Before the Algorithm: Building the Business Foundation Your AI Investment Actually Needs
The Technology Issue
 

Before the Algorithm: Building the Business Foundation Your AI Investment Actually Needs

Many firms are adopting AI tools without completing the three essential steps that make the integration successful.
By Gary G. Allen, Esq.
September 2026
 

You have undoubtedly heard many pitches for AI in your law firm. Let’s take one set of key workflows in your firm — revenue operations (e.g timekeeping, billing, trust accounting, and reporting) — to look at how to make AI adoption successful.

AI platforms promise to transform your billing workflows, flag collection risks before they become problems and surface realization gaps your current reports miss entirely. The demos are impressive. The partners are excited. Yet 12 months later, the system is barely used, the data it produces is unreliable and you are answering questions from the managing partner about what happened to the investment.

Here is what happened: The technology was fine. The foundation was not.

AI Reflects What Is Already There

Artificial intelligence depends on sound processes. If your time entry is sketchy, your billing codes are inconsistent, your matter budgets are poorly documented and trust accounting is manual, an AI platform will likely surface those problems faster and more easily than any report you have run before. But it will not fix them.

Before your firm spends another dollar on AI for revenue operations, it is worth asking a straightforward question: Are our underlying processes clean enough for AI to work with? In many firms, the honest answer may be, “Not yet.”

The Three Things That Have to Come First

Over the past several years, watching firms implement AI tools with wildly different results, I have noticed that the ones that succeed have three things in place before the platform goes live. The ones that struggle are missing at least one of them.

The first is process rationalization. This means your revenue workflows — how time gets entered, how bills get generated and reviewed, how collection follow-up is handled — are documented, consistent and actually followed. Not perfect. Consistent. AI depends on pattern recognition, and it cannot find patterns in chaos. Standardizing billing codes, tightening matter budget discipline and establishing clear timekeeping expectations are not exciting projects. But they are the ones that determine whether your AI investment pays off.

Clio
Clio
The second is the right enabling tools. AI does not sit on top of your practice management system and magically sort things out. It integrates with it, pulls from it and is only as good as the data your underlying systems contain. Firms with fragmented technology — billing in one place, collections tracking in another, matter budgets and trust accounts managed in spreadsheets — have a data integrity problem that no AI platform can solve for them. Getting your technology stack rationalized is part of the foundation, not a future phase.

The third is personnel alignment. This is the one that gets underestimated most often. Partners who do not understand the payoff for adopting consistent timekeeping standards will not comply with them. Billing staff who are not trained on new workflows will return to old ways. If firm leadership has not made clear that AI adoption is a priority with real expectations attached, it will not happen. Change management can’t be an afterthought; it needs to be rigorous and disciplined.

Your Role in This

If you are a firm administrator reading this, you already know that ensuring the success of AI adoption is ultimately your job. You are the person who understands how revenue actually moves through the firm, where the process gaps are and which partners are going to need a different kind of conversation than others. That makes you the most important person in any AI readiness effort — not the vendor, not the IT director, not the managing partner who approved the budget.

Getting your technology stack rationalized is part of the foundation, not a future phase.
The good news is you are already equipped to do this work. Process documentation, technology assessment, stakeholder alignment — these are core competencies for any seasoned midsize firm operator. AI readiness is not a new discipline. It is an operational discipline applied to a new context.

The firms that are getting real value from AI right now are not necessarily the ones that bought the most sophisticated platform. They are the ones that did the unglamorous work first. That work is available to every firm. And it begins well before you start using the algorithm.

About the Author

Gary G. Allen, Esq.

Gary G. Allen, Esq.

Founder and Vice President
LeanLaw

Gary G. Allen, Esq., is a Founder and Vice President at LeanLaw, a legal timekeeping, invoicing and reporting software company, as well as a recently retired partner at Givens Pursley LLP. He was only two years out of Stanford Law School when the firm he was working for imploded. It happened again a few years later. He was left without a job with a six-month old baby to feed. Allen was fortunate to land at a firm that understood the business of law, where he practiced happily for 30+ years. These experiences created a passion in Allen to help law firms be better businesses, with efficient operations, streamlined financial management and a laser focus on profitability.

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