On Thursday, October 23rd, LexisNexis Intellectual Property Solutions and Ocean Tomo co-hosted an event in San Francisco, focusing on Data-Driven Decision-Making in IP, with a particular focus on using AI in Patent Licensing. The event brought together about 40 intellectual property professionals, including representatives from leading technology companies such as Qualcomm, Interdigital, Ericsson, Dolby, Meta, Google, Apple, HP, and Amazon, alongside participants from patent pools, patent aggregators, patent assertion entities, prominent law firms, and economic consulting organizations.
The session opened with a keynote presentation by Tim Pohlmann, Managing Director, Americas, who illustrated the critical role data can play in guiding patent licensing discussions. Tim emphasized that data provides an objective lens through which parties can better understand patent ownership structures and explore potential royalty rate ranges. As he explained, “Data will never provide a precise dollar value for a patent portfolio or determine the exact royalty rate, but it offers a range. With these ballpark figures, negotiating parties have a reference point for meaningful discussions.”
Tim supported this perspective with a real-world example involving the licensing of Wi-Fi 6 patents. Using the LexisNexis IPlytics database, he demonstrated how patent pool coverage can be calculated and how publicly available royalty information, such as patent pool rates, can be used to extrapolate an aggregate royalty rate. While these results yield a range rather than a single definitive number, they allow licensors and licensees to approach negotiations with greater clarity and confidence.
He further noted that “there is currently limited transparency in the public domain regarding who owns specific patents and how many patents are included in a pool compared to what exists outside it for technologies such as Wi-Fi, Video or Audio Codecs, Cellular IoT or Wireless Charging standards such as Qi.” By mapping the relevant patent landscape for a standard or technology, IP licensing professionals gain an objective benchmark. This enables them to compare new deals with existing agreements, public rates, or court-determined benchmarks, ultimately supporting more informed and efficient licensing decisions.
The audience at the event was notably well-balanced. On one side were IP professionals with years of experience establishing licensing programs and enforcing patent rights, while on the other were IP professionals who often find themselves on the receiving end of patent licensing requests. Both perspectives recognized that a more informed approach, incorporating objective data, facilitates reaching a consensus on what constitutes a reasonable royalty rate.
A distinguished panel of experts was invited to the stage to share their daily experiences in patent licensing and to discuss how data informs the negotiation and closing of deals. Tim moderated the session, bringing together an impressive group of industry leaders, including Gail Su, Senior Counsel at Google; Sean Clark, Vice President of Licensing at Adeia; Atolani Akinkuotu, Associate General Counsel at Meta; and Sam Wiley, Managing Director at Ocean Tomo.
The panelists emphasized that while data plays a crucial role in bringing parties closer together, it represents only one element in a broader mix of information needed to navigate the interests of all stakeholders. They elaborated that negotiations also rely heavily on comparable licensing agreements, ensuring that competitors are treated consistently. However, such agreements are often protected under non-disclosure agreements, and even when disclosed, there is the risk that selectively referencing them may not provide an objective picture of industry standards.
Licensing discussions, the experts explained, are also inherently tied to the underlying technology and the value it brings to a product or service. Furthermore, successful negotiations require alignment not only among IP licensing teams but also across the broader management structures supporting them, whose goals often include maximizing revenue, profits, or reducing costs for shareholders.
Sam Wiley from Ocean Tomo noted, “I have been working in the IP space for two decades, and using data is always my first step. It provides a directional understanding of where we stand. It serves as a starting point that allows me to focus and reduce complexity.”
Atolani Akinkuotu from Meta added, “Patent licensing can involve dealing with grey zones. It is our responsibility to ensure we close sound agreements, and data helps illuminate areas that are otherwise opaque. Using data increases my confidence in assessing what constitutes a fair royalty rate.”
Sean Clark from Adeia observed, “The biggest challenge for me is entering new industry verticals and initiating negotiations with IP teams that have limited prior experience in patent licensing. Data serves as a neutral and objective reference point, helping to educate these teams.”
During the discussion, both the audience and the expert panel agreed that the use of data analytics in IP workflows has become a standard practice. Nevertheless, they emphasized that the subject-matter expert who interprets and applies the data remains central to the process. The consensus was that IP professionals operate in an inherently complex environment, and that patent licensing cannot be resolved solely by data. Although organizations are increasingly embedding patent data analytics into their processes, human expertise remains essential for validating, refining, and providing context to the information.
The discussion among attendees and panel experts also touched on the particularities of licensing standard-essential patents (SEPs) compared to patents that are not related to standards. When SEPs are involved, the stakes are typically very high. SEPs represent some of the most valuable intellectual property assets, with royalties for widely implemented standards often reaching millions of dollars. The broad adoption of these standards across smartphones, computers, and even adjacent industries, such as automotive, logistics, medical technology, smart metering, and home appliances, can create challenges. In many cases, the Original Equipment Manufacturer (OEM) has limited technical knowledge of the patented technologies being licensed. Nevertheless, SEPs are most often licensed at the OEM level, which can lead to conflicting perspectives between licensing parties: SEP owners may have a very different view of the value their patented technology contributes to a final product or service than the OEM does.
At the same time, because most SEPs are widely licensed and many standards are covered by multiple patent pools and licensing programs, the SEP licensing landscape is relatively well understood. There are numerous reference points and, thanks to sophisticated data providers such as LexisNexis IPlytics, among others, increasingly reliable insights into who owns which patents for specific standards. Still, SEPs typically relate to highly complex technologies such as 5G, a field specified by more than 1,200 technical specifications describing a vast and continuously evolving ecosystem. Moreover, standards rarely remain static. They evolve through successive versions and generations, each introducing a wave of newly filed SEPs. This ongoing evolution is why very few standards are royalty-free or consist solely of expired patents.
Among the most relevant technologies discussed at the conference were cellular standards such as 3G, 4G, and 5G, along with their associated IoT protocols including Cellular IoT (NB-IoT, LTE-M, Cat1, and V2X); Wi-Fi generations; video codecs such as AVC, HEVC, VVC, AV1, and VP9; audio standards including AAC, OPUS, MPEG-H, EVS and IVAS; wireless power technologies like Qi 1 and Qi 2; and smart home connectivity standards such as Matter, Thread, ZigBee, Bluetooth Low Energy (BLE), and Z-Wave.
The expert panel and attending professionals engaged in a lively discussion on the ways AI currently supports IP practitioners. Many IP professionals today approach AI with cautious skepticism, questioning its ability to address complex intellectual property challenges, such as AI-assisted claim charting or AI in patent licensing. One attendee in the audience commented, “These days, we sometimes receive a dozen AI-generated claim charts accompanied by a letter from a party seeking a license. While these charts may appear impressive at first glance, a deeper review often reveals fabricated claims, fictitious products, and incorrect mappings of elements. Understanding these charts frequently requires more time than traditional analyses.”
Sam Wiley from Ocean Tomo added, “Yes, we have explored many AI solutions, and often the results have not been particularly useful. However, when expectations are aligned toward generating evidence-of-use analyses rather than perfect claim charts, we have observed some positive outcomes.”
Overall, the audience appeared to share the view that AI-assisted claim charting has not yet lived up to the high expectations placed upon it. Nevertheless, the consensus was that the technology is still in its early stages, and with additional time, experience, and refined prompting techniques, AI could be leveraged more effectively to support IP workflows.
An attendee from the audience noted, “Another issue is that AI often provides inconsistent responses, which is problematic in an industry such as patent licensing, where reliable data and consistent messaging are critical for establishing trust among all parties. Currently, no one can guarantee that AI is unbiased or that it will consistently produce valid results over time.”
Tim Pohlmann responded, “I agree with that concern, but AI can still significantly support workflows, reducing effort and enabling humans to accomplish more in less time. Moreover, it allows us to look beyond the immediate information in front of us and uncover insights we might otherwise overlook.”
At the conclusion of the event, both attendees and the expert panel explored the evolving landscape of technology and markets in recent years, highlighting the growing convergence of industries. Software, connectivity, and AI are increasingly merging into traditionally separate sectors such as healthcare, logistics, energy, manufacturing, and finance. As technology becomes more complex, so too does patent licensing. Each patent license, in essence, must anticipate the future: how the business will evolve over the next five years, the volume of products that will be shipped, and how the technology will shape the success of those products and services.
The convergence of connectivity and AI into new industries also heightens the risks of IP enforcement and infringement. Today, healthcare or industrial manufacturing companies increasingly function as technology companies. This transition exposes them to highly patented areas of technology, populated by industries with a long history of active patent licensing and enforcement practice. The stakes are significant for all parties involved. On one side, patent holders have invested billions in research and development to advance connectivity, and they rely on licensing revenues to meet shareholder expectations. On the other side, innovative product companies adopt these highly patented technologies to enter new market segments, enhance their offerings by connecting devices to one another and the Internet, and integrate AI and software into traditionally mechanical products. These opportunities, however, come with the risk of royalty obligations or potential IP litigation in domains where the companies may have limited prior experience.
AI presents a powerful opportunity to manage this increasing complexity and derive actionable insights. Objective, high-quality data serves as the foundation for any meaningful AI-driven analysis. For any innovative companies, the time is now to be proactive: to envision how their business may evolve over the next five, ten, or even fifteen years, and to align their IP strategies with these emerging business realities.
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