The question I heard most in the later part of my time at Thomson Reuters was not which tool to buy. It was earlier than that. Managing partners, operations directors, and solo practitioners would get on a call, explain that they had been watching the legal AI space for a while, and then ask: do we actually need this? Are we falling behind? Or are we overthinking it?
Those are good questions, and they deserve a straight answer rather than a vendor pitch. The honest answer is: it depends on your firm, your practice area, and where you are in your workflow maturity. Some firms should be moving now. Others are right to wait. And the calculus is not as complicated as the marketing would suggest.
A note on my perspective
I sold CoCounsel, Westlaw, and Practical Law to attorneys and law firms through my time at Thomson Reuters. My perspective on legal AI comes from the sales side: understanding how firms evaluate these tools, what their due diligence looks like, and where procurement conversations tend to stall. For tools I have not sold directly, I rely on what firms report publicly, vendor documentation, and the patterns I have observed in how firms describe their experiences. Where I am speaking from direct experience, I will say so.
Why some firms are adopting now and seeing results
The firms that have moved early on legal AI are not the ones chasing novelty. They are the ones that identified a specific workflow problem and found a tool that addressed it.
Legal research is the clearest example. Attorneys who use CoCounsel for research describe a consistent pattern: the time between a legal question and usable work product has compressed significantly. A research task that took a junior associate several hours now produces a structured first pass in a fraction of that time. The associate still reviews it. The partner still signs off. But the work that used to fill an afternoon is done before lunch. From my own sales calls, the attorneys who became the strongest internal advocates for CoCounsel were the ones who started using it for a single research question and found themselves depending on it within a week.
Contract work follows a similar pattern. Firms report that tools in this category allow attorneys to identify problematic clauses and deviations from market standards in a fraction of the time a manual review would take. For a corporate practice handling high volumes of NDAs, commercial agreements, or employment contracts, that speed compounds quickly across a matter load.
Due diligence is where specialist tools have produced the most consistent adoption results. Firms doing M&A work report that purpose-built platforms allow them to run more thorough reviews without expanding headcount, and to catch issues in large contract portfolios that manual review would miss under time pressure.
The common thread across all of these cases is specificity. The firms seeing results are using AI for a defined task in a defined workflow. If you have a practice area that produces high-volume, repetitive legal work, that is where adoption is most likely to pay off quickly. If you want a breakdown of how this plays out across specific use cases, How Law Firms Are Actually Using AI in 2026 covers each one in detail.
Why some firms are right to wait
Not every firm is in a position where legal AI will produce a meaningful return right now. Buying a tool before you are ready for it is a reliable way to waste money and create frustration among your attorneys.
Practice area matters. Legal AI has advanced furthest in legal research, contract review, and document-heavy due diligence. Firms that are primarily litigation-focused, working in niche practice areas, or whose workflows involve a high degree of client-specific judgment at every step will find fewer immediate applications. The tools are improving in litigation support, but the use cases are less mature and the feedback loop is harder to validate.
Workflow readiness matters. AI tools do not drop into disorganized workflows and make them better. Firms where attorneys are still working primarily from email, where matter management is inconsistent, or where there is no clear owner for a technology decision will struggle to get traction from an AI deployment even if the tool itself is excellent. The firms that see the fastest adoption are the ones where at least one attorney is genuinely interested in the tool, prepared to use it consistently, and willing to advocate for it internally.
Budget relative to billable volume matters. For a sole practitioner or a very small firm, the monthly cost of an enterprise legal AI subscription is meaningful, and the volume of work that needs to flow through the tool to justify it may simply not be there yet. A two-person firm billing four hundred hours a month does not have the same calculus as a fifty-attorney firm. Waiting until the work volume supports the cost is not a failure of vision. It is sound management.
If any of those conditions describe your firm right now, the responsible answer is to watch the market, track the tools advancing in your practice area, and revisit the decision in six months. This market is moving fast enough that waiting does not mean falling permanently behind. It means making a decision when you are actually ready to execute on it.
The real cost of not adopting, without the fear-mongering
There is a version of this conversation that leans heavily on phrases like existential threat and firms that don't adopt AI will cease to exist. That framing oversells the urgency and undersells the nuance. But the risk of inaction is real, and it is worth understanding clearly rather than dismissing it because the loudest version of the argument is overblown.
The pressure is coming from client expectations. Clients who know that their outside counsel's competitors are doing legal research and contract review faster are going to start asking questions about staffing, billing models, and rates. Not immediately, and not in every practice area, but the direction is not reversing. Firms that have meaningful AI-assisted workflows in place will be able to respond to those questions with specifics. Firms that do not will eventually be explaining why they have not.
The pressure is also coming from the talent market. Law students and junior associates entering the profession right now have a baseline familiarity with AI tools that attorneys who graduated a decade ago did not. Firms that offer access to and training on legal AI are increasingly treating that as a recruitment and retention factor. The associates who want to develop this skill set are going to look for firms where they can.
The billing model is a slower-moving but more structurally significant source of pressure. If a task that used to bill eight hours now takes two hours with AI assistance, the firm has to make a decision: bill for two hours and absorb the margin impact, find a way to capture the value of speed through fixed or value-based fees, or hold the hourly rate and hope clients do not notice. Firms that have not thought through that transition are going to be caught off guard when clients start asking about it.
None of this is catastrophic on a twelve-month timeline. But it accumulates. The firms that are thinking through these questions now, even if they are not deploying tools yet, will be better positioned when the adoption decision becomes harder to delay.
What to look for when you're ready
When your firm does reach the point of evaluating tools, the questions that will save you the most time in procurement are not the ones vendors lead with in their demos.
Data privacy and confidentiality should be the first line of inquiry. The relevant questions are specific: does this vendor use client documents to train or improve the model? Which underlying AI providers process the data and under what agreements? Where is the data stored, and what happens to it when you off-board? Vendors have detailed answers to these questions. Getting those answers upfront will prevent you from discovering a conflict with your professional responsibility obligations after you have already moved client matters into the platform.
Integration with your existing research infrastructure matters more than it sounds in a demo. If your firm runs on Westlaw, CoCounsel's integration with the Westlaw database is a genuine advantage: the AI is working with the same case law you have already verified and paid for, and the workflow does not require moving between platforms. If your firm is on LexisNexis, the equivalent consideration applies to Lexis+ AI. Switching research databases to accommodate an AI tool is almost never worth the disruption. Start with what you already have access to.
Trial access before contract commitment is standard in this market and you should expect it. Any vendor pushing you toward an annual commitment before you have spent meaningful time in the product on real work is a signal to slow down. The tools that hold up in practice will tolerate being evaluated on actual matters before you sign.
The Best Legal AI Tools overview covers the six leading platforms in detail, including pricing, use case fit, and who each one is actually built for. If you are early in the evaluation process, that is a useful starting point before engaging vendors directly.
How to start small without committing to an enterprise platform
The most common mistake I saw firms make during AI evaluations was trying to solve too many problems at once. A firm would see a demo covering research, drafting, contract review, and client intake automation, decide they wanted all of it, and spend six months in procurement while their attorneys kept doing everything the old way. By the time the contract was signed, the internal momentum had dissipated and no one knew who was supposed to drive adoption.
A better path is to pick one workflow and one practice group and run a real test. If your firm is already paying for Westlaw, ask your Thomson Reuters representative about CoCounsel access. The integration is built in, the learning curve is short, and the feedback loop from your research attorneys will be immediate and verifiable. If your firm is on LexisNexis, the equivalent conversation starts with Lexis+ AI. Neither requires a separate procurement process from scratch.
If contract drafting is the workflow with the most volume and the most friction, Spellbook is known for offering a low-friction starting point. It operates as a Word add-in, which means attorneys do not have to change where they work, only what they have available to them while drafting. Firms report that adoption in this format tends to happen faster because it does not require attorneys to build new habits around an unfamiliar interface.
For firms not yet ready for a full platform subscription, the Lexis+ AI vs CoCounsel comparison and the Harvey vs Spellbook comparison are good ways to narrow the field before your first vendor call. Reading those will surface the right questions to ask before you commit any time to a demo.
The goal of a first engagement with legal AI is not to transform your firm. It is to find out whether a specific tool makes a specific workflow meaningfully better. If it does, you have a clear foundation to expand from. If it does not, you have learned something important before spending significant money and internal capital on a broader rollout.
The bottom line
Legal AI is not a trend that is going away, and the firms that will be best positioned in three years are the ones that started learning now, even if they are not buying yet. That learning does not require a six-figure enterprise contract. It requires someone at the firm to run a real test on a real workflow and pay attention to what happens.
If you are not sure which tool fits your firm's specific practice area, firm size, and existing infrastructure, the Legal AI assessment below is designed exactly for that.
