What’s Wrong With CLM Systems? – Artificial Lawyer

By Jim Chiang, Docgility.

The CLM Reality Check

If you’ve been to any legal tech conference lately, you’ve probably heard the horror stories. Conversations either revolve around AI or tales of CLM implementations gone wrong. Traditional CLM systems often promise the world but deliver disappointment – poor user adoption, metrics that don’t improve, and rollouts that never quite make it company-wide.

When things go south, the finger-pointing starts. Tech vendors blame the business side, citing culture issues, poor integration, or lack of ‘readiness’. But here’s the thing: there are some real technology problems that make success really hard. So what’s actually broken?

Why CLM Systems Make Contracts Take Longer to Execute

Let’s talk about the metric that actually matters: contract cycle time. That’s the time from ‘we want to do a deal’ to ‘contract is signed’ – covering everything from drafting through review, redlining, collaboration, negotiation, and finally getting signatures.  For most customers, this is the only metric that really counts. Close deals faster, make more money. Simple, right?

Now imagine spending a fortune on a CLM system only to discover that your contracts are actually taking longer to close. That’s the nightmare scenario many companies face, and it happens more often than you’d think.

The Concurrency Problem (Or: Why Only One Person Can Touch a Contract)

Here’s a big part of the problem: most CLM systems don’t support multiple people working on the same contract at once. They’re built around this old-school idea where you have to ‘check out’ a document (like borrowing a library book), make your changes, then ‘check it back in’ before anyone else can touch it.

So if legal is reviewing a contract, finance has to wait. If sales wants to make a change, they’re stuck until whoever checked it out is done. Not exactly what you’d call collaboration, is it?

This doesn’t just slow things down – it kills any chance of real teamwork on contract negotiations.

Workflow: The Answer That Isn’t Really an Answer

Workflow sounds great in theory. It makes sure the right people review contracts at the right time—legal first, then finance, then whoever needs to sign off. It keeps things organized and ensures proper approvals.

But here’s where it breaks down: what happens when you need multiple teams to collaborate on the same issue? Say you’re trying to figure out pricing and payment terms together. With traditional workflow, the contract just sits there waiting for the next person in line to do their thing.  In many ways, workflow is the answer when it’s not possible to support concurrent contract edits, because it enforces one user at a time.

Workflow is basically an ordered, sequential process – do A, then B, then C. That works great for building cars (you definitely want to put the tire on the wheel before mounting it), but contracts aren’t cars. With the right permissions, you should be able to have any team review and edit at any time.

The bottom line? With workflow, you’re always going to have slower contract cycle times. Next time you talk to a CLM vendor, ask them to design a workflow that gets the right approvals but runs four times faster. Watch their faces – it’s pretty entertaining.

Is Your CLM Just a Fancy Document Versioning System?

Most CLM systems treat every little change as a brand new document version. Want to add the word “not” to a sentence? Check out the contract, add “not,” check it back in—boom, new version.

Think about how wasteful that is. By the time you’re done negotiating, you might have 60+ versions of the same contract sitting in your system, just because people made small edits along the way.

And here’s the nightmare scenario: someone accidentally checks in an old version of the contract, wiping out all the recent changes. Depending on how the workflow is set up, that contract might actually get executed with all the previous work lost.  This happens way more than anyone wants to admit.

Can AI Fix Everything?

We love AI we’re working with it every day and seeing real advances. But let’s be honest: AI isn’t going to magically solve all these problems overnight.

We’re still in the early days of AI technology, and there’s going to be huge progress in the coming years. But without systems that ensure human oversight and contextual intelligence (AI that actually understands your organization’s practices, relationships, and business context), AI recommendations are always going to be limited.

Contracts Need a Village

Here’s the reality: even if you had the most advanced AI-powered application on your laptop, you still couldn’t execute contracts quickly on your own. Contract review and approval requires a whole team of people.

Inside your organization, you might have finance, operations, legal, sales, executives – all needing to weigh in before anything gets signed.  But it doesn’t stop there. You might have outside legal counsel, subcontractors you need to coordinate with, plus the counter parties and their representatives, often spread across multiple geographies.

The complexity grows exponentially with longer, more complex contracts– more time needed by each reviewer, more reviewers from all parties involved. CLMs might handle internal workflow okay, but they completely fall apart when you need to involve outside parties.

According to WorldCC, complex international contracts take an average of 26 weeks to complete. In today’s fast-moving business world, are six-month contract cycles really acceptable to anyone?

The Bottom Line

The problems with CLM systems aren’t just about company culture or implementation approach—though those matter too. There are real technological limitations that make it hard for these systems to deliver on their promises. Until we address the core issues around concurrency, workflow flexibility, and multi-party collaboration, CLM implementations will keep falling short of expectations.

You can find more about Docgility here.

About the author:

Jim Chiang is the CEO and Founder of Docgility, makers of the industry’s first AI-powered Contract Acceleration Platform.  Before starting Docgility, Jim led AI engineering at two of the biggest names in CLM: Icertis and Apttus (merged with Conga).

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[ This is a sponsored thought leadership article by Docgility. ]