How to Write Your Legal Playbook for AI

It’s a universal truth: legal—and everyone else—is being asked to do more with less right now.

In a 2026 Gartner report, 81% of legal departments reported increased demand for contract support over the past year. But the traditional model where every contract review depends entirely on lawyer time doesn’t scale. 

That’s where AI can be truly helpful for legal teams. At Ironclad, we’re using AI to manage a higher volume of contracts, address repetitive (and frankly, boring) pieces of contract review, and give our legal team a chance to be more strategic and impactful with their team. 

Creating a legal AI playbook gives you consistency across your entire organization. “What you end up doing is individuals will build their own playbooks, and then you get inconsistent results,” says Alastair Peterson, director of Consilio. “I used to be a practicing attorney, and I find that you’re so heads down on doing the work. You don’t have time or at least you don’t think you have time to translate what you’re doing into something repeatable into a process. Taking the time to build a playbook for everyone will be worth it in the long run.”

To show you exactly how we built our legal AI playbook, we conducted a three-part webinar series. You can watch the entire series here, or read on for some of our key takeaways so you can get started building your own playbook.

How to develop your legal AI playbook

Contracts are a great use case for AI because they’re often repeatable processes. Codifying your rules, fallback positions, and patterns into a playbook so AI can take a first pass can save your team a lot of time—but there’s a lot to consider to make sure everything goes right. Says 

Michael Berrini, AGC at Ironclad, “Using generic AI models with no grounding in your legal standards, company positions, or risk framework won’t work. It’s important to think through all of the possible scenarios and give specific instructions so you’re not creating more work for your teams, or more deal risk.”

Think of developing your playbook as less outsourcing everything to AI and more creating a set of guidelines where AI can make it easier for a human to review. Says Berrini, “You have to layer in that lawyer’s judgment, awareness, and negotiation strategy to ensure the deal gets done the right way. So AI can take many tasks, but we definitely reserve certain aspects of the process for humans, and your playbook should reflect that.”

Tasks to outsource to AI	Where a human stays in the loop
Any standard, repeatable positions where you can make assumptions with information like contract type, data sensitivity, or deal size	Live trade offs where motivation and context matters

To determine what tasks you can automate, think about these questions:

• What is the relationship history between you and the other party?
• What is the broader commercial picture? It may be a small deal today, but is it an investment to grow?
• Is it on third party paper?
• Which contract types or deal conditions should this AI playbook be used for? You may need to separate by type.
• Is there additional contextual information that AI might not know, based on the deal itself?

The key to success is being as specific as possible with your instructions. In a non-AI playbook, for example, you may have a narrow non-solicit clause. But for AI, you’ll need to be more specific, like adding language applying the non-solicitation clause only to current employees engaged in the project. “This gives AI the guardrails it needs to narrow the clause instead of leaving it up to interpretation,” adds Berrini.

The best playbooks don’t stop at preferred language. They also add in fallbacks and fail-safes, including what’s unacceptable for your terms, and when you need to escalate an issue to a human. This is all about establishing guardrails and determining where to put a human in the loop so you know when AI can take a first pass vs. when someone on your team needs to approve the changes.

An example rule could be that if supplier spend is above a certain threshold, say, $100M ARR, use X liability position. But the human piece is that if it’s a strategic, tier one supplier, or it’s been a tense negotiation, you may need to flex to preserve the relationship. 

Says Berrini, “The value of lawyers is not going away. What sits at the heart of negotiation is that judgment piece, understanding those motivations, reading the room, deciding how to treat internal versus external stakeholders, and figuring out what strategy actually gets the deal done.”

Refining the legal AI playbook so it works for your team

Where most organizations stop is in step one, but it’s crucial to continue to evaluate your playbooks on a regular basis. “It’s not a one-time build,” says Ed Cottrell who manages Ironclad’s legal AI specialists. “You’re going to hit a point where the playbook isn’t sufficient, and you need to make sure it remains applicable within the context of your organization.”

That’s because your organization will keep changing, and whoever is picking up the work needs to be confident they’re using a playbook that actually is going to help them get it done, whether they’re brand new to the firm or have decades of institutional knowledge.

At Consilio, they’ve seen customers whose playbooks worked well for American law, but didn’t correctly address multinational concerns. They created new playbooks to better match the legal landscape in other locations. “Your U.S. playbook for NDAs could be very different from a French one, for example,” says Peterson. “It goes both ways, with things like HIPAA in the United States, and different data privacy laws in France. I’ve also seen customers that create playbooks just for specific critical suppliers, like one for Amazon.”

Include review cycles for your playbooks just like any other asset, watching for changes like:

• Internal policy changes
• Supplier paper changing or post-renewal changes that may impact a variety of clauses
• New or changed legal landscape in your country of operation, such as tariffs or privacy laws

“You want to be able to be consistent from page one to six hundred, with no formatting errors,” says Peterson. “Generative AI enables you to do that.”

How do you know your playbook is out of date? You’ll need to check in with your team on a regular basis, recommends Peterson. If you’re finding lots of folks need to spend cycles going back-and-forth with AI to try and modify the changes, or they’re constantly making edits after the playbook runs, it’s probably not quite where it needs to be.

“One of the hardest things as a lawyer is to recognize your own fallibility, to know I’m not actually doing a perfect review every time, especially when you’re talking at these massive agreements, like MSAs with twelve attachments or it’s a 201-page play playbook,” he says. “But no human being does a perfect job with that. AI can give you consistency, and the challenge becomes how to keep your rules up to date so you don’t end up with twenty people prompting it in different ways when it doesn’t work right the first time.”

As you start to use your playbook, think about how you’ll stay in touch with your team and solicit feedback to improve. This could be:

• A designated governance committee that updates the playbooks each quarter
• An anonymous suggestion box where teammates can submit issues with the playbook
• Monthly check-in where your team can deliver feedback or talk through how they’re using it
• Tracking the number of AI suggestions used vs. overwritten in the platform

“Overall, look at the output and make sure you’re inspecting what’s happening, and getting feedback on the results. You want to make sure you’re providing resources for your team to keep learning as AI gets better and better,” adds Berrini.

Keep the legal AI playbook running smoothly

When it comes to actually using the playbook, Ironclad’s GC Jasmine Singh recommends doubling down on AI assistance. She uses Ironclad’s Jurist to pull relevant rules from the playbook and summarize any red line edits to make her review go that much faster. “What’s really exciting and helpful about this is that it recounts all of the choices that I’ve made, and gives me the context up front, like whether or not I’m the customer, whether or not it’s third party paper, and then it can provide a status bar to help me track my progress,” she says. “If I want to scale up, I need to move faster, but I still want to make sure I’m doing my due diligence.”

Using an AI companion alongside your playbook can speed up the human element of review so that you’re not missing out on the context you need to get it done. You can ask it questions like:

• What is the history with this supplier?
• Is this a renewal or net new contract?
• How did we deal with a similar vendor or similar contract language in the past?
• What’s an example of getting around a similar tricky provision in another contract?
• Who submitted the contract and what team needs it?
• What work product is being expected by way of the contract?
• What role does the actual purchase play in the organization?

AI can serve up your organization’s legal precedents so you’re not starting from scratch or wasting time debating your next course of action. “This is where the real value of AI in the legal workflow begins,” says Suha Saya, Director of PMM, Jurist. “How can we leverage those contracts historically that we have redlined against in our future redlines so that we’re not having to reinvent the wheel. We’re not having to always manually draft playbooks. Especially as commercial lawyers, we know that not all redlines are driven by the document, but by what’s true about the deal at large.”

Ready to write your legal playbook for AI?

You already know that a playbook sets clear and consistent guardrails for how your company thinks about contracts.

But it’s more than that. “Your playbook takes a stand at, with respect to priority, what you think is

most important, what to do in the absence of language in a contract,, and what fallbacks to offer if a counterparty pushes back on your original revisions. With a playbook, you know where you’re willing to be flexible to get the deal done,” says Singh. “You don’t have to manually edit it for the hundredth time.”

Is it possible to redline an agreement without a playbook? Of course. That’s always been true. But a playbook can make it so much easier. It reflects what your organization thinks is a good redline and what’s unacceptable so everyone is on the same page.

“Imagine you have a new junior attorney starting. That person, of course, is gonna know how to redline the agreement, and they might do an okay job on certain sections. But if it’s their first week, what they don’t know is what do you or your company care about and how do you work,” explains Singh. “Do you pay invoices in 30 days or 90? Do you agree to late payments? Do you ask for uncapped indemnities in the event of a data breach? Are you okay with aggregated anonymized data? There’s no way they can know that unless you tell them. That’s the context that can be stored directly into AI so you’ve got it every single time.”

Watch the full series here.

Ironclad is not a law firm, and this post does not constitute or contain legal advice. To evaluate the accuracy, sufficiency, or reliability of the ideas and guidance reflected here, or the applicability of these materials to your business, you should consult with a licensed attorney.