Patent attorneys are undergoing a transformative shift due to the advancements in artificial intelligence. Traditionally, a patent attorney measured the value of their services by their hourly rate. Clients may view the issue differently, preferring to give counsel incentives to accomplish these tasks more quickly. This creates an inherent conflict of interest between the attorney and the client. These concepts of value are being challenged and are changing. The integration of AI into patent application drafting threatens to affect this balance further. The perceived value of lower-level, repetitive, or mundane tasks that can be automated will likely be discounted further; the value of high-level strategic planning and thinking, in contrast, will be elevated. This article uses an unscientific yet fair example to explore the mechanics of this increase in value, how AI redefines attorneys’ contributions, and why clients and firms alike benefit from this change.
A mid-level associate at a large law firm billing at $750 per hour aligns with current market standards and expectations. Each hour the attorney spends on the drafting process arguably contributes $750 in value to the client. Yet, not every hour worked delivers the same value. Some tasks require deep, strategic thinking and legal acumen; others are mundane, routine, and tedious.
Preparing a patent application involves a series of discrete tasks. These range from drafting claims to preparing drawings, each requiring an investment of time and resources. Figure 1 illustrates how patent preparation tasks range widely in the amount of “actual value” they offer clients based on the level of skill and mental effort required (scaled for a billing rate of $750). The tasks with values at or above the hourly billing rate have been highlighted in green.
The values presented in Figure 1 are purely anecdotal based on the author’s own perceptions from many years of experience with patent preparation. Individual opinions may differ on these relative values, but the material point stands that different tasks have different real values for clients.
Just as patent application preparation tasks vary in the effort needed, the time traditionally required to complete each task also varies. Figure 2 breaks down the approximate time an attorney may spend on each task, here totaling 20 hours. At a $750 hourly rate, this culminates in a total cost of $15,000 per patent application for the client. Again, the values presented in Figure 2 are anecdotal and may deviate from others’ views, but they should be at least close to ballpark for many patent attorneys with more than a few years of drafting experience.
The tasks demanding the highest intellectual engagement (marked in green), such as drafting the claims or interviewing the inventor, often take less time than more time-consuming but less valuable activities, such as drafting the detailed description or finalizing drawing figures. Notably, the time-consuming nature of certain lower-value tasks not only increases costs but also risks potential bottlenecks in traditional workflows.
By multiplying the value per hour (see Figure 1) by the time spent (see Figure 2) for each task, we can calculate the cumulative value each task adds to the project. Figure 3 shows the resulting total values contributed by individual tasks, underscoring how certain high-value tasks contribute disproportionately to the overall project value. In particular, tasks related to initial invention intake and claims drafting emerge as pivotal, offering both high value per hour and a significant cumulative contribution.
This is where the value of the AI can have the most substantial impact. The ability of AI to automate low-value, time-intensive tasks can free up attorneys to focus more on high-value activities, thereby increasing their effective hourly value. This reallocation of effort favors a quality-over-quantity approach. Each hour dedicated to high-value tasks potentially yields insights that improve the robustness of patents, increasing their defensibility and commercial utility.
Modern AI-driven tools are already capable of handling many lower-value, time-consuming tasks in patent drafting. These tasks, which are shown in blue in our figures, encompass areas that are more mechanical or require minimal intellectual rigor—making them prime candidates for automation. Table 1 outlines the expected impact of AI on attorney productivity by tabulating the example data from the figures above and evaluating tasks based on their automation feasibility and value contribution.
As AI takes on these lower-value tasks, an attorney is left focusing only on high-value tasks—reducing the time spent per patent application to approximately 6.7 hours in our example. This shift allows attorneys to potentially handle three times as many applications within the same time frame.
When only high-value tasks remain for the attorney, the total project value does not diminish. If anything, the redistribution of effort amplifies the attorney’s effective billing rate. Based on the above example, in about one-third of the time (6.7 hours), the attorney contributes about two-thirds ($10,430) of the value through these high-value tasks. Meanwhile, the AI contributes about one-third ($4,570) of the total project value buy handling the low-level tasks more cost-effectively.
This AI-supported structure yields an effective billing rate for our example attorney that exceeds $1,500 per hour—double the value traditionally attributed to their work. Critically, it does so without placing any additional demands on the attorney, who can maintain high standards of professional contribution on a greater number of applications due to the efficiency AI provides.
The benefits of AI-enhanced patent preparation extend beyond the attorney. Clients gain by receiving high-quality applications more quickly and at a potentially reduced cost. While this may seem contrary to the firm’s billing goals, it is not. The economic upside is clear: by handling more applications, revenue increases without a proportionate rise in labor costs. Moreover, the use of AI can lead to streamlined workflows, lower error rates, and a competitive edge in the legal market, where efficiency and expertise are paramount.
Firms adopting effective AI solutions are well-positioned to capture a larger market share. As clients increasingly seek innovation-driven legal providers, firms that utilize AI in substantive, measurable ways can distinguish themselves as industry leaders. Additionally, AI’s capability to produce data-driven insights on task efficiency and project timelines enables firms to more accurately predict and manage caseloads, reinforcing client confidence and satisfaction.
In this AI-integrated approach, the attorney’s role becomes more strategic, focused on tasks requiring judgment, legal expertise, and nuanced thinking. By eliminating the lower-value portions of their work, attorneys are free to engage in higher-order problem-solving and to contribute at a level that more closely aligns with their training and expertise. Ultimately, AI makes patent attorneys not only more efficient but also, arguably, more valuable than ever before.
The integration of AI into patent law is more than a tool for reducing time spent on routine tasks; it represents a paradigm shift in how value is created and distributed in the profession. By automating lower-value tasks, AI enables patent attorneys to double their effective value to clients and firms alike. This shift does not just enhance productivity—it positions patent attorneys to be the strategic, high-impact professionals the legal market increasingly demands.
