The Future of IP Operations: Efficiency, AI, and Human Decision-Making

IP operations were once seen as an administrative task, but their role has shifted to the center of corporate strategy. In this article, Justin Delfino, Executive Vice President, Global Head of IP and R&D at Evalueserve IP and R&D, explores how efficiency, AI, and human decision-making together define the future of IP operations — transforming them from back-office support into a strategic driver of growth.

Intellectual property was once treated as an administrative burden. That perception has changed. Today, IP is at the heart of business strategy. Shareholders expect to see how portfolios support growth and development. Regulators require evidence of compliance. Competitors monitor filings as part of their intelligence gathering.

The scale reinforces this reality. According to WIPO’s World Intellectual Property Indicators 2024 report, the most recent full dataset available, innovators filed 3.55 million patent applications and 11.6 million trademark applications worldwide in 2023. Innovation is no longer just output; it is an asset that must be protected, managed, and monetised. Yet legacy systems are under strain. Patent offices face record backlogs, and corporate IP budgets are shrinking.

The organisations that will succeed are those that build operations on three pillars: efficiency, artificial intelligence, and human decision-making. These elements are not independent. Efficiency creates the foundation, AI expands capacity, and human expertise provides direction and accountability.

Efficiency is the starting point. As of late 2024, the U.S. Patent and Trademark Office (USPTO) had over 800,000 unexamined patent applications in its backlog. This number represents applications awaiting their First Office Action, for utility, plant, and reissue (UPR) applications. At the same time in 2024 and 2025, several major technology firms announced selective reductions or reallocations in their R&D and related IP budgets, trimming non-core projects and slowing expenditure growth. However, the scale varies by company and is not uniformly in the range of 5 to 10 percent across the sector. Teams are being asked to deliver more with fewer resources.

Process redesign is the only way forward. Automating invention disclosures produces structured and searchable records. Centralised dashboards reduce the risk of missed deadlines. Streamlined prior art searches and information disclosure statements save days per filing.

These improvements may seem small in isolation, but across large portfolios they compound into significant savings of both time and cost. Efficiency provides the baseline from which AI and human expertise can add further value.

AI is already changing how IP teams work.

Patent licensing
A global technology company implemented an AI-assisted workflow that streamlined patent-to-product matching, enhanced evidence-of-use chart preparation, and expedited licensing package delivery. This approach reduced delays, improved negotiation readiness, and enabled the company to scale its licensing program without proportional cost increases.

Landscape analysis
An innovation-driven client needed faster and more consistent visibility across technologies and markets. By introducing an AI-assisted intelligence framework, we reduced data collection, taxonomy building, categorization, and reporting time by 15–20 percent across more than 100 recurring projects. Analysts shifted their focus from manual groundwork to interpretation and strategy, providing decision-makers with timely market and technology foresight.

Prior art search
A global technology company facing increasing portfolio complexity implemented an AI-augmented search framework. Patent understanding, query formulation, and reporting were partially automated, leading to a 20–25 percent reduction in effort per search. Over 1,000 AI-assisted searches have since been completed, enhancing the accuracy, turnaround time, and scalability of invalidity and prior art projects.

AI accelerates processes and scales analysis. What it cannot do is replace decision-making. Algorithms can highlight risks or generate insights, but they cannot balance market opportunity, ethics, or reputation.

This fact is why AI must be seen as an enhancer. By itself, it only magnifies the strengths and weaknesses already in place. A poorly designed process will only become faster at producing poor outcomes. A strong human-led framework, supported by AI, achieves speed and foresight without losing accountability.

Some decisions cannot be automated.

Should a biotech company open CRISPR patents to support global health or keep them closed for competitive advantage? Should a telecoms company pursue litigation over a 5G patent or negotiate cross-licensing to stabilise the market?

These choices involve strategy, ethics, and reputation. Boards and regulators expect clear accountability, not algorithmic outputs. IP leaders, therefore, serve as strategists who link technical claims to revenue and risk, and as decision-makers who determine when to file, license, or walk away from a particular opportunity.

AI can inform these choices, but only human decision-making can weigh the trade-offs and own the consequences.

The future of IP operations is not human or machine. It is a human working with a machine.

A global automaker demonstrates the model. Engineers log inventions in a portal. AI clusters disclosures, compares them with competitor filings, and generates a risk map. Legal teams then receive a prioritised list aligned with business strategy.

The combination is what creates value. Machines deliver speed and volume. Humans deliver direction and oversight. Together, they make a system that is both efficient and accountable.

This integration only works if the systems are connected. AI tools that cannot link with docketing or corporate strategy platforms add little value. And industry requirements differ. Biotech companies need domain-specific training data. Gaming firms prioritise rapid cycles. Automotive companies balance electrification portfolios with licensing across multiple jurisdictions. Vendors that adapt to these needs will lead the market.

The role of IP is expanding beyond compliance and cost.

Qualcomm generates billions each year from licensing. UK universities earn hundreds of millions through spinouts and licensing programmes. Patent pools for video codecs produce recurring revenues at scale.

IP leaders now have a direct role in valuation and growth. They demonstrate how portfolios support market entry, competitive advantage, and investor confidence. IP has become a strategic asset that drives both revenue and market positioning.

The direction is clear. Efficiency provides the foundation. AI enhances and accelerates processes. Human decision-making ensures strategy, ethics, and accountability.

Each component matters, but its full value emerges only when they are combined. AI alone is not a solution. It amplifies the existing processes and expertise. When paired with experienced IP professionals and sound systems, it becomes a force multiplier.

In the decade ahead, IP leaders will shape not only portfolios but also corporate strategy, market entry, and industry disruption. Organisations that remain tied to outdated processes will struggle under the weight of filings. Those that adopt efficient operations, AI acceleration, and human decision-making will turn IP into a growth engine and a competitive advantage.