Artificial intelligence is making its way into the legal field: 73% of lawyers say they plan generative AI in their work and 46% say they have already used itmainly for research and drafting correspondence. However, many in-house lawyers continue to have concerns about integrating AI into their daily work and what it would mean for job security.

According to the ABA Legal Technology Survey ReportThe biggest concerns are the accuracy and reliability of the technology, data privacy and security, and implementation costs.

From my work with IP organizations, I know that in-house counsel are adopting AI more and more eagerly than their law firm counterparts. They are beginning to use AI for logging, classification, patent research, and trademark image recognition.

For their part, lawyers at law firms are concerned that technology could make patent prosecution even more commoditized, particularly in drafting patents and responding to office actions.

Because in-house counsel often rely on outside counsel to prosecute patents on their behalf, firm lawyers assume the risks and liabilities associated with this work and may therefore be more cautious about entering this uncharted territory.

With this in mind, in-house lawyers can be assured that AI will not replace their jobs. However, it is true that those with AI skills will have a competitive advantage in the IP space in the coming years. By understanding how AI can support legal tech, facilitate internal work and promote professional development, in-house lawyers can overcome their fears and benefit from this technology.

Understanding AI in Legal Tech

AI is already integrated into some areas of the in-house IP counsel role. In-house counsel are leveraging AI for various use cases, including:

• Automating administrative tasks, such as processing PTO documents
• Use of image recognition for brand research and monitoring and to combat product counterfeiting
• Summarizing parts of patents and agreements, assisting inventors in filing new inventions and creating new reports through AI agents and assistants
• Conducting patent searches
• Applying your organization’s classification tree to your patent portfolio and/or third-party patent portfolios
• Support with e-discovery and litigation

Other use cases have gained importance with the emergence of large language models with user-friendly interfaces. These new applications are more closely linked to the substantive legal work typically performed by lawyers:

• Drafting of patents
• Preparation of responses to official notices
• Prepare objections
• Creating patent/product claim diagrams

These substantive use cases are a concern for law firm lawyers. They could lead to further commercialization of the patent prosecution business and are therefore seen as a threat by many freelance lawyers, even though they recognize that they need to leverage the technology to remain competitive.

However, for many in-house counsel, these new use cases represent a great opportunity to do more with less. This is critical at a time when companies are demanding a higher return on intellectual property investments, leading to greater budget constraints for in-house counsel.

While these applications are exciting, legal professionals must be careful not to overuse or over-use AI tools in their work. Current guidelines from the USPTO, for example, remind patent applicants of the risks associated with using AI and provide suggestions for mitigating those risks. Attorneys must review and verify the accuracy of AI-generated documents and ensure that everything is compliant and meets legal standards. This need for oversight is well understood in some non-generative AI use cases, such as automated processing of PTO documents, where the technology can significantly reduce errors and streamline workflows.

Verifying the accuracy of AI-generated work is especially important given the limitations of the technology in its current form. Lawyers should be careful of AI “hallucinations” where generative AI tools invent texts (such as previous legal cases or prior art) that are not real. In addition, privacy concerns must be addressed by ensuring that AI only processes public data and is used securely, for example by using dedicated LLMs for a single client when dealing with private data.

According to the American Bar Association, lawyers must also keep ethical obligations in mind when using generative AI tools. It warned in a recent Ethics opinion that lawyers “must consider their responsibilities to provide competent legal representation, protect client information, communicate with clients, supervise their employees and agents, bring only legitimate claims and issues, ensure candor with the court, and charge reasonable fees.”

While AI can be a valuable addition to in-house legal teams, it must be used responsibly and carefully reviewed and monitored to effectively mitigate risks.