Transforming Legal Teams with AI to Make IP a Growth Driver – with Leaders from Clarivate and AbbVie

This interview evaluation is sponsored by Clarivate and was written, edited, and revealed in alignment with our Emerj sponsored content guidelines. Learn extra about our thought management and content material creation providers on our Emerj Media Services page.

Legal and mental property (IP) groups are going through mounting strain to transfer past conventional administrative features and function strategic enterprise enablers. From managing advanced regulatory environments to extracting industrial worth from innovation, the expectations are rising — and so are the dangers. 

Many organizations nonetheless depend on fragmented techniques for overseeing mental property and AI instruments, making it troublesome to scale oversight, uncover new income channels, or mitigate enterprise-wide publicity.

Patent filings are one clear sign of this strategic shift. According to the World Intellectual Property Indicators 2024 report, world patent functions surpassed 3.46 million in 2022 — the twelfth consecutive 12 months of progress. 

As WIPO notes, this sustained improve displays a rising world demand for cover of innovation and funding. Yet regardless of this quantity, many companies wrestle to benchmark their portfolios towards evolving markets, leaving beneficial belongings underutilized or misaligned with enterprise aims.

The increasing use of AI introduces complexities, significantly in governance. According to the OECD’s 2024 State of Implementation of the AI Principles report, solely 19% of surveyed enterprises have inside insurance policies for the cross-functional governance of AI techniques. This governance hole poses vital dangers, together with potential misuse and lack of accountability, that are vital considerations for authorized and compliance groups, particularly when AI instruments are built-in into delicate workflows like doc overview and contract era.

Meeting these challenges requires greater than inside guardrails. Legal and IP groups want frameworks that combine compliance with proactive decision-making and align intently with IT, procurement, and line-of-business leaders.

Emerj not too long ago featured discussions with two IP consultants in a particular sequence of the ‘AI in Business’ podcast to shed larger gentle on how AI will be deployed to assist resolve these challenges for IP groups. 

In their respective appearances on the podcast, Shandon Quinn, Vice President of Patent Intelligence, Search, and Analytics at Clarivate, and Christo Siebrits, Senior Associate and General Counsel at AbbVie, share how authorized and IP leaders can construct techniques that do greater than handle threat — they assist authorized function a strategic engine for progress.

This article examines the next vital insights from each visitors for IP leaders deploying AI of their operations:

• Benchmarking IP portfolios reveals progress alternatives: Competitive evaluation frameworks assist determine the place patents can generate licensing income or enhance market positioning.
• AI adoption for predictive patent technique: Predictive analytics permits IP groups to assess the longer term relevance, industrial viability, and authorized threat of patents — empowering smarter R&D investments, budgeting, and cross-functional alignment.
• Centralizing AI utilization audits curbs authorized threat: Proactive auditing of AI instruments throughout groups ensures higher procurement selections and decreased legal responsibility publicity.
• Establishing AI governance throughout authorized features: Cross-jurisdictional insurance policies enable authorized groups to handle third-party fashions with consistency and transparency.

Benchmarking IP Portfolios Reveals Growth Opportunities

Episode:  How AI Is Reshaping Patent Strategy and Portfolio Management – with Shandon Quinn of Clarivate

Guest: Shandon Quinn, Vice President of Patent Intelligence, Search, and Analytics, Clarivate

Expertise: Patent Intelligence, Intellectual Property Strategy, AI Adoption in Legal Workflows, Portfolio Valuation

Brief Recognition: Shandon leads Clarivate’s world patent intelligence, search, and analytics operations, serving to enterprise shoppers leverage AI-driven options for portfolio benchmarking and monetization. He beforehand held senior product management roles at Elsevier, the place he oversaw acquisitions and product progress initiatives. A acknowledged skilled in mental property and AI-enabled productiveness throughout regulated industries, Shandon holds a BSE in Chemical Engineering from Princeton University.

Shandon Quinn begins his podcast look explaining to the chief viewers that, for years, mental property administration has been seen primarily as a defensive necessity — or a approach to shield improvements from infringement and keep aggressive obstacles.

But in a data-driven economic system, IP is more and more acknowledged as an energetic supply of strategic intelligence. The problem for a lot of organizations, he emphasizes, lies in turning uncooked patent data into actionable insights that serve broader enterprise objectives.

Shandon then argues that benchmarking is the software that transforms patent knowledge from an administrative perform into a progress engine. He explains that firms too typically consider their IP portfolios in isolation, measuring success by counts and submitting charges somewhat than by strategic relevance or market positioning: 

“We’ve traditionally seen IP groups concentrate on quantity — what number of filings, what number of patents are stay. But with out context, these numbers don’t inform a enterprise story. When you begin evaluating portfolios, you start to see patterns that reveal the place innovation is powerful, the place it’s stagnant, and the place the market’s shifting sooner than you might be. Those comparisons can highlight areas to double down on or determine white areas rivals are starting to fill.”

— Shandon Quinn, VP of Patent Intelligence, Search, and Analytics at Clarivate

Quinn emphasizes that benchmarking permits firms to place their IP not solely in relation to rivals but in addition in rising expertise classes which will redefine future markets. 

Using AI-powered analytics, platforms like Clarivate can map complete ecosystems of patent exercise, revealing the place innovation is concentrated or absent. For instance, a diagnostics agency may uncover it’s trailing in biosensor integration regardless of main in knowledge analytics — prompting new R&D funding.

These insights illustrate how IP administration is evolving from a value middle to a contributor to enterprise worth. Quinn highlights that benchmarking portfolios towards friends and assessing strategic instructions permits IP groups to higher perceive their alternatives.

Shandon additionally notes that patent portfolios can generate income via licensing or sale, and that comparative analytics assist determine which belongings may very well be leveraged out there.

Quinn notes that AI is meant to increase human experience, not change it. Patent evaluation nonetheless requires deep area information, however AI could make that experience scalable by compressing weeks or months of guide work into hours and organizing massive datasets into actionable summaries.

Benchmarking and strategic portfolio evaluation present IP groups with levers to affect income era or value discount, supporting extra knowledgeable decision-making inside the group.

AI Adoption for Predictive Patent Strategy

As mental property portfolios develop extra advanced and world, IP leaders face an amazing quantity of choices — the place to make investments, when to renew, and which filings will really create long-term enterprise worth, in accordance to the IP Business Academy’s 2021 lecture notes on IP technique.

Quinn describes the complexity and calls for of the sphere: “The head of mental property at many firms, I believe proper now, is among the hardest jobs on this planet, anyplace, in any perform, in any trade.”

Shandon highlights that AI instruments allow sooner identification of patents with strategic potential and assist extra knowledgeable assessments of the place to focus sources. This can improve not solely authorized decision-making but in addition collaboration with different elements of the group, corresponding to R&D.

Quinn emphasizes that whereas AI can floor actionable insights and make portfolio administration extra proactive, its best worth comes from supporting — somewhat than changing — skilled judgment. By integrating AI into portfolio administration, organizations can transfer past purely defensive workflows, unlocking extra alternatives to align innovation technique with broader enterprise objectives.

Centralizing AI Usage Audits Curbs Legal Risk

Episode: From Tool Sprawl to Defensible Value in AI for Legal 

Guest: Christo Siebrits, Senior Associate and General Counsel at AbbVie, AbbVie

Expertise: AI Governance, Legal Innovation, Compliance Strategy, Life Sciences Regulation

Brief Recognition: Christo leads AbbVie’s AI authorized and governance technique, guiding moral and compliant adoption of rising applied sciences throughout the enterprise. He beforehand served as Area Counsel for AbbVie’s worldwide markets and as Legal Director for AstraZeneca throughout EMEA. Christo holds a Bachelor of Laws (LLB) and a BA in Law and Economics from Stellenbosch University.

Siebrits opens the dialog by highlighting the rising complexity authorized and compliance groups face as generative AI turns into embedded throughout the enterprise. He factors out that the urgent problem isn’t simply staff’ use of recent instruments, however the group’s readiness to embrace, or include, exterior AI options. Shadow AI — the unsanctioned use of third-party AI instruments by staff — emerges, he displays, the place governance and consolation with third-party instruments lag behind worker curiosity and enterprise wants.

Siebrits emphasizes a sensible method to managing AI instruments:

• Assess knowledge sensitivity and threat tolerance: Identify which knowledge should stay inside and which may very well be used with exterior AI platforms.
• Collaborate throughout features: Work with IT, authorized, knowledge privateness, and enterprise groups to perceive all AI instruments at the moment in use, each inside and exterior.
• Review and replace governance recurrently: Ensure insurance policies evolve with rising instruments and regulatory necessities.
• Document decision-making: Keep a report of threat assessments and rationale for utilizing inside versus exterior options.
• Maintain human oversight: Insert people at vital junctures in AI workflows to validate outputs and scale back exterior threat.
• Foster ongoing communication and consciousness: Educate groups about AI dangers, together with shadow AI, and create pathways for accountable experimentation.

Christo notes that in extremely regulated industries like life sciences, untracked AI exercise can lead to compliance breaches or confidentiality dangers. He stresses that structured processes for auditing and monitoring AI instruments assist groups make higher procurement and deployment selections, decreasing authorized and compliance threat.

He provides that groups can stability inside and exterior instruments by preserving extremely delicate knowledge safe internally whereas leveraging third-party AI for lower-risk workflows, and that monitoring adoption and outcomes helps guarantee investments ship measurable worth.

Siebrits highlights that staff typically don’t notice AI outputs can grow to be enterprise data or that delicate prompts may be saved externally. He stresses that this makes training and consciousness packages important.

Establishing AI Governance Across Legal Functions

As AI adoption scales throughout completely different authorized and enterprise contexts, Christo notes that governance frameworks should be constant but adaptable — making certain ideas apply broadly whereas accommodating how authorized groups really work:

“You need to ensure that your governance ideas are extensively relevant but in addition responsive to how authorized groups really work. What does transparency seem like in a authorized course of? It’s not simply explainability of the mannequin — it’s about whether or not the lawyer understands the complete context during which the mannequin is being utilized, and whether or not they’re educated and supported to use it appropriately. That’s the place threat lives.”

— Christo Siebrits, Senior Associate General Counsel at AbbVie

The precept Siebrits underscores helps a broader vendor alignment narrative: leaders should weigh whether or not to construct or purchase options that meet their governance wants. A vendor may supply explainability however lack the retention insurance policies a authorized division requires, whereas in-house improvement offers management however can restrict agility and scalability.

Embedding governance into procurement ensures that authorized necessities are addressed from the outset. This contains aligning on jurisdictional threat, auditability, and human-in-the-loop protocols. Siebrits provides that even sturdy instruments should earn belief over time. Early missteps can stall AI adoption throughout complete authorized groups.

“If your first use case goes sideways,” he says, “you don’t get a second one.” Governance ensures that every step ahead is deliberate, supported, and sustainable.