Most law firms don’t have a software problem.
They have a software sprawl problem.

Between Microsoft 365, iManage or NetDocuments, security tools, billing systems, AI platforms, and a growing list of niche solutions, firms are now managing dozens of licenses per user—often with very little visibility into actual usage.

And now AI is entering the mix, adding:

• new tools
• new pricing models
• and new layers of redundancy

The result?
Firms are overspending, underutilizing, and duplicating capabilities at scale.

AI isn’t just another line item it’s the tool that can finally fix this.

The Real Problem: You’re Paying for What You’re Not Using

In most firms, license management looks like this:

• Licenses purchased at the firm level
• Assigned broadly “just in case”
• Rarely audited after initial rollout

What we consistently see:

• 20–40% of licenses are unused or underutilized
• Multiple tools performing overlapping functions
• Premium tiers assigned where basic would suffice

And with AI:

• Firms add tools like ChatGPT Enterprise, Copilot, Harvey, or others
• Without removing anything else

Costs go up. Value doesn’t.

Where AI Changes the Game

AI introduces something most firms have never had:

real visibility into how tools are actually used

When deployed correctly, AI can:

1. Analyze Usage Patterns Automatically

• Who is using what tools—and how often
• Which features are actually being used
• Where licenses are idle

No more guessing. No more annual “best effort” audits.

2. Identify Redundancies Across the Stack

AI can map capabilities across systems and flag overlap:

• Document review → Harvey vs CoCounsel vs internal tools
• Drafting → Copilot vs ChatGPT vs legacy templates
• Search → DMS vs AI vs external research platforms

Most firms are paying for the same function 2–3 times.

3. Recommend Right-Sizing by Role

Not every attorney—or staff member—needs the same tools.

AI helps segment:

• Power users vs occasional users
• Practice-specific needs
• Admin vs attorney vs paralegal workflows

Result: smarter license allocation instead of blanket provisioning

4. Continuously Optimize (Not Just Once a Year)

Traditional license reviews happen:

• once a year
• maybe twice

AI enables:

• ongoing monitoring
• proactive recommendations
• real-time adjustments

License optimization becomes a system, not a project

The Hidden Risk: AI Without Optimization

Here’s where most firms get it wrong:

They adopt AI on top of an already inefficient stack.

Instead of:

“What should we remove, consolidate, or replace?”

The mindset becomes:

“What else should we add?”

This leads to:

• rising software costs
• fragmented workflows
• user confusion
• and poor adoption

🔥AI becomes expensive and underwhelming

What Smart Firms Are Doing Instead

The firms getting this right are taking a different approach:

Step 1: Audit Before Expanding

• What do we already have?
• What’s actually being used?
• Where are we duplicating?

Step 2: Rationalize the Stack

• Consolidate overlapping tools
• Eliminate unused licenses
• Align tools to real workflows

Step 3: Layer AI Intentionally

• Deploy AI where it replaces—not duplicates
• Align AI tools to specific use cases
• Integrate with existing systems (DMS, M365, etc.)

Step 4: Build Ongoing Governance

• Usage tracking
• cost monitoring
• role-based provisioning
• periodic optimization

The Opportunity

License optimization isn’t just about cost savings.

It’s about:

• simplifying the user experience
• improving adoption of AI tools
• reducing risk and sprawl
• and making your technology stack actually work together

Most firms can:

reduce software spend
improve performance
and accelerate AI adoption

All at the same time.

Final Thought

AI isn’t just another tool to buy.

It’s a forcing function.

The firms that treat it as:

• a cost driver
  will struggle.

The firms that use it to:

• optimize what they already have
  will come out ahead.