As the year winds down, the legal profession is flooded with retrospectives: the growing AI adoption rate by solos and smalls (now around 70%), ways that AI is leveling the playing field between large and small firms (including on the hallucination front where large firms and solos are equal offenders) and the familiar observation noting the shift from chat-based tools to agentic systems. Much of this commentary is accurate — but it’s also repetitive and boring. Rather than regurgitate what most lawyers already know or could readily learn from AI, I’ll take a different approach and examine five distinct business models that offer new opportunities for solo and small-firm lawyers in the AI age.
Let’s take a step back. According to Wikipedia, a business model describes how a business organization creates, delivers, and captures value. For decades, law firm business models have been downright boring, largely based on selling time in billable increments. That’s changed to some degree in recent years with flat fees and law subscription models like Mathew Kerbis’s The Subscription Attorney, but these approaches — along with six new law business models that I imagined years ago — never gained any real traction.
In AI era, all of that may change. And in fact, some would argue that it has to change since with AI cutting down on the time required for legal tasks, billable revenue is bound to decline. But AI can also power new business models, or revive traditional ones. Below are five law firm business models for the AI age that can help solo and small law firms diversify their offerings.
1. Artisanal Legal: “Good Old-Fashioned Law,” Reimagined
The first model may seem counterintuitive in an AI-driven era: Artisanal Legal. This is the deliberate embrace of high-touch, bespoke legal services grounded in judgment, strategy, and human insight — augmented, but not replaced, by AI.
In this model, AI operates largely behind the scenes. It supports research, drafting, and issue spotting, allowing the lawyer to focus on what clients value most: interpretation, advocacy, and trust. The lawyer’s brand is built not on speed or scale, but on craftsmanship. Think of appellate advocacy, regulatory counseling, complex negotiations, and niche advisory practices where outcomes hinge on experience rather than volume.
As AI commoditizes routine legal outputs, the perceived value of deep expertise and individualized counsel will increase, not decrease. Clients facing high-stakes matters will seek lawyers who can explain why a strategy works, not just produce a document. Artisanal Legal practices will likely charge premium fees, emphasize reputation and referrals, and remain relatively small by design.
2. Human-AI Document Review: The dott.legal Model
At the opposite end of the spectrum lies Human-AI Document Review, exemplified by platforms such as dott.legal. This model addresses a persistent reality: while AI is exceptionally good at sorting, clustering, and flagging documents, clients and courts still want human accountability. As part of this model, clients come to an attorney with an AI-generated document, and the attorney steps up to validate and certify results.
This model requires efficiency and subject matter familiarity. Dott.legal is priced at $199 for a document or demand letter — which doesn’t seem workable for anything longer than four or five pages. And if the document is a real clunker, the revisions would be more involved. AI can’t solve the problem because the model promises attorney review. Still at a higher price point at scale and with caveats as to the size of the document, this model may have legs.
3. AI-Enabled Contract Lawyer Services (Shared Access)
A third category of AI-enabled legal services adapts the traditional contract-lawyer model to the economics of modern legal technology. As the cost of advanced AI research and discovery tools continues to rise — often $1,000 per month or more — many solos and small firms cannot justify maintaining subscriptions for occasional use. What they can justify is paying for the output of those tools when a matter requires it.
Under this model, an attorney makes the upfront investment in premium AI-enhanced platforms — such as comprehensive Westlaw products, AI research tools, or enterprise discovery systems — and offers the benefit of those tools to other lawyers on a contract basis. The service is sold not as software access, but as lawyer-supervised work product, preserving ethical compliance and professional accountability.
For example, a lawyer with a full Westlaw AI suite could provide per-diem or project-based services such as 50-state surveys, multijurisdictional research memoranda, issue-spotting analyses, or first-draft briefs, complete with supporting authorities and research trails. The hiring firm receives high-quality, defensible work product without incurring ongoing technology costs, while the providing lawyer monetizes both expertise and infrastructure.
The same model applies to discovery and litigation support. A lawyer with access to an advanced discovery platform can manage document review, privilege analysis, and issue tagging for other firms, using AI to accelerate review while maintaining human oversight. Rather than each firm purchasing and mastering complex discovery software, discrete litigation functions are outsourced to a specialist who already has the tools and systems in place.
This shared-access approach transforms expensive AI platforms into revenue-generating assets and creates a new class of supercharged contract legal services — faster, more scalable, and accessible to firms that do not need full-time ownership of advanced legal technology.
4. Next-Generation Law Practices Capturing Older Lawyer Knowledge
One of the most underappreciated opportunities in the AI age is the capture and reuse of institutional legal knowledge, particularly from senior and retiring lawyers. Decades of expertise — how to handle regulators, negotiate industry-specific contracts, or manage recurring disputes — often walks out the door when a lawyer retires.
In this model, law practices would acquire not a law practice but senior lawyers’ knowledge which could be encoded into AI systems: curated document libraries, annotated precedents, decision trees, and training datasets. These systems are then used to train junior lawyers, support client-facing work, or even generate new revenue streams.
The practice becomes not just a provider of legal services, but a knowledge steward. This model is especially powerful in niche regulatory, industry-specific, or regional practices where tacit knowledge matters more than published law.
It also offers a compelling succession strategy. Rather than selling a book of business, older lawyers can help build durable systems that preserve their expertise while reducing dependence on their personal availability.
5. AI-Forward Law Firm Offshoots
Another emerging model is the creation of AI-forward offshoots within or alongside traditional law firms. These are not full-service firms, but specialized entities focused on AI-enabled services: compliance audits, internal investigations support, contract analytics, discovery management, or regulatory monitoring.
The offshoot structure matters. By separating these services from the core firm, lawyers gain flexibility in pricing, staffing, and technology adoption without disrupting legacy billing models. These entities may employ technologists, project managers, and non-lawyer specialists alongside lawyers.
Clients benefit from clarity: they know they are buying a process-driven, technology-enabled service rather than bespoke legal advice. Firms benefit from diversification and innovation without existential risk to the main practice.
Over time, some offshoots may grow into standalone businesses — or even outpace their parent firms in revenue.
The AI age does not point toward a single future for law practice or for the wholesale extinction of lawyers. Instead, it opens multiple viable paths — each with different tradeoffs in scale, income, identity, and impact. Lawyers who focus solely on AI tools without thinking about the underlying business model risk missing the larger opportunity: rethinking how legal value is created and delivered.
Carolyn Elefant is one of the country’s most recognized advocates for solo and small firm lawyers. She founded MyShingle.com in 2002, the longest-running blog for solo practitioners, where she has published thousands of articles, resources, and guides on starting, running, and growing independent law practices. She is the author of Solo by Choice, widely regarded as the definitive handbook for launching and sustaining a law practice, and has spoken at countless bar events and legal conferences on technology, innovation, and regulatory reform that impacts solos and smalls. Elefant also develops practical tools like the AI Teach-In to help small firms adopt AI and she consistently champions reforms to level the playing field for independent lawyers. Alongside this work, she runs the Law Offices of Carolyn Elefant, a national energy and regulatory practice that handles selective complex, high-stakes matters.
The post Five New AI-Powered Business Models For Solos And Smalls In 2026 appeared first on Above the Law.
As the year winds down, the legal profession is flooded with retrospectives: the growing AI adoption rate by solos and smalls (now around 70%), ways that AI is leveling the playing field between large and small firms (including on the hallucination front where large firms and solos are equal offenders) and the familiar observation noting the shift from chat-based tools to agentic systems. Much of this commentary is accurate — but it’s also repetitive and boring. Rather than regurgitate what most lawyers already know or could readily learn from AI, I’ll take a different approach and examine five distinct business models that offer new opportunities for solo and small-firm lawyers in the AI age.
Let’s take a step back. According to Wikipedia, a business model describes how a business organization creates, delivers, and captures value. For decades, law firm business models have been downright boring, largely based on selling time in billable increments. That’s changed to some degree in recent years with flat fees and law subscription models like Mathew Kerbis’s The Subscription Attorney, but these approaches — along with six new law business models that I imagined years ago — never gained any real traction.
In AI era, all of that may change. And in fact, some would argue that it has to change since with AI cutting down on the time required for legal tasks, billable revenue is bound to decline. But AI can also power new business models, or revive traditional ones. Below are five law firm business models for the AI age that can help solo and small law firms diversify their offerings.
1. Artisanal Legal: “Good Old-Fashioned Law,” Reimagined
The first model may seem counterintuitive in an AI-driven era: Artisanal Legal. This is the deliberate embrace of high-touch, bespoke legal services grounded in judgment, strategy, and human insight — augmented, but not replaced, by AI.
In this model, AI operates largely behind the scenes. It supports research, drafting, and issue spotting, allowing the lawyer to focus on what clients value most: interpretation, advocacy, and trust. The lawyer’s brand is built not on speed or scale, but on craftsmanship. Think of appellate advocacy, regulatory counseling, complex negotiations, and niche advisory practices where outcomes hinge on experience rather than volume.
As AI commoditizes routine legal outputs, the perceived value of deep expertise and individualized counsel will increase, not decrease. Clients facing high-stakes matters will seek lawyers who can explain why a strategy works, not just produce a document. Artisanal Legal practices will likely charge premium fees, emphasize reputation and referrals, and remain relatively small by design.
2. Human-AI Document Review: The dott.legal Model
At the opposite end of the spectrum lies Human-AI Document Review, exemplified by platforms such as dott.legal. This model addresses a persistent reality: while AI is exceptionally good at sorting, clustering, and flagging documents, clients and courts still want human accountability. As part of this model, clients come to an attorney with an AI-generated document, and the attorney steps up to validate and certify results.
This model requires efficiency and subject matter familiarity. Dott.legal is priced at $199 for a document or demand letter — which doesn’t seem workable for anything longer than four or five pages. And if the document is a real clunker, the revisions would be more involved. AI can’t solve the problem because the model promises attorney review. Still at a higher price point at scale and with caveats as to the size of the document, this model may have legs.
3. AI-Enabled Contract Lawyer Services (Shared Access)
A third category of AI-enabled legal services adapts the traditional contract-lawyer model to the economics of modern legal technology. As the cost of advanced AI research and discovery tools continues to rise — often $1,000 per month or more — many solos and small firms cannot justify maintaining subscriptions for occasional use. What they can justify is paying for the output of those tools when a matter requires it.
Under this model, an attorney makes the upfront investment in premium AI-enhanced platforms — such as comprehensive Westlaw products, AI research tools, or enterprise discovery systems — and offers the benefit of those tools to other lawyers on a contract basis. The service is sold not as software access, but as lawyer-supervised work product, preserving ethical compliance and professional accountability.
For example, a lawyer with a full Westlaw AI suite could provide per-diem or project-based services such as 50-state surveys, multijurisdictional research memoranda, issue-spotting analyses, or first-draft briefs, complete with supporting authorities and research trails. The hiring firm receives high-quality, defensible work product without incurring ongoing technology costs, while the providing lawyer monetizes both expertise and infrastructure.
The same model applies to discovery and litigation support. A lawyer with access to an advanced discovery platform can manage document review, privilege analysis, and issue tagging for other firms, using AI to accelerate review while maintaining human oversight. Rather than each firm purchasing and mastering complex discovery software, discrete litigation functions are outsourced to a specialist who already has the tools and systems in place.
This shared-access approach transforms expensive AI platforms into revenue-generating assets and creates a new class of supercharged contract legal services — faster, more scalable, and accessible to firms that do not need full-time ownership of advanced legal technology.
4. Next-Generation Law Practices Capturing Older Lawyer Knowledge
One of the most underappreciated opportunities in the AI age is the capture and reuse of institutional legal knowledge, particularly from senior and retiring lawyers. Decades of expertise — how to handle regulators, negotiate industry-specific contracts, or manage recurring disputes — often walks out the door when a lawyer retires.
In this model, law practices would acquire not a law practice but senior lawyers’ knowledge which could be encoded into AI systems: curated document libraries, annotated precedents, decision trees, and training datasets. These systems are then used to train junior lawyers, support client-facing work, or even generate new revenue streams.
The practice becomes not just a provider of legal services, but a knowledge steward. This model is especially powerful in niche regulatory, industry-specific, or regional practices where tacit knowledge matters more than published law.
It also offers a compelling succession strategy. Rather than selling a book of business, older lawyers can help build durable systems that preserve their expertise while reducing dependence on their personal availability.
5. AI-Forward Law Firm Offshoots
Another emerging model is the creation of AI-forward offshoots within or alongside traditional law firms. These are not full-service firms, but specialized entities focused on AI-enabled services: compliance audits, internal investigations support, contract analytics, discovery management, or regulatory monitoring.
The offshoot structure matters. By separating these services from the core firm, lawyers gain flexibility in pricing, staffing, and technology adoption without disrupting legacy billing models. These entities may employ technologists, project managers, and non-lawyer specialists alongside lawyers.
Clients benefit from clarity: they know they are buying a process-driven, technology-enabled service rather than bespoke legal advice. Firms benefit from diversification and innovation without existential risk to the main practice.
Over time, some offshoots may grow into standalone businesses — or even outpace their parent firms in revenue.
Conclusion
The AI age does not point toward a single future for law practice or for the wholesale extinction of lawyers. Instead, it opens multiple viable paths — each with different tradeoffs in scale, income, identity, and impact. Lawyers who focus solely on AI tools without thinking about the underlying business model risk missing the larger opportunity: rethinking how legal value is created and delivered.
Carolyn Elefant is one of the country’s most recognized advocates for solo and small firm lawyers. She founded MyShingle.com in 2002, the longest-running blog for solo practitioners, where she has published thousands of articles, resources, and guides on starting, running, and growing independent law practices. She is the author of Solo by Choice, widely regarded as the definitive handbook for launching and sustaining a law practice, and has spoken at countless bar events and legal conferences on technology, innovation, and regulatory reform that impacts solos and smalls. Elefant also develops practical tools like the AI Teach-In to help small firms adopt AI and she consistently champions reforms to level the playing field for independent lawyers. Alongside this work, she runs the Law Offices of Carolyn Elefant, a national energy and regulatory practice that handles selective complex, high-stakes matters.
