Rethinking Legal Work in the Intellectual Age:

 The Impact of Artificial Intelligence and the Role of Human Judgment

Authors Note:

The following article has been in the works cerebrally for a long time. As I continue to contemplate the benefits of new technologies and specifically AI, as well as adjust how I deliver legal services I have wanted to get these thoughts organized and written down. I am not a strong writer - never have been, through all three degrees I have done my best to avoid writing. I’m a technologist first, not that some technologists aren’t great writers, it’s just not why many of us ended up in engineering and technology programs. Thanks to AI, I can now shape my ideas into written words without the barriers that once were completely daunting.

           This realization about writing and technology became clearer to me during a recent project. One of my many hobbies involves woodworking. I am able to reflect on a myriad of things while I’m in what we call “the shop” which is just me taking over the garage during projects. During a recent project it occurred to me that I was doing the very thing that I have been railing against – not using AI to do the “work”, feeling somehow that I needed to be the writer to be the author of the work to be honest. It’s this mindset and paradigm can be so difficult to change and overcome, even for a technologist.

           The following article was not written by me, it was authored by me. I used AI to get what I wanted articulated, organized, and written in the style and manner that I instructed. Does this make the article somehow less real, or my cerebral crafting somehow dishonest? I will share with the reader that for me it made the process much more enjoyable, interactive, and less daunting. Had I not had an AI tool to use I would have likely never slogged through the part of the task that I simply don’t enjoy.

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Rethinking Legal Work in the Intellectual Age:

The Impact of Artificial Intelligence and the Role of Human Judgment

 In my opinion the legal profession is amid a seismic transformation that is being largely either ignored or not understood. The transformation is driven by a shift from the Information Age—defined by data acquisition and analysis—toward an Intellectual Age where human expertise increasingly revolves around asking the right questions and applying strategic insight. Artificial intelligence (AI) lies at the heart of this evolution, reshaping the boundaries of work and redefining what it means to be a lawyer.

The Shift from Data Scarcity to Data Saturation

Historically, legal work was synonymous with the process of slogging through the task of information gathering: scouring statutes, analyzing case law, and conducting exhaustive discovery. In the Information Age, lawyers were information gatekeepers, valued for their mastery of data, spending countless hours sifting through material to glean actionable insights.

Today, advanced algorithms and legal databases can process, summarize, and cross-reference huge volumes of information—in minutes, not weeks—rendering manual review inefficient, if not obsolete. The bottleneck has moved; now, meaningful work is about filtering insights from the deluge of data readily available to clients and lawyers alike and transforming that information into legal insight and judgment.

My more sophisticated clients have already processed their information via AI and now look to me for collaboration and insight. I am no longer the gatekeeper of information and data. For those clients my job has changed from spending hours upon hours reviewing and redlining to providing usable insight and collaboration. During a recent dinner meeting with a client that is one of the principals for a large real estate and mortgage organization we discussed technology and AI. He shared with me that before he sends me a document, he has already used AI to give him some guidance. He doesn’t need me to slog through the information - he needs me to partner with him to develop a course of action and to develop ways to work through key elements. Candidly, I prefer having a tool that can comb through data and information in minutes and allow me to focus on the higher-level intellectual aspects of the process. That’s not to forgo acknowledging that there are issues related to using these tools, there are and those are best be served in a separate article.

Technical Mechanisms and AI’s Inner Workings

I have always believed it’s important to have some base level of understanding of technology to make the best use of it. Modern legal AI encompasses a spectrum of technologies that are currently available to legal professionals. Below are just some of the most relevant:

Technology-Assisted Review (TAR) and legal AI agents are used to supervise machine learning to triage discovery, flag relevant documents, and eliminate irrelevant ones, learning from attorney feedback to refine results.

Natural Language Processing (NLP) tools drive advanced legal research platforms, interpreting plain-language queries, extracting and summarizing precedent, and ranking documents semantically rather than by pure keyword matches.

Generative AI (GenAI) systems and large language models (LLMs), like GPT-4, Claude, Paxon, Perplexity, Spellbook, Copilot, and others synthesize contracts, memos, and even legal arguments, sometimes producing a basic piece of advice in just minutes—a process that once took junior lawyers an entire day.

Predictive Analytics leverage historical data to forecast outcomes and offer quantitative risk assessments.

Agentic AI coordinates multistage workflow automation, handling everything from intake to drafting to risk scoring with increasing contextual awareness.

These AI systems combine enormous corpora of legal text, advanced neural networks, and iterative training to model the relationships among concepts, rules, and precedents. However, despite their extraordinary speed and scope, they remain bound by the data they process and the quality of the algorithms that interpret it.

Human Judgment: From Analysis to Strategic Inquiry

As technology automates manual and routine data processing, the value proposition for lawyers centers on conceptualization, question design, and judgment. This transition is not merely technical—it entails a profound shift in mindset. Lawyers must move from seeing themselves as “data processors” to “question architects,” focusing on how to direct AI and interpret its output in service of client needs. The profession’s most valuable members will be those who can ask incisive questions, apply legal theory, and navigate ethical, contextual, and practical complexities.

Emotional and Ethical Resistance

As I wrote in my Authors Note legal professionals face emotional hurdles. Years of training reinforce the belief that rigorous legal work involves exhaustive manual analysis—ceding research and drafting tasks to AI can create guilt, anxiety, or a sense of “cheating”. The abstract nature of AI’s black box operations can compound concerns regarding ethical responsibility and accountability. The American Bar Association and state bars stress that lawyers must remain competent, diligent, and ultimately responsible for their work, never delegating their professional judgment wholly to AI. The key is to understand AI as an advanced instrument, akin to historic shifts from handwritten briefs to word processing and online databases, with human oversight and expertise still vital to high-level legal reasoning. One of the examples I use is the shift I experienced during my master degree where some professors still required brute force memory of theorems and equations while others allowed those to be programmed into engineering calculators of the day. The paradigm shift is that lower-level work is no longer the value-add work. I recognize that the billable hour model, to a significant degree, is built upon lower-lever work and have strong opinions on the future of such a model – but that also is a topic for a different article. O the benefit of AI!

Bloom’s Taxonomy: Mapping AI’s Cognitive Boundaries

Bloom’s Taxonomy provides a useful lens for understanding AI’s place within the legal profession. The taxonomy’s progression—remembering, understanding, applying, analyzing, evaluating, and creating—maps closely to AI capabilities: