At a time when everyone seems to have something to say about AI and companies are increasingly looking to reap efficiency benefits, cutting through the noise can be a challenge. The first section of our Special Report aims to do exactly that: equip chief IP officers with a handbook to help understand how AI intersects with their work and advise on how to take a practical approach to considering the opportunities and risks that arise when shifting work practices to embed AI functionality.
Our first article explores the intersection between AI, innovation and IP and the potential for a paradigm shift in the pace and nature of innovation. In the future, the focus may switch from merely protecting inventions through patents to a more open strategy of publishing, lead-time through inventiveness, and pre-empting competition. It is CIPOs who will have to balance strategy with regulations to safeguard IP while leveraging AI’s transformative potential responsibly.
The second part of our handbook takes a step-by-step approach to how to leverage AI reasoning in IP workflows while managing the crucial balance between potential benefits and data security concerns. This article walks you through how AI can be used in a variety of tasks, including in patent drafting, mining, portfolio management and responding to the threat of enforcement. We also study best practices for integrating AI in IP and break down AI model security, prompt chaining, task decomposition, user involvement, and feedback mechanisms for evolving AI.
CIPOs must also have robust policies in place to ensure engineers and scientists understand the implications of using AI tools when it comes to protecting – or endangering – IP rights. Our third article explores the critical considerations for IP counsel crafting generative AI policies for R&D. In particular, we dive into the risk factors for patents, trade secrets and copyrights and guiding principles for AI policy.
Finally, our handbook explores AI and trade secret management. Tools are being marketing to IP departments that promise to streamline internal processes, monitor breaches and detect misuse via publicly available information. However, concerns around the security and trustworthiness of AI and the barriers to entry for, particularly small businesses, make the spin-up challenging.