Though new to the IP stage, AI patent tools have made a big splash in areas such as patent application drafting, office action responses, and analytics. Across law firms and in-house teams alike, these tools are delivering increasingly tangible efficiency gains and practical insights, with capabilities advancing at remarkable speed.

Many IP professionals, including myself, have moved past initial skepticism. We now accept that the cognitive revolution brought by AI will dramatically impact how patent work is done. To survive and thrive, patent professionals will need to adapt and evolve in subtle and significant ways.

Broad acceptance of patent-related AI tools and technologies is an important first step, but it’s just the start of our collective journey. The real challenge lies in translating AI’s promise into sustainable changes in how patent professionals work. If we’re honest, many of us would admit that we’re scrambling (and at times struggling) to gain a foothold on the AI mountain, as we aim to become competent AI “mountaineers.”

Put On Your 3D Glasses

How can we deftly navigate AI’s daunting complexities and fully exploit its incredible power? How can we make sure we’re not left behind?

As patent professionals climb higher up the AI mountain, the fog often thickens rather than clears. New capabilities emerge rapidly, bold claims are made, and it becomes harder to distinguish durable progress from short-term experimentation.

One useful way to gain clarity is to put on “3D glasses.” By viewing AI adoption through three distinct but interconnected dimensions, patent professionals and organizations can better orient themselves, make deliberate choices, and avoid reacting blindly as the terrain continues to shift.

1.        First Dimension – The Individual

To function capably in the AI world, each patent professional must upskill rapidly. Firms should assume that within the next 12 to 18 months, practitioners’ baseline drafting competence will expand to include effective AI prompting, tool validation, and AI-assisted review. Associates who lack these core skills will not be competitive, regardless of technical background. 

Upskilling ideally is achieved through a hybrid approach. For example, professionals should invest time and energy in building skills through doing, experimenting, and self-study. Likewise, their organizations should provide structured training opportunities that expedite each person’s acquisition and development of crucial skills.

The skill premium is shifting from raw drafting throughput to judgment, review, and strategy. AI does not eliminate the need for expertise, but it compresses the time in which expertise must be demonstrated.

2.        Second Dimension – The Collaboration Ecosystem

This dimension focuses on how AI tools can be used to optimize the performance and delivery of patent work within and across organizations, enabling better outcomes with less friction.

Much like systems engineers do, law firms and in-house teams should critically assess the strengths and weaknesses of current processes, both at the micro and macro levels. 

With a clear understanding of where time, effort, and risk are concentrated, enterprises can then reimagine their ways of working and design AI-enabled workflows to enrich collaboration, allow each person to focus on higher-impact tasks, and ultimately elevate their work product and service delivery.

 3.        Third Dimension – The Economic Ecosystem

Inevitably, AI adoption reshapes the economic relationships that underpin the patent ecosystem. Both law firms and in-house teams are responding to legitimate, and often competing, institutional pressures. Understanding these dynamics is essential to navigating the next phase of AI adoption constructively.

Consider the following scenarios:

• You’re an IP partner at a general practice or boutique firm. A key patent prosecution client begins reassessing pricing expectations in light of perceived AI-driven efficiency gains across the industry. The client asks how your firm’s pricing and delivery model reflects these changes, and whether alternative fee structures or scope adjustments can be proposed.

• You’re a senior IP or legal leader at a corporation or university. Executive leadership has instructed you to focus on improving predictability and return on IP spend, and has asked you to explore how AI adoption might support more efficient portfolio development, including selective insourcing and reallocation of work.

• You’re a law school student or early- or mid-career patent attorney, agent, or other patent professional with plans to build your career on providing patent prosecution services, whether in a law firm, alternative legal service provider (ALSP), or in-house setting. As AI capabilities advance, you will have to constantly reassess which skills will remain differentiated and how best to invest in your professional development.

None of these scenarios are inherently unreasonable. Each reflects rational responses to changing technology, economic pressures, and institutional responsibility. The challenge lies in navigating these forces without eroding trust or long-term value across the patent ecosystem.

Perspective from Practice

Having practiced for over 24 years in both private and in-house settings, I have seen these dynamics from multiple vantage points. As a law firm partner in a large IP practice group, I’ve experienced the challenges of building, sustaining, and growing a profitable patent practice in an increasingly competitive legal services industry. As chief IP counsel, I’ve been an architect and implementer of corporate insourcing and other spend-reduction initiatives that cut our service providers’ revenue.

And in my decades as a supervising attorney, department leader, and adjunct law professor, I have worked closely with younger practitioners navigating an evolving profession. Even before AI, each generation faced higher expectations and greater pressure. AI now promises to accelerate and intensify those challenges.

Professionals and enterprises that dismiss the above scenarios as exaggerated, temporary, or driven by FOMO may be gambling with their economic future. A passive or dismissive attitude toward AI adoption appears highly imprudent.

Be Holistic and Future-Minded

Fortunately, proactive patent practitioners and organizations still have time to assess and solve for AI’s impacts on their economic ecosystem. Boutique law firms, practice groups, and in-house teams can stress-test and de-risk current approaches and assumptions. They have time to look multiple steps ahead and plan for the AI-native future.

With foresight and intentional design, enterprises still can architect new ways of working, collaborating, and pricing and delivering services that preserve value, or add new value, that clients and employers are willing to pay for.

In this early chapter of the AI revolution, many in the IP field have concentrated on understanding what emerging AI patent tools can do and putting them to productive real-world use. 

However, given the highly disruptive nature of AI, practitioners and enterprises should approach their AI adoption journey from all three dimensions above. In so doing, they’ll be best positioned to deliver optimal client and business outcomes and safeguard their economic livelihood now and in the future.

The future of patent practice will not be defined by those who use AI more aggressively, but by those who use it more intelligently - aligning incentives, preserving trust, and reallocating human expertise to where it matters most.