🍔 Your Takeaways

  • Agentic AI executes multi-step workflows autonomously; different from assistive AI

  • Early adopters report 60-80% cycle time reduction, though results vary by firm maturity

  • Implementation requires governance setup and workflow redesign—not plug-and-play

  • Accuracy issues persist (17-34% error rates); agentic systems can compound errors

  • Firms that restructure deliberately see margin retention; those that just add AI see compression

The conversation around agentic AI has the same energy as Chief AI Officers did last year: everyone's worried about falling behind, everyone's overlooking whether they're actually ready.

Agentic AI isn't magic.

The firms seeing real gains aren't licensing tools and hoping for the best.

They're asking hard questions about workflows, governance, and economics.

Liam


❓ What Agentic AI Actually Is

Assistive AI: you ask a question, you get an answer.

You're in the loop at every step.

Agentic AI: you define a goal, the system figures out how to get there.

It breaks the task into steps, executes them, adapts to unexpected data, delivers a result.

No prompting between steps.

Early adopters report 60-80% cycle time reduction on document work, though results vary significantly by firm maturity.

What's Actually Shipping

Thomson Reuters launched agentic capabilities in CoCounsel in January 2026.

Process up to 10,000 documents without human intervention between steps.

Define workflows once, run them on every new matter.

M&A due diligence: 2-3 weeks compressed to 3-5 days.

45% of law firms are deploying AI or plan to within one year.

Implementation success depends heavily on workflow maturity and governance infrastructure.

The Real Watch Outs

Implementation is not plug-and-play.

You need workflow redesign, governance setup, partner training—4-6 weeks minimum.

Accuracy issues persist.

17-34% error rates on legal tasks; agentic systems compound errors across workflows.

Governance is the hard part.

Clear escalation criteria, audit trails, quality checkpoints—most firms skip this.

Exception rates take time to refine.

Early pilots see 15-25% exception rates; takes 60+ days of tuning.

Staffing disruption is real.

If you don't frame redeployment as opportunity, associates see automation as threat.

Timeline reality.

90-120 days for meaningful gains if everything goes well; most firms take 6+ months.

Why This Still Matters

Competitive positioning: 6-12 month advantage before this becomes table stakes.

Client expectations: In-house legal departments adopting AI at 2x the rate of outside counsel.

Talent value: Associates who design and oversee autonomous workflows will be more valuable than those doing manual review.

Economics work IF you restructure deliberately.

You can't just add agentic AI to your billable hour model and expect the same revenue.

Choose: capacity expansion, pricing shift to fixed-fee, or hybrid.

Without deliberate choice, you compress margins without capturing upside.

Readiness, not technology, is the differentiator.


Getting Implementation Right

Governance first, tools second.

Define what the agentic system decides autonomously versus what escalates—4-6 weeks upfront, not optional.

Workflow redesign is required; you can't just apply agentic AI to existing workflows.

Associates move from document review to exception handling, client communication, and workflow refinement.

Realistic metrics:

Month 1: Governance design, workflow selection.

Month 2-3: Pilot execution, measure exception rates and cycle time.

Month 4+: Scale if solid (<20% exception rate, 50%+ cycle time reduction target).

Red flag: Exception rates above 25% after 60 days = workflow needs redesign.

The Custom-Built Alternative

Not everyone needs vendor tools.

Firms with budget and technical capability can build custom workflows.

Pros: Highly customized, handles edge cases, proprietary advantage.

Cons: $100K-$300K+ upfront, 6-12 month timeline, requires ongoing maintenance.

Who: Larger firms with high-value workflows where differentiation matters.

Hybrid approach: Start with vendor tools to learn, then build custom workflows for differentiating areas.

Are You Ready?

Are You Ready?

Not: "Do we have the right tool?"

Real question: "Do we have documented workflows, partner alignment, and governance discipline?"

If no: Start with fundamentals first.

If yes: Ready to pilot—pick one high-volume workflow, measure results, scale from there.

FREE ROADMAP

Ready to Pilot Agentic AI?

Get your personalized 90-day implementation roadmap with governance milestones, success metrics, and red flag warnings—tailored to your firm's readiness level.

Related Legal AI News:

🛠️ 10 Second Explainers - AI Tools & Tech

  • Leah (formerly ContractPodAi) All-in-one CLM platform with agentic AI built in.

    Leah can flag risky clauses, propose redlines, and run compliance checks against your clause libraries autonomously.

    Integrates with Microsoft Word and supports negotiation workflows inside its CLM environment.

  • Luminance AI platform built for high-stakes document analysis.

    Strong in anomaly detection and compliance mapping, particularly for cross-border M&A and due diligence.

    Can process thousands of documents and surface insights without manual intervention between steps.

    Best for firms handling complex, multi-jurisdictional reviews where edge case detection matters.

READER POLL

Where is your firm on agentic AI adoption?

A) Already piloting or deploying agentic workflows

B) Evaluating tools but haven't started pilots yet

C) Aware of agentic AI but no concrete plans

D) Still focused on basic AI tools (research, drafting assist)

E) Not prioritizing AI adoption right now

[Reply with your letter choice] - I'll share the results in the next edition.

Final Take…

Here's what I'm seeing: the firms that are getting real value from agentic AI aren't the ones that moved fastest.

They're the ones that moved deliberately.

They spent 4-6 weeks on governance before deploying.

They picked one workflow instead of trying to do everything at once.

They measured exception rates and cycle time.

They restructured pricing or staffing to capture the gains instead of just hoping margins would hold.

This is transformation work.

It requires discipline.

And yes, there are real risks and limitations that matter.

But the competitive window is real.

In 12 months, this will be table stakes.

The firms that move carefully now will lead the firms that panic and move fast later.

Hit reply if you want to talk through where to start or what's actually realistic for your firm.

— Liam Barnes

Need help designing governance frameworks and workflow architecture for agentic AI deployment?

Grab some time to chat

(if you don’t see a suitable time, just shoot me an email [email protected])

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