IP management is time consuming and risky ? errors can lead to significant value losses. Law firms and corporate IP departments must manage intellectual property in multiple jurisdictions and across different products and services. Historically, this process has been manual and slow.
The number of patent filings between 2014 and 2015 suggests that IP assets are growing at an annual rate of approximately 7.8%. While searching for and maintaining IP documentation can be tedious, new strategies for developing IP services using end-to-end automation and outsourcing aim to provide legal and corporate IP departments with more effective ways of managing their intellectual property.
Existing IP management strategies target the following areas:
- identifying the value of intellectual property across multiple jurisdictions;
- protecting intellectual property more effectively;
- providing automated responses to office action;
- automating IP-driven insights and provide better decision making; and
- employing human intervention to provide semi-automated analysis with more accuracy.
In a nutshell, IP management involves creating, protecting, managing and optimising intellectual property. Each of these stages might include automation ? for example, integrating machine learning and artificial intelligence to provide faster data with greater accuracy.
Future IP professionals are likely to favour R&D, decision-making and protection strategies for intellectual property rather than just protecting it. Therefore, organisations should make strategic decisions by analysing their own IP portfolios and those of other organisations to identify any technological gaps and formulate their IP strategies accordingly. Companies have access to over 100 million patents in more than 150 countries at the click of a button. Future IP strategies should focus on making this access smoother, faster and more informed through automation. Such an insight-driven approach would be advantageous to companies as existing processes require a lot of manual intervention.
Automation ? including artificial intelligence and machine learning ? has already infiltrated the IP industry; it is utilised in data sanitisation for bibliographic details of patents, docketing, automated response generation and information disclosure statement (IDS) generation. By reducing manual intervention, automation has increased the overall efficiently of IP professionals, allowing them to focus on strategy rather than the manual aspects of IP management. Automating searches for prior art could reduce the time required to prosecute IP infringement. For office action, IDS generation and prior-art identification, automation would provide faster IP application processing for applicants and examiners.
IP management and optimisation
In order to monetise an IP portfolio, a company must first determine the potential revenue of its patents. However, these IP assessments are usually performed manually. While some companies employ IP management and ranking systems to manage their portfolios, existing solutions still require human intervention.
The future of IP management lies in complete automation, which would offer more effective portfolio licensing and acquisition strategies. At the click of a button, users would be able to assess the value of their intellectual property and identify the best strategies to manage it.
Companies have already automated patent ranking and valuation tools, but these tools are based on objective parameters. With IP data coverage expanding and its availability more widespread, big data analytics will play a crucial role in helping companies expand their IP portfolios using accurate and global insight. The data generated through automation will offer future IP professionals the ability to work together to formulate business-driven IP management strategies.
Future IP management strategies should focus on complete automation and utilise new technologies and software to reduce human intervention and provide strategic insight for IP departments. Automation using artificial intelligence and machine learning will be decisive for improving IP management and information flow. Further, automated patent services will help companies to assess and formulate their IP portfolios strategically. The combination of accurate IP and market data can provide a complete and accurate overview of a company’s position, thus save time and money. IP analysis would no longer be a manual task, but available on-demand at the click of a button.
However, further enhancements are needed to meet the evolving demands of the industry and challenge traditional ways of identifying and managing business assets. Companies would be wise to embrace greater automation in order to benefit from the early-bird advantages offered by this form of IP management.
This article first appeared in IAM. For further information please visit www.iam-media.com.