AI transforming the patent search process. Artificial intelligence (AI) is a broad topic that has subtly and beneficially infiltrated our environment. Although all technological advances have a major impact on human existence, AI goes beyond simply changing lives. It seeks to understand and replicate the entire fabric of cognition and reality.
In its most basic form, AI is simply a computer programme that attempts to learn. AI, like humans, observes and absorbs its surroundings, learning from the information provided to it.
However, as AI technologies advance, reliance on computer systems to make certain decisions within the IP sector has managed to cause trouble and outwit the most enticing IP search strategies. The technical and adaptable IP departments spend the majority of their time making decisions based on machine results or insights. AI systems are crucial in simplifying the typical IP search operation.
AI technologies are assisting IP departments in reducing the effort spent on various IP searches and patent searches in various categories. But, before we get into the roles of AI in patent searching, let’s define patent searching.
What is Patent Search?
A patent search, also known as a patentability search, determines whether your idea is patentable. If a granted patent for the same invention already exists, any authority patent office to which you appeal (e.g., USPTO, JPO, CNIPA, etc.) will reject your provisional patent.
As a result, before investing too much time and money in your innovation, double-check its uniqueness. It is not difficult to conduct a patent search; in fact, many inventors and businesses conduct patent searches to save money.
However, if you have the funds, hiring an expert or using patent search software is often a better option for a more thorough search result. So, how does AI fit into the patent search process? Let’s look at what they have in common.
AI and Patent Search Process
The number of IP assets filed globally is rapidly increasing. According to the WIPO 2019 analysis, between 2018 and 2019, patent filings increased by 5.2%, while utility model applications increased by 21.8%. This upward trend in filings has lasted more than two decades.
As a result, IP resources have grown year after year, and finding meaningful information in this massive dataset is becoming more difficult and time-consuming. With an ever-increasing volume of patent data, manually identifying relevant data and analyzing prior art takes time, especially if clarity and consistency are desired.
AI can help you save time, money, and effort when searching for patents. When conducting patent searches, AI provides high accuracy and superior quality in a timely manner.
Coherent strategy centered on optimal knowledge reuse
Deep learning and neural networks are currently being used in research to classify or categorize patents as well as locate comparable patents. Natural language processing (NLP) is also employed to recommend context-sensitive keywords and synonyms.
This leads to better alignment between the available information and the content that users want to find. AI may also aid in drawing insight into the strengths and limitations of a technological sector in specific locations by cross-referencing with IP data and providing a quick glimpse of the domain.
Patent Search Process Made Easier with AI Tools
There are also AI-powered search engines that find similar previous work by focusing on the desired concept rather than the keywords. They use cutting-edge machine learning technology to analyze documents and find the common threads within them.
AI tools, like infants, have an insatiable thirst for knowledge and are just waiting for us to teach them. As you examine the results provided by the AI engine, augmented AI learns alongside you.
Many AI tools have reactive intelligence, which allows them to grow in conscience and knowledge as we conduct more and more searches.
Improving Patent Databases Using AI
IP professionals now have complete access to a wide range of patent databases and tools that produce reliable patent search results. Many patent databases, including XLSCOUT, Amplified AI, Dorothy AI, Resolute AI, and others, use artificial intelligence to provide analysis and improve searching.
Because of updated algorithms, IP professionals now have more powerful decision-making tools, and they can effectively draw conclusions based on their interpretations and analysis of intelligence outcomes.
AI’s Advantages in Patent Search Process
AI technologies are having a significant impact on the typical IP search operation. Artificial intelligence (AI) technologies are assisting IP disciplines in reducing the time spent on various IP searches and patent search results.
The following are the key advantages of AI in a patent search.
1. Novelty Checking
Patentability searches are performed in-house or outsourced by IP departments on innovations shared by R&D departments.
AI technologies are revolutionizing the traditional way of doing inventive step searches by using NLP, Machine Learning, and sentiment analysis. Users first submit innovative ideas to AI engines to obtain novelty updates and simulation models to determine their likely future stages. XLSCOUT’s Novelty Checker helps you conduct quick first pass prior art searches using AI and Machine Learning models.
2. Improving Patent Performance
IP departments are now taking a more focused approach to filing IP; it is much more focused and with explicit knowledge about where fulfilment is, and ONLY a defined set of patent applications are carried forward—the culling procedure is in real-time and faster using AI.
3. Actions to abandon, maintain, or out-license
Competitive analysis tracking is an ongoing procedure that necessitates repeated searches after a predetermined time period. AI algorithms are useful, and they have the potential to replace manual, time-consuming searches with an automatic warning system.
4. Recognizing the Most Crucial Patents in a Portfolio
Finding crucial patents in a portfolio is a time-consuming task that can be aided by automation by evaluating established factors. Furthermore, by contrasting competition and market intelligence to Patent data, AI algorithms may be able to mimic the behavior of an expert searcher.
5. Invalidity Search Using Automation
Invalidation Search Automation saves approximately 60% of time. AI can analyze the significance of text data and match similarities between different texts using NLP and Machine Learning technology. Automated Invalidation (XLSCOUT’s Invalidator+) combines intelligent patent parameters including classification, citations, assignees, etc. with Natural Language Processing models to generate a quick patent invalidation search to uncover results based on contextual and expert parameters.
6. Innovation Automation
AI can understand user technology and generate new ideas. It aids in defining the scope and additional implementations for a better system design. Ideacue by XLSCOUT is designed to assist inventors with idea generation. Click here to learn more.
Conclusion
Digitalization has resulted in the rapid development of many businesses and industries. Artificial intelligence (AI) is a modern technology that has made a significant impact on a wide range of industries.
AI is a suitable optimization concept due to enhanced computer functionality to perform tasks such as text processing, visual perception, judgement, contextual matchmaking, language translation, NLP, and so on, with the digitalization and creation of big patent data.
AI has advanced rapidly in the IP sector in recent years. Though technology is still a long way from aligning the multidimensionality of human intelligence, it has allowed IP professionals to shift their focus to more strategic duties and make better use of the data that surrounds them.
