The Best AI Portfolio is a Smaller One

This past week at ILTACON, 241 legal technology vendors filled the exhibit hall with custom-built booths and activities to attract law firms. From a Goo Goo Clusters customization station to an actual rage room, there was no shortage of noise on the floor.

But while vendors competed to add to firms’ technology stacks, many attendees actually came to evaluate how to reduce, consolidate, and better govern the tools they already have—a tension that surfaced across several seemingly unrelated sessions.

At Technology Strategy Beyond Roadmaps, Karyl Davis from Troutman Pepper and Locke Lord discussed the technology strategy behind a large law firm merger. Her company’s merger objectives were ambitious. It outlined goals to operate as one firm from the first day, become fully integrated within nine months, and avoid disrupting client service in the process. 

The guiding principle was to minimize the amount of change experienced by the greatest number of people.

Later, Managing AI Tool Overload focused on similar operational topics, including how to think through the impact of AI tools on your firm’s infrastructure. As of June, the Legal Technology Hub listed 1,196 generative AI solutions. Large firms are on average evaluating over 100 new tools while the solutions they already own remain unadopted. 

Every AI product a firm adopts today becomes something it may have to integrate, govern, train, support, renew, and eventually replace tomorrow.

That means a tool can succeed in a pilot and still be the wrong decision for the firm. Across the sessions, that decision came down to three questions about cost, strategic priority, and the capabilities firms already own.

How much does your AI cost?

Once a tool is adopted, the firm has to manage access, security reviews, client restrictions, integrations, training, support, usage data, renewals, and product changes. Attorneys build processes around it. Practice groups develop their own workflows. Data starts moving through another system.

A narrow use case may justify the price of the software without justifying the operating burden that comes with it.

That burden grows as AI becomes more capable. A system that retrieves information needs governance. One that drafts or analyzes work needs review. One that changes data or takes action needs clear approval, audit, and revocation controls.

The question, then, is not simply whether a tool works. It is whether the value it creates is worth adding another layer to the firm's operating environment.

What are the software that law firms prioritize today?

Mergers force firms to decide which systems will become standard.

During one ILTACON session, senior technology executives were asked which systems they would prioritize for transfer during a merger. Document management ranked first at 29%, followed by time entry and billing at 24%, and intake and conflicts at 18%. 

These are the systems at the firm's operating core. They hold the documents, client information, financial records, and workflows that keep the business running.

But firms do not need to undergo a merger to face the same decision. Many law firms already operate as a collection of distinct practices. Different groups serve different clients, follow different billing requirements, and prefer different tools. A specialized product may improve one group's work while making firm-wide standardization more difficult.

Over time, the firm accumulates products with overlapping capabilities, separate data, different governance requirements, and small groups of users who depend on them. Technology leaders then end up spending more time maintaining the portfolio than improving the firm's underlying workflows.

Does your existing stack cover 80% of your firm’s workflow?

A useful starting point is to audit the firm's existing workflows and ask whether its current technology already handles roughly 80% of what people need.

If it does, the first question should be whether the firm can improve adoption of what it already owns. If it cannot, then test whether the missing 20% is important enough to warrant another system.

The 80% rule is often treated as a way to control spending. However, its underlying value is actually in control complexity.

A new point solution will often perform a narrow task better than a broad enterprise platform. That is why it exists. But the improvement has to justify more than another software bill. 

I am not arguing that firms should avoid point solutions or wait for one platform to do everything. Specialized products can create significant value when they solve a meaningful problem. But the new tool should have to prove that the problem is important enough, and the improvement large enough, to justify making it permanent.

At PointOne, this view is shaping our evolution from AI timekeeping into an AI Revenue Platform. Time capture, billing compliance, bill review, and revenue intelligence are not separate problems. They are connected parts of the same process. Treating them as a shared workflow reduces the number of handoffs, preserves the underlying data, and gives firms a clearer view of how work becomes revenue.

The best AI portfolio may become smaller

Legal innovation has often been measured by how quickly firms can test new products. But with over 1,000 generative AI solutions competing for attention, testing is no longer the scarce capability.

Law firms are re-assessing their AI strategy to decide which workflows are important enough to support at the enterprise level and how to double down on user adoption rates. 

This has become a firm-wide effort. AI now affects every level of the firm, from individual practice groups to firm management. Innovation and data are no longer isolated functions or standalone projects. 

At ILTACON’s closing session, Jim McKenna, CIO at Foley & Lardner, compared an effective AI strategy to the Olympic rings: multiple parts that overlap and work together. The same applies to implementation. CIOs, Chief Data and AI Officers, CTOs, practice leaders, and firm management all have a role in deciding how AI is adopted across the firm.

Take it from Tim Fox, the Chief Data and AI Officer at Ogletree Deakins: technology capabilities may represent one-third of the AI adoption strategy at a law firm, but the people and processes around it determine the remaining two-thirds.

The goal is not to build the largest possible AI portfolio. It is to make the firm more capable without making it harder to operate.

Book a demo to see how PointOne is connecting the workflows and data behind law firm revenue.

Explore more analysis on the future of legal AI in Attorney Intelligence.

Katon Luaces