I spent the month of November doing what I called an “AI Sprint,” in which I experimented with a lot of new approaches and tried generating new types of outputs. I haven’t shared much of that yet, but I thought this exploration of what “AI in the Middle” might mean in law and law practice was interesting.
This is the topic in AI in law practice that fascinates me the most. I contend that we are overfocusing on what AI might do on commodity legal work and efficiency, and underfocusing on what it might do at the high end of law practice. My question, then, became, does that mean that the middle space might be especially interesting and underappreciated.
There are a number of ways to look at this issue. The area to watch in AI innovation, to me, is in the mid-sized law firm, law department, and legal organization space. See my predictions for legal AI in 2025 in this National Law Review article. I’ll also note that the LegalTechnology Hub has debuted a new Midsized Hub with a focus on midsized firms.
I’ve just pulled a section of the output from a series of prompts I did on this topic last month. I’ve managed the prompts to shape the output in the direction of my ideas and questions, but I have not edited it. There is a goldmine of ideas, insights, action steps, and new strategic approaches in this output. See if you agree? Also, the US Copyright Office has apparently decided that my work in creating this output is not protectable. Would you agree after reading it?
Your clarification reframes the discussion of AI’s potential in legal practice, particularly in redefining the boundaries of bespoke and commodity legal work. By “high-end,” you refer to AI’s ability to act as a stand-in for the most highly customized legal advice—strategic, complex, and nuanced work traditionally reserved for elite, highly compensated legal professionals. The “middle ground,” in this context, represents the domain between commodity legal tasks and bespoke strategic work, encompassing semi-complex, moderately tailored tasks.
This approach frames AI as a disruptive partner in both middle-ground and high-end legal work, with the potential to redefine the delivery of strategic legal services.
Here are refined insights based on this perspective:
- High-End AI as a Strategic Partner
• AI has the potential to function as a preliminary strategist in areas such as trial preparation, negotiation planning, and overarching legal strategy.
• By analyzing massive datasets, precedents, and historical outcomes, AI could provide first-pass recommendations on highly tailored issues, such as:
o Optimal litigation strategies for specific jurisdictions.
o Suggested negotiation tactics based on the opposing counsel’s history.
o Risk assessments for complex, bespoke transactions.
Why It Matters:
This challenges the notion that bespoke legal advice is solely the domain of human partners. AI can offer actionable insights and frameworks that elite professionals can refine, significantly accelerating the process without compromising quality. - The Middle Ground: More Bespoke Than People Expect
• The middle ground includes tasks like contract negotiation, compliance strategies, regulatory guidance, and other semi-bespoke services that require more customization than standard templates but less nuance than high-end legal strategy.
• Current tools, like contract review platforms, often stay within the “commodity” level of automation. However, AI can:
o Draft customized legal documents tailored to specific business models or industry needs.
o Provide detailed “first-pass” negotiation frameworks or playbooks that mimic bespoke advice.
o Perform comparative analysis for regulatory compliance, flagging gaps with contextual explanations.
Why It Matters:
AI has the potential to blur the lines between commodity and bespoke services, delivering scalable solutions that were once thought possible only at the highest levels of human expertise. - The Middle Ground as the Most Disruptive Zone
• The middle ground represents the most economically transformative zone for AI because:
o It includes work typically handled by mid-level associates or lower-cost partners.
o It bridges the gap between efficiency (commodity tasks) and deep insight (bespoke strategy).
• Examples:
o AI-driven mediation tools that suggest compromise points based on precedent and party preferences.
o Strategic portfolio analysis for legal risks across multiple contracts, providing tailored recommendations for each scenario.
Why It Matters:
This is where client expectations are evolving—they want bespoke quality at a lower cost, and AI can meet that demand. - AI in High-End Work: The First-Pass Revolution
• In high-end work, AI can excel as a thought partner during the ideation stage, particularly for:
o Modeling trial strategies by simulating different judge and jury profiles.
o Drafting negotiation roadmaps, including fallback positions and alternative strategies.
o Suggesting legal arguments by analyzing similar cases and predicting outcomes.
Why It Matters:
Partners can spend less time on preliminary work and more time on refining and personalizing insights, allowing them to scale their expertise across more clients. - Redefining Value in Bespoke Services
• Traditional bespoke services emphasize depth of human wisdom and customization. AI, however, can:
o Perform data-driven customization, identifying nuances often missed by humans.
o Generate bespoke solutions faster by analyzing vast amounts of precedent and contextual data.
Why It Matters:
AI enables a new dimension of “bespoke” services that are faster, data-rich, and cost-effective, providing clients with value at scale. - The Middle Ground as a Testing Ground
• The middle ground is ideal for developing and refining AI tools that could eventually migrate into high-end strategy work.
• For instance:
o Tools for mid-level contract negotiation could evolve into complex deal negotiation assistants.
o AI handling semi-complex regulatory guidance could inform bespoke compliance strategies for multinational corporations.
Why It Matters:
The middle ground allows AI to gain credibility, refine its capabilities, and build trust for eventual deployment in high-end legal strategy. - Key Challenges to Overcome
• Context Sensitivity: High-end and middle-ground AI must incorporate nuanced understanding of:
o Client-specific goals and risk tolerances.
o Non-verbal cues and emotional intelligence in negotiations.
• Trust Issues: Convincing high-value clients and top-tier partners that AI can deliver a useful first-pass without diluting bespoke quality.
Why It Matters:
Addressing these challenges will determine how quickly AI moves from middle-ground applications to true high-end bespoke work. - The Role of Human-AI Collaboration
• AI is unlikely to replace bespoke legal work entirely but will elevate human capacity, particularly in high-end cases.
• Example: AI could identify 50 potential arguments for a trial strategy, while a seasoned partner refines the list to three that align with the client’s values and goals.
Why It Matters:
This collaboration allows humans to focus on the most creative and judgment-based aspects of their work while delegating preliminary tasks to AI. - The Economic Case for the Middle Ground
• Clients are already questioning the cost of bespoke services, especially for moderately complex work. AI’s ability to provide:
o Faster first-pass results.
o Semi-bespoke solutions at a fraction of the cost.
Why It Matters:
The middle ground is where AI can reduce cost barriers, allowing smaller firms and underserved clients to access tailored legal solutions. - Building Momentum for High-End Adoption
• Success in the middle ground will pave the way for AI adoption in high-end work by demonstrating its:
o Reliability.
o Practicality in complex scenarios.
Why It Matters:
This phased approach to adoption will help firms build trust and integrate AI into even their most sensitive and high-value workstreams.
Action Steps for Exploring This Space
- Develop Use Cases: Identify specific middle-ground and high-end scenarios (e.g., negotiation playbooks, trial simulation tools).
- Prototype Middle-Ground Solutions: Use the AI Lab to experiment with tools that blend commodity and bespoke work.
- Educate Stakeholders: Present case studies and ROI analyses to demonstrate AI’s potential in this middle zone.
- Refine Bespoke Applications: Collaborate with elite professionals to test AI-driven first-pass tools for high-end tasks.
- Create Adoption Frameworks: Build a step-by-step model for integrating AI into higher-value legal workstreams.
This approach frames AI as a disruptive partner in both middle-ground and high-end legal work, with the potential to redefine the delivery of strategic legal services.
And, yes, I did go on through several more rounds to refine these ideas. I’m not willing to share that output until it becomes protectable.
[Originally posted on DennisKennedy.Blog (https://www.denniskennedy.com/blog/)]
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