What to Decide Before Your Firm Touches an AI Tool

Your firm is already running on AI. Most managing partners have no idea how much.

That is the argument Kathy Serenko, Amy Adams, and I made during our June 3rd webinar on “Three AI Conversations Every Law Firm Needs to Have”, hosted by the Law Firm Profitability Group on LinkedIn. Not which tools to use, but what your firm needs to have decided before it touches any of them. The recording is here.

Kathy Serenko is the founder of AI Efficiency Labs, and Amy Adams is the founder of Gaia Allies and AIReady™.

Kathy led with the governance perspective. Her opening question: Are you already exposed? Her answer, based on what she sees in firms daily: almost certainly yes.

AI enters your firm in ways leadership cannot see. A paralegal uploads 300 pages of medical records to a personal ChatGPT account under a deadline. The summary looks clean. Three months later, the error surfaces in a settlement discussion. A vendor tool your firm approved last year has AI inside it you never examined. The tools you signed off on produce errors that reach binding deliverables before anyone reviews them. AI is designed to produce plausible output, and it will not tell you when it is filling in blanks.

Kathy’s second point: having an AI policy is not the same as having governance. Less than 40% of law firms have a policy at all, and a policy is only a statement of intent. The missing layer is the day-to-day controls built into your actual workflow. Without those controls, the policy and the reality of what is happening in your firm will not align.

Governance means a domain expert, not IT, is the authority over AI output in each practice area. Someone who reads a research memo and recognizes when the content is wrong. The errors appearing in court sanctions are content errors, and the people catching them are judges and opposing counsel. They are domain experts. Your oversight authority in each practice area needs to be one too.

Amy made the workflow case. Her rule before recommending any AI system: map the workflow first. She recently spent 90 minutes with a family law partner doing exactly that. In your firm, that work probably has not been done. If the process exists only in someone’s head, the AI system inherits every gap in it. The tool scales what is already there.

Before the workflow is designed, the economics need to be settled. If a matter that used to take 10 hours now takes five, and your firm is still billing hourly, you may be cutting your revenue in half for that work. Pricing needs to be decided before the workflow is built. Firms that build the workflow first and sort out the pricing later often discover they cannot make money at it.

Everyone in your firm is asking the same question in different ways: what happens to me? The concern is real at every level, and dismissing it does not make it go away. What is actually changing is what each role does. Paralegals are running AI systems that used to require associate hours. Associates who used to produce first drafts are now verifying AI output and building judgment through that review. Partners who used to do the work are moving toward designing the systems that do it. The firms handling this well are having that conversation before the tools arrive.

Leadership does not get to delegate this responsibility. You cannot hand AI governance to a technology committee and check back in six months. You have to understand where the exposure is and whether your compensation structure supports what you are asking of your partners.

Your partners who put their expertise into an AI system will watch their billable hours fall as the system takes on that work. That contribution needs to be reflected in how they are compensated. If your firm still pays only for billable hours, you will not get the cooperation needed to build something that works.

The firms moving ahead well on this have answered the harder questions before reaching for tools.

Three AI Conversations Every Law Firm Needs to Have

I am not going to tell you AI will transform your law firm.

Transformation will not begin until you address three priorities most firms have yet to discuss. And order matters.

Business model first. Workflow second. Guardrails throughout.

On June 3, I’m moderating a webinar with two people who think about this for a living.

I’m a law firm management consultant with more than 35 years of experience in the legal industry. The emergence of AI is already transforming how law firms operate and compete, and this disruption will only accelerate.

The goal of the webinar is to highlight the key strategic and operational issues you need to address in order to implement AI successfully in your firm.

We will discuss:

Business Model: I’ll dig into pricing, leverage, partner compensation, and the decisions firms need to make. Unless they want AI to make them by default.

Workflow: Amy Adams, Gaia Allies + AIReady™, will unpack where AI fits into the actual work, and why adoption stalls after the champion stage.

AI Guardrails: Kathy Serenko, AI Efficiency Labs, will lay out what’s allowed, who’s accountable, and how risk is contained.

Sixty minutes, three perspectives.

Wednesday, June 3 | 11 AM PDT | 2 PM EDT – Webinar hosted by the Law Firm Profitability Group on LinkedIn. Register: https://us06web.zoom.us/meeting/register/N9SV1dEcRC6X5GXwdRxO0g

MikeOSS and the New Bargaining Power in Legal AI

Will Chen, a developer, saw enterprise legal AI demos and realized their premium pricing wasn’t justified by basic features like chat interfaces or prompt templates. By building and releasing MikeOSS, he showed that much of what is marketed as sophisticated legal AI can be reproduced by skilled individuals.

When Will appeared on a fireside chat with Jamie Tso and Raymond Sun of Legal Quants shortly after, the conversation moved quickly to what MikeOSS actually revealed. Three bargaining power shifts are happening at once. Each follows from the same underlying move: someone who was assumed not to understand what they were buying figured it out. That happened first between firms and vendors. It is now happening between innovative lawyers and the firms that employ them, as well as between clients and outside counsel. The client shift is the one most firms are not watching closely enough. When an in-house team runs the same calculation Will ran, watching a demo and asking what it would cost to build, the case for sending routine work outside gets harder to make.

What You Are Actually Paying For

Vendors charge what they charge because buyers have not been able to evaluate what they are buying. MikeOSS changes that. The chat interfaces, the playbooks, the document review tables: those are replicable, as Will demonstrated. What companies like Harvey and Legora legitimately earn their fees for is the enterprise wrapper: security, deployment, configuration, and support. That is a service business, not a moat. Before your next renewal, the question worth asking is which of those two things you are actually paying for, and whether the price reflects it.

The next round of legal AI value will not come from general platforms. Will was clear about this in the fireside chat: generalist tools will be copied, and the firms that build on top of them for a specific workflow or jurisdiction will be the ones creating defensible value. That applies to vendors building on MikeOSS, and it applies to the lawyers inside your firm who understand a workflow well enough to improve it. General capability is becoming a baseline. Depth is where the advantage will be.

The Harder Problem Is Inside the Firm

The harder challenge is inside the firm, and this is where you need to be honest with your partners. Most compensation systems reward production. They do not reward the creation of tools that make other lawyers more productive. If you want that to change, build incentives around what you actually want to reward. A lawyer who makes twenty other lawyers more productive has created real value for the firm. Integrate that recognition into formal evaluations alongside billable production.

Consider this: If a junior lawyer created a tool that saved forty hours on a fixed-fee matter, how would your firm reward them? Typically, origination credit goes elsewhere, and fewer billable hours may even penalize the innovator. Law firms lack an equity-sharing system like those used by software companies.

Will described how most firms reward output rather than the creation of tools that boost others’ productivity. Jamie pressed him on this misalignment. The implication of that conversation is direct: if your firm wants real innovation, the compensation system has to recognize it.

What Happens to Your Billing Model

Jamie raised pricing directly: If AI increases lawyer productivity, what happens to billing? Fewer hours mean the rate-times-hours formula works against you. Move to value-based or fixed pricing before clients require it. Most firms haven’t. They add AI subscriptions but keep billing unchanged. Clients will soon get better tools, making this model hard to justify.

Raymond Sun pressed Will on this directly. Will’s answer was that client relationships still matter, but clients will increasingly want measurable results from AI. Right now, saying the firm uses Harvey is no longer a differentiator. Clients will want to see concrete outcomes. A firm that cannot show what its AI investment produces is competing on a claim that the whole market is already making.

Raymond Sun’s questions pushed toward the strategic position of law firms and in-house teams. If AI-native firms charge premium prices, where does the money come from? If client legal budgets remain constrained, will in-house teams use open-source tools to do more themselves?

Will agreed that this is a real possibility. In-house teams may not replace outside counsel for complex transactions or high-risk litigation. But they may use open-source tools and enterprise AI subscriptions to handle more repeatable work internally.

The Real Lesson

This is why MikeOSS matters. It is not only a product. It is a signal that the cost of building is falling and that law firms should no longer treat legal AI as a black box.

Commercial legal AI platforms will still matter. Many firms will prefer supported, secure, enterprise-ready tools. But the existence of open-source alternatives should make the market more honest. Vendors will need to show where their value really sits. Firms will need to understand which workflows are worth buying, which are worth building, and which should be redesigned altogether.

The firms that benefit most from AI will not necessarily be the firms that buy the most impressive platform. They will be the firms that understand their own work deeply enough to know where AI can create economic value.

That is the real lesson of MikeOSS.

Legal AI strategy cannot simply be a software purchase. It touches pricing, compensation, governance, client service, training, and profitability. The firms that understand that will have more bargaining power than the firms that simply buy what they are sold.