Posts in Technology & Innovation

Managing patent portfolios requires investment. There are significant costs associated with both building and maintaining patent portfolios, but all too often only a fraction of their potential business impact is ever realized. While obtaining and maintaining weak patents is a real concern, the strength of any particular patent, family or portfolio is not always tied to overall strength. Frequently, the problem is that the organization does not really know what it owns, why it owns what it does own, where patents fit from a strategic perspective, and whether the assets can be credibly used to support any commercial outcome.

For much of the last four decades, American innovation policy has rested on a premise that should be obvious but too often is not: strong intellectual property rights are not an obstacle to competition. Quite the opposite—strong IP rights are the precursor to robust competition. The alternative to a robust patent system is not some frictionless utopia of open competition. The alternative is secrecy, copying, and underinvestment. If patents are too weak, companies will rely more heavily on trade secrets. That means less disclosure, less technical diffusion, and fewer opportunities for others to build upon what has been invented. Weak patents do not democratize innovation—they often bury it. Weak patents also reward copycats who find it far more expedient and financially rewarding to take rather than to innovate themselves. These truths were the main point at the center of my recent conversation with Alden Abbott, Senior Research Fellow at the Mercatus Center at George Mason University and former General Counsel of the Federal Trade Commission.

While AI can improve research, drafting, analysis, and overall work product quality, the panel emphasized that it is not a magic button and cannot replace expert legal judgment. The most effective use of AI in patent practice is incremental, targeted, and lawyer-directed—more co-pilot than autopilot. Panelists explored the risks created when inventors, clients, or law firms over-rely on AI-generated disclosures, patent application critiques, or claim strategy recommendations, including the potential for increased attorney workload, inventorship complications, technical inaccuracies, and downstream litigation vulnerabilities. The conversation ultimately framed AI as both a market disruptor and a strategic opportunity for patent law firms. Firms that respond defensively or compete solely on price risk being pushed into an unsustainable race to the bottom. Firms that lean into client education, workflow redesign, transparent billing expectations, disciplined AI usage, and higher-value counseling will be better positioned to compete. The panel made clear that AI will not eliminate the need for sophisticated patent counsel; it will expose which firms are genuinely strategic partners and which are merely labor providers.

The U.S. Patent and Trademark Office (USPTO) is going through a significant digital transformation. With the Office seemingly updating its procedures as rapidly as the latest AI model, it’s important to track what this means for IP practice. AI is transforming the tools governing how the Office now processes what is filed, and the Office’s vacillations on AI inventorship should be top of mind for every practitioner.

This week on IPWatchdog Unleashed, I spoke with Kristen Osenga, who is a Professor of Law and Associate Dean for Academic Affairs at the University of Richmond School of Law. Kristen is a familiar voice to many in the patent community. She has been a regular participant in serious conversations about patent law, standard essential patents (SEPs), antitrust, competition policy, injunctions, and the broader innovation ecosystem.

“Should we insource IP work?” This perennial question is posed by in-house professionals and organizational leaders in corporations, universities, and other institutions—and dreaded by outside IP counsel, who fear loss of insourced client business. Deceptively binary and straightforward, the insourcing question often can’t be answered without in-house teams first exploring a host of underlying considerations. Their decision-making calculus may confront grey areas and vexing tradeoffs, ultimately coming down to rough cost-benefit analyses and gut instincts.

To say we live in perplexing times is an understatement. Everything seems to be shifting beneath our feet, often with seemingly little thought. One example is the move to change how the federal government supports research. It wasn’t until the passage of the Bayh-Dole Act in 1980, which injected the incentives of patent ownership into the system, that the situation changed. And the result was dramatic.

Artificial intelligence has moved beyond the experimental phase in legal practice. The legal industry is no longer debating whether lawyers can or should use AI tools, or whether AI will affect the economics of law firm and in-house legal department operations. Those questions have been answered. AI is already reshaping how legal work is performed, how legal departments manage demand, how law firms are expected to price services, how patent teams analyze portfolios, and how clients evaluate outside counsel.

When the Food and Drug Administration (FDA) approved a new, easier-to-administer version of a popular cancer medicine called Keytruda a few months ago, patients celebrated. But critics quickly cried foul, accusing the drug’s manufacturer of gaming the patent system to preserve its monopoly and prevent cheaper competitors from coming to market. 

During a Senate Judiciary Subcommittee on Intellectual Property hearing on the Oversight of the U.S. Copyright Office on Tuesday, the intersection of copyright law, artificial intelligence, and executive branch interference were the key focuses. Register of Copyrights Shira Perlmutter provided critical updates on the Copyright Office’s modernization efforts. However, the hearing was punctuated by sharp rebukes from Democratic senators regarding former President Donald Trump’s recent attempts to assert executive control over the legislative branch agency.

For years, design patent practitioners dealing with graphical user interfaces (GUIs) and icons have been shackled to the ghost of Ex parte Strijland. If you wanted to get a case through the USPTO for a GUI or an icon, you had to meticulously include a broken line depicting a display screen or monitor. Under the old MPEP 1504.01(a) regime, the effect of the GUI was treated essentially as surface ornamentation applied to that specific physical screen to satisfy the “article of manufacture” requirement under 35 U.S.C. § 171.

Artificial intelligence (AI) is moving faster than traditional intellectual property (IP) strategy was designed to handle. The issue is not simply speed, although speed is certainly part of the problem. The deeper challenge is that AI innovation does not fit neatly into the legacy IP operating model. The assets, development cycles, regulatory environment, and commercial pathways are all different. And the value drivers are increasingly distributed across a spectrum of AI-related intangible domains, which include patents, trade secrets, data rights, software architecture, licensing models, and customer contracts.

Artificial intelligence is no longer a futuristic talking point in patent practice. It is already being deployed by patent practitioners who understand a simple truth: AI is not a substitute for legal judgment, technical understanding, claim strategy, or client counseling. When implemented properly, AI is a force multiplier. It can compress timelines, improve consistency, reduce low-value friction, provide meaningful portfolio intelligence, and allow practitioners to spend more time on the work that actually requires professional expertise.

The U.S. Court of Appeals for the Federal Circuit (CAFC) issued a decision today in TJTM Technologies, LLC v. Google LLC, affirming the U.S. District Court for the Northern District of California’s dismissal of a patent infringement lawsuit and holding that the asserted patent claims are directed to patent-ineligible subject matter under 35 U.S.C. § 101. The nonprecedential decision was authored by Judge Chen and joined by Judges Dyk and Stark.