollars. It is worth noting that the World Intellectual Property Organization (WIPO) estimates that approximately one-quarter of patent information is incorrect. As a result, the dangers are obvious. 

Implementing AI

Furthermore, the manual labor involved in data entry consumes a significant amount of time and money. If this activity can be automated, it frees up law firms and IP experts to concentrate on more strategic issues. AI, which excels at processing large amounts of data accurately and quickly, can improve both accuracy and efficiency. This also allows law firms and IP professionals to play a more strategic role in the organization, generating data-driven insights to help shape future company performance while computers handle the more mundane aspects of IP management. 

Correspondence from the numerous patent offices and agent networks can be easily sorted and searched on demand by automating data submission and making sure that every single item of IP has a distinct identifier. After that, an AI engine can be used to identify pertinent information in correspondence, resulting in more rapid and precise results. 

Search and Analytics 

Globally, the number of intellectual property assets is increasing. As a result, IP documentation and resources are expanding. Finding pertinent information in this enormous quantity of data is becoming more difficult. Historically, searches were conducted manually, with static search databases serving as the only aid. 

Artificial Intelligence (AI) and Machine Learning (ML) are capable of not only automating the process of searching massive databases, but they can also store and use previous information to enhance the accuracy of future searches. AI can also be used to provide information about a specific geographical or vertical market. Consider a company that wants to exploit its intellectual property in new markets. It may want to consider which countries are best suited to file for protection. Insight into the strengths and weaknesses of specific markets could be cross-referenced with competitive IP data to provide an instant overview of the most advantageous geographies to apply for additional protection. Research that might have previously taken months to complete can now be completed in minutes by effectively deploying AI. 

XLSCOUT’s Novelty Checker employs Artificial Intelligence (AI) and makes patent searches easier for inventors. The tool searches for similar inventions to yours to determine whether a patent is feasible.   

A step-by-step guide to conducting an AI-powered patent search with Novelty Checker can be accessed by clicking here.

Novelty Checker
XLSCOUT Novelty Checker, source: xlscout.ai

 

Driving insights 

A large intellectual property portfolio is bound to have both strengths and weaknesses. Indeed, one of the portfolio’s weaknesses could be its sheer size. As a patent portfolio grows in size, it becomes more difficult to effectively manage it and gain insight from it. As a result, businesses are limited not only in managing processes like renewals but also in utilizing insight to gain a competitive edge. 

Many intellectual property professionals are already assessing the worth of their patent portfolio. What are the most effective patents? Which generates the most licensing revenue? Which countries are they? What is the value of intellectual property to a company in comparison to the cost of renewal? AI can identify where a company’s IP portfolio is strongest and weakest by analyzing large amounts of data. 

This, in turn:

  • can shape future R&D investment decisions
  • assist companies in understanding their relative strengths and weaknesses in comparison to competitors, and
  • enable companies to learn more about potential opportunities in new markets

Conclusion 

AI is now providing real value to businesses that need to solve complex problems. AI has the potential to empower IP professionals in the field of IP management. Day-to-day IP tasks can be time-consuming, but AI technology allows professionals to focus on more strategic decisions in their portfolio. It will also improve accuracy while lowering the risk of IP insight and intelligence being lost as employees leave. The real opportunity for IP professionals, however, emerges from the insight that AI can provide into otherwise inaccessible and impenetrable volumes of data. AI will assist IP professionals in generating business insight that will allow them to enter new markets, precisely value an IP portfolio, and provide a deeper understanding of both what and where the subsequent generation of IP investment should come from. 

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