Day 1 of the Global IP Impact Summit set the strategic stage, with speakers exploring how IP can create business value in a world shaped by digital transformation, geopolitical change, sustainability demands, and shifting innovation priorities. The discussions showed that bringing IP to the boardroom requires more than strong portfolios; it requires sharper intelligence, clearer communication, and a stronger connection between patent strategy and business outcomes. Read the Day 1 recap article here.
Day 2 carried that conversation into the Innovation Analytics Academy, where the focus shifted from why IP intelligence matters to how teams can put it into practice. Sessions covered a deep dive into the Innovation Momentum Report 2026, integrating LexisNexis® PatentSight+™ with Protégé™ into patent analytics workflows, patent pruning, business pivots, decision-ready insights, and scaling IP analytics with Databricks and AI.
Day 2 discussions kicked off with a deep dive into the Innovation Momentum Report 2026, which offers a different perspective on innovation leadership. Traditional innovation rankings often reward scale. Larger portfolios can appear stronger simply because they contain more patents. But volume alone does not show whether a company is building relevance in future technologies, improving portfolio quality, or gaining strategic ground. A large patent portfolio may indicate past investment, but it does not necessarily indicate where innovation is accelerating now.
Participants learned that instead of asking only, “Who has the largest portfolio?” IP and business leaders should be asking :
Another important thread from the Academy was the role of inventor networks in understanding innovation performance. Patent data not only shows what a company protects; it can also reveal how innovation is organized within the business, because innovation is not only visible in patent filings but also in the structure of collaboration.
The 2026 edition of Innovation Momentum introduces inventor network analysis, using co-invention relationships to identify core teams driving portfolio strength, key connectors linking knowledge clusters, and structural patterns that influence innovation scalability.
Dr. Dirk Caspary, Principal Consultant at LexisNexis® Intellectual Property Solutions, who is the primary contributor to the Innovation Momentum reports and conceptualized the inventor network analysis, explained to the group that although counting patents per inventor can show activity, it does not explain how knowledge moves through an organization. Detailed network analysis can help identify collaborative cores, inventors who work at the intersection between different teams, isolated teams that innovate independently, and emerging technical communities.
For business leaders, inventor network analysis can support competitive intelligence, talent strategy, organizational benchmarking, M&A due diligence, and post-merger integration. A portfolio may look strong on paper, but the organization behind it may be fragile if knowledge is concentrated in isolated teams. Conversely, a well-connected inventor network may signal a more resilient innovation engine.
The Day 2 agenda also looked at how IP teams can move from standard analytics outputs to more scalable intelligence workflows. Traditional patent dashboards remain useful, especially for monitoring portfolios, comparing competitors, and tracking known metrics. But some strategic questions do not fit neatly into a standard dashboard. For example:
These questions require more than visualization. They require analytical infrastructure.
Attendees in this session learned how LexisNexis PatentSight+ Bulk Data provides teams with curated, ownership-verified, family-level patent datasets, enriched with metrics such as the Patent Asset Index. Through the LexisNexis Intellectual Property Solutions Data Platform, built on Databricks technology, teams can work with harmonized, analytics-ready patent data in a secure and scalable environment, query it directly, join it with internal data, and connect it to enterprise analytics tools.
In practical terms, this allows IP teams to move beyond one-off analysis and build repeatable intelligence workflows. Filing routes, protection patterns, renewal decisions, business pivots, inventor networks, and competitive benchmarks can be incorporated into a broader decision system.
The data platform also supports seamless integrations into your own data in other analytical systems like Power BI, Tableau, and Looker, making patent intelligence easier to connect with the systems business teams already use.
The session on integrating PatentSight+™ with Protégé™ into patent analytics workflows, led by William Mansfield, Head of Data Strategy and Quality at LexisNexis Intellectual Property Solutions, reflected a broader shift in expectations. Business stakeholders increasingly want faster answers, clearer outputs, and more direct connections between patent signals and strategic decisions.
William showed the participants how LexisNexis Protégé™ helps IP and business professionals start with a plain-language question, structure the analysis, make the reasoning visible, and generate outputs that can be shared with stakeholders. Its value lies not only in speed but also in how it connects AI-guided workflows to curated PatentSight+ data, transparent logic, and established portfolio metrics.
In PatentSight+, Protégé helps IP and business professionals start with a plain-language question, structure the analysis, make the reasoning visible, and generate outputs that can be shared with stakeholders. Its value lies not only in speed but also in how it connects AI-guided workflows to curated PatentSight+ data, transparent logic, and established portfolio metrics.
That distinction matters. Executives may want to know whether a technology area warrants further investment, whether a competitor is gaining strength, or whether a portfolio supports a business pivot, a licensing strategy, or an acquisition thesis. These are not simple data-retrieval questions. They require context, judgment, and traceability.
General-purpose AI tools can create risk when they rely on unverified sources, lack transparency, or cannot access validated patent data and portfolio metrics. LexisNexis notes that professional patent analysis requires verified data, traceable results, and defensible outputs, especially when the insights support high-value business decisions.
The strongest use of AI in patent intelligence is not to shortcut expertise, but to accelerate expert analysis, make it more transparent, and connect it more easily to business action.
Throughout Day 2, the Global IP Impact Summit Academy sessions moved from innovation benchmarking to inventor networks, from patent pruning to business pivots, and from AI-assisted workflows to enterprise-scale analytics infrastructure. Taken together, these topics point to a clear direction for the IP function. Patent intelligence is moving from reporting to strategy. It is no longer enough to know what is in the portfolio. IP teams must be able to explain where innovation is gaining momentum, which technologies deserve attention, how collaboration networks shape innovation capacity, and how patent data can support decisions across R&D, corporate strategy, M&A, licensing, and portfolio management.
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