Say you have a big contract review project to do, in connection with an M&A deal you’re working on. Should you just use an AI-enabled CLM to do this work? This is pretty tempting if you already have AI capabilities through your contract management solution. Is that technology enough to meet your M&A due diligence contract review needs?
TL;DR: Your CLM is not designed for M&A due diligence contract review. Contract Analysis AI is better suited for this.
We meet a lot of Contract Lifecycle Management system (CLM) users.
CLMs have features and capabilities galore. Some CLM vendors might pitch that their systems can be used for AI review of your contracts.
Knowing that you have access to AI contract review features, it can be easy to assume that those same features will help with any M&A reviews you do in-house.
In reality, CLMs are not designed to support M&A due diligence review. In fact, if you try to use a CLM to in-source M&A due diligence review, your CLM won’t do what you need it to.
Why CLMs are not good for M&A due diligence
1. CLMs don’t care about your target company’s contracts
They care about yours.
CLMs focus on workflows for contracts your company is signing, not for contracts you’re reviewing as part of an acquisition.
CLMs focus on contract organization, contract management, and contract review workflows. They’re set up to support your team’s review of existing contract types according to your existing needs. For example, your CLM may have a workflow for Master Services Agreement (MSA) reviews:
- a new MSA request comes in ➡️
- a workflow kicks off to send that request to Legal ➡️
- business and legal collaborate (and maybe capture an approval or two) ➡️
- the contract is negotiated (perhaps with the help of some AI review) ➡️
- the contract is signed ➡️
- the contract and its metadata are stored in the CLM.
If you’re looking to acquire a new entity, it becomes burdensome to put that entity’s contracts into your workflow. Let’s assume those contracts are MSAs. If you put them into your MSA workflow, you’d need to upload them as a signed contract (so that the CLM doesn’t think they’re a contract that’s being actively negotiated). You’d then need to ensure that:
- The AI is pulling information you care about in your due diligence review so that you can see and review that information,
- That you’ve carefully marked those contracts as separate from your own contract repository (you’ll have deletion obligations after diligence review is completed AND you’ll want to be careful not to confuse those contracts as contracts that your company has entered into), and
- That no one is pulling reports on MSAs during the diligence review period, because the CLM will treat those target company contracts as if they were your own (and your reporting will be inaccurate as a result).
This process is complicated, overly burdensome, and highly manual, making it prone to human error. Nobody wants to be the one responsible for not deleting a target company’s contracts from an old diligence review.
2. CLMs are often mediocre at post-signing contract review
Your CLM’s capabilities might not support post-signing review, or may do so with only limited success.
First, the term “AI” covers a lot of ground. Your CLM may have AI capabilities, but that doesn’t necessarily mean that those capabilities are the right ones for M&A due diligence purposes. Some CLMs support AI contract review pre-signing (review of contracts for risky terms or review of contracts against your playbook). Those are focused on whether your company should sign a contract and helping you negotiate that contract to better protect your organization.
Second, CLMs tend to be optimized for executing new contracts and storing completed ones. They are often subpar at bulk contract review. Ask around with the people who originally implemented your CLM: find out how fun it was to get data out of your pre-existing contracts and into the CLM.
M&A due diligence requires review of lots of pre-executed agreements, meaning that the AI is reviewing final, executed contracts for specific terms.
Even if your CLM’s AI supports post-signing review, there are three key problems you’ll run into:
i. The AI may not be able to track as many data fields as you need
While many CLMs tout post-signing AI capabilities, sometimes those fields are really limited, or focused on things that don’t matter for M&A due diligence reviews.
For example, it’s a timesaver for your CLM to capture things like parties, title, date, and payment terms from your contracts, but for due diligence review, you need to know things like change of control, assignment, and termination for convenience rights. Your CLM’s AI may not be equipped to find those for you.
ii. The AI may not have the accuracy levels you need
Even if your CLM’s AI is capable of finding the information you need (in theory), it may do so with very low accuracy (not all AI is the same, and CLM users may be more tolerant of misses while needing few false positives). Misses can be really bad in due diligence. Low accuracy rates, combined with other challenges with using a CLM for this purpose can spell disaster for anyone trying to use a CLM for M&A due diligence review.
iii. The AI is set up to review your contracts for things that may not matter to you in diligence review
CLMs are designed to cover your ongoing needs based on your company’s contractual obligations – Who do you have to pay and when? Who has to pay you and when? What did the counterparty promise to provide you? What did you promise to provide to the counterparty? On what timelines?
Those obligation-specific data fields are important, of course, and something you might be interested in in a M&A due diligence review, but they’re less important than change of control, assignment, exclusivity, non-competition, and the like.
3. CLMs don’t review contracts for your M&A due diligence needs
Your CLM’s AI is focused on your company’s contracts. That means it’s looking for all of the information that your company needs to know about its own contracts to understand its own obligations. It’s not set up to review the risks of acquiring another company based on what’s in its contracts, and it’s certainly not designed to answer the specific questions your company will have about those risks (when it comes time for your company to make a buying decision).
Handling that in your CLM would mean changing the AI’s review requirements for all contracts of that type (meaning those changes would apply to your company’s contracts, too). As a result, you’d get a lot of extraneous information on your M&A due diligence review and perhaps for your company’s own contracts, too (unless you would like that information for all of your contracts, that is).
4. CLMs are not designed with project-based flexibility in mind
Because CLMs are designed to cover your company’s day-to-day contract review workflows, they’re not set up to review contracts in batches on a project-by-project basis.
Now, we know what you’re thinking: “Our team uploaded thousands of contracts when my organization went through CLM implementation!”
Yes, you did, but those contracts were uploaded and linked to your company’s specific workflow and data capture needs. You told those contracts where to go, and what data should be captured along the way (if you were using AI to capture data for those contracts).
Everything was still tied to your company’s own needs and was not at all designed to be flexible. And, realistically, how did that implementation go?
When you’re doing buy-side M&A due diligence review (especially if you’re doing a lot of it on a regular basis), you need tech that supports bulk contract uploads, review of different data fields for different purposes (not all M&A due diligence reviews are the same), and supports your eventual obligation to both report on and make use of that data, then delete those contracts and their associated data once diligence review is complete.
Your CLM won’t parse out M&A due diligence contracts into separate projects, it won’t support project-specific AI review needs, and it won’t support easy bulk upload of those contracts into a project-specific workflow. It’s just not designed for that.
5. CLMs are not friendly to M&A due diligence review timelines
Have you ever tried to make a significant change to your CLM (add a workflow, add a new contract type, etc.)? It takes TIME, time you don’t have in a due diligence review.
Bottom line: CLMs support M&A once you acquire a company, not when you’re making a buying decision.
Contract Analysis AI is different.
Why contract analysis AI is great for M&A due diligence
Contract analysis AI is exactly what it sounds like: AI you can use to review contracts. Contract analysis AI designed for post-signature contract reviews won’t build flashy approval workflows for you (not by itself, anyway). It won’t support contract request intake, or various other CLM-specific features that your CLM will do really well.
But that’s okay.
Post-signature contract analysis AI (we’re not talking about pre-signature AI review here, because all M&A due diligence review will be done on contracts that have already been signed) has very specific purposes. Among those, is M&A due diligence reviews. Large law firms have been using this tech in M&A since 2013, and it has been pretty common since 2017.
Contract analysis AI is the best way to use technology to help M&A due diligence you do in-house.
Here’s why.
1. Contract analysis AI is project-friendly
Contract analysis AI does what you tell it to do. If you would like it to review one set of contracts for one specific grouping of data, it will do so.
2. Contract analysis AI is project-specific
Contract analysis AI doesn’t care about what you did in your last due diligence review (unless you would like it to!). You can use it to find different things for different diligence reviews based on the unique characteristics of that deal, and that won’t negatively affect your next diligence review project.
3. Contract analysis AI identifies the due diligence risks you care about
Contract analysis AI finds what you ask it to find, so you can focus your review on very specific clauses. Because AI will never be 100% accurate, it helps your legal team focus manual efforts (validation of AI extractions and review of highlighted risks across the contract portfolio you’re analyzing) on only the very specific things they should be reviewing. Importantly, contract analysis AI vendors tend to optimize their software to have fewer misses and more false positives (there’s a tradeoff), and interfaces that allow users to quickly refine results.
4. Contract analysis AI captures more information
Contract analysis AI has a narrow focus – finding important information in contracts, which means it will almost always have more data fields it is trained to extract (with higher accuracy) than your CLM, where AI is an add-on.
5. Contract analysis AI is customizable
Contract analysis AI will have a lot of out-of-the-box fields ready for your use, but sometimes you have review needs that go beyond those out-of-the-box fields. Contract analysis AI also lets you create and train your own fields, which allows you to leverage the power of Contract analysis AI for things that are unique to that specific deal.
6. Contract analysis AI is designed to give you data
The purpose of using Contract analysis AI is to extract information from contracts. That information becomes data: usable, powerful data to help you make buying decisions. Instead of being built to store your data, contract analysis AI exists to help users get the data and get out.
7. Contract analysis AI use will help you meet your M&A due diligence review timelines
M&A due diligence is time-consuming, while also conveniently packaged in a very short review timeline. Contract analysis AI can be up and running for a diligence review very quickly – right away if you’re using out-of-the-box fields or within a few hours if you’re training custom fields. Between the AI and UI, we find contract analysis AI users can often review agreements 2–3x faster than manual review.
The same is not true for other solutions, like CLMs or manual review efforts. Having quick access to data allows you and your team to focus on what has been asked of you – identification and analysis of risk – without risking a delay in the overall project timeline.
Bottom line: Contract analysis AI is the best technology solution to support your M&A due diligence reviews. Contract analysis AI delivers actionable data, quickly and seamlessly, so that your legal team can identify key risks and support buying decisions.
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