AI strategy isn’t about tools. It’s about culture shift.

Law firms are investing in AI, but implementation rarely matches ambition. From research platforms and automated summarization tools to client intake chatbots and voice-driven documentation assistants, the legal tech market is crowded with solutions. The problem? Many sit idle, misconfigured, or mismatched to firm workflows. Instead of streamlining operations, they often create friction, widening the gap between capability and utility.

This isn’t an AI problem. It’s a culture problem.

Everyone’s buying, few are solving

For managing partners and marketing leads, AI adoption feels increasingly urgent. That urgency often gets mistaken for progress. But installing a tool isn’t the same as solving a problem, especially when your workflows, roles, and trust structures weren’t designed for automation.

A 2024 ILTA survey found that while 37% of firms reported implementing AI tools, 54% cited “resistance to change among users” as their biggest barrier to success. The disconnect? Implementation without integration.

When tools are dropped into legacy systems without operational context, resistance is rational. People push back not because they dislike innovation, but because the technology doesn’t match the way they actually work. Intake teams don’t know how or when to use it. Marketing can’t access the right data to evaluate ROI. Partners don’t see results.

Integrated solutions, on the other hand, reduce friction. They clarify ownership. They streamline adoption by embedding AI into familiar workflows rather than layering it awkwardly on top. And when teams see how these tools simplify—not complicate—their day-to-day work, resistance becomes curiosity. Curiosity becomes usage. Usage becomes value.

But that transformation doesn’t start with capabilities. It starts with culture.

Rethinking roles and workflows

Real AI adoption starts by asking: who owns this change? Who’s accountable for using AI ethically, effectively, and consistently? More importantly, who’s empowered to say when it’s not working?

If you want AI to stick, you need more than buy-in. You need alignment across levels:

• Leadership must set the vision and identify meaningful use cases. This includes defining success metrics beyond just cost savings—client experience, cycle time, and team engagement should all be part of the conversation.
• Operations must evaluate how AI fits (or breaks) existing systems. A firm that’s never conducted a workflow audit can’t expect seamless automation.
• Frontline staff must trust the tools enough to use them. That trust doesn’t happen through memos or demos. It happens through transparency, hands-on training, and iterative feedback loops.

AI’s value lives in process transformation, not task substitution. A chatbot can answer FAQs, sure. But if intake paralegals aren’t trained to step in when that handoff fails, you’ve just built a bottleneck.

A maturity model for AI strategy

We’ve seen three stages of AI adoption in law firms. These aren’t just tech levels, they’re cultural milestones:

Stage 1: Reactive AI

• Tools are chosen ad hoc, often by vendor hype rather than strategic need.
• No cross-functional alignment on implementation.
• Little to no documentation, oversight, or iteration.

Symptoms: High staff frustration, shadow IT, and poor client handoffs.

Stage 2: Integrated AI

• Tools are selected based on real use cases and integrated into core workflows.
• Staff are trained with clear SOPs and success metrics.
• Internal data begins to inform future decisions.

Symptoms: Measurable efficiency gains in specific areas (e.g., intake triage, document review).

Stage 3: Adaptive AI

• AI tools and processes evolve in sync with firm-wide objectives.
• Data flows freely between platforms (e.g., CRM → intake → marketing).
• Teams experiment, refine, and co-create new uses for AI.

Symptoms: Decreased time-to-retain, better client experience, and a culture of continuous improvement.

The culture gap: Why most firms stall at stage 2

Stage 2 is where most firms stall. Why? Because the cultural underpinnings of Stage 3 (trust, experimentation, aligned incentives) don’t emerge automatically. They have to be built. Moving from Integrated AI to Adaptive takes more than budget. It takes mindset. Without intentional change management, even the best tech becomes shelfware.

Building an adaptive culture requires:

• Psychological safety to report when tools break workflows.
• Feedback infrastructure, like weekly retros, intake logs, and usage audits.
• Transparent KPIs that track outcomes, not effort.

Law firms that have successfully moved into adaptive AI culture share common traits: they conduct regular retrospectives, cross-train departments on both tool use and process impacts, and prioritize workflow feedback over vanity metrics. When these elements are in place, they report not just better efficiency but more resilient operations and higher staff retention. These aren’t hypotheticals; they’re patterns we’ve seen across multiple engagements and industry reports.

The trust hierarchy: Why bottom-up buy-in matters

In legacy firms, strategy flows top-down. But AI demands a hybrid model. Your frontline staff will often spot broken processes before your exec team does. If they don’t have a voice in your AI roadmap, you’ll end up optimizing for the wrong things.

Examples:

• A receptionist knows which clients hang up on the chatbot.
• A case manager sees where automated summaries miss key context.
• A paralegal understands when predictive coding flags the wrong documents.

Ignoring those signals is the fastest way to sabotage your investment.

Building bottom-up trust means:

• Involving staff in tool evaluation and pilot tests.
• Sharing success stories and postmortems.
• Measuring adoption, not just access.

Ethics, compliance, and the human factor

AI isn’t just a workflow accelerator, it’s a compliance minefield. From confidentiality risks in document automation to bias in LLM-driven intake tools, every AI move must pass a legal ethics sniff test. That means:

• Reviewing ABA guidance and local jurisdictional rules.
• Training staff on prompt sensitivity and bias awareness.
• Logging tool use for auditability.

A culture-first approach to AI doesn’t just drive efficiency—it helps you avoid ethics violations and reputational harm. However, in the 2024 ILTA survey, 34% of firms said that they don’t have an official generative AI policy and another 26% said they were working on one.

(If you need help building an AI policy, we’re happy to share our approach with you. Just send us an email.

Where’s your firm on this spectrum?

If you’re buying tools without changing how you work, you’re not adopting AI. You’re just accessorizing your inefficiencies.

Audit your last three AI-related decisions:

• Who initiated them?
• Who was trained?
• Who is accountable for success?

Then ask the bigger question: are you building a smarter firm or just a shinier one? Let’s change that. LaFleur offers comprehensive AI consulting services that can help you improve your systems, foster team buy-in, and make the most of your firm data.

References

ILTA 2024 Technology Survey Results Released Today: Legal Technology Trends. (2024, September 20). eDiscovery Today. Retrieved from https://ediscoverytoday.com/2024/09/30/ilta-2024-technology-survey-results-released-today-legal-technology-trends/