The AI Bedrock Law Firms Are Missing — And It's Limiting Your Team's AI Productivity

Today I'm going to talk to you about the single biggest productivity boost that you can give your law firm or legal team using AI in 2026. We custom build AI

automations for law firms and legal teams, in-house legal teams. And when we find the right process and we do that either by going in and doing an order where we speak to stakeholders and we learn about their workflows and we

identify where there's inefficiencies or often times a partner or a senior partner knows processes that are very laborious, very repetitive uh eat up a lot of manual hours and if it were to be

automated in part or in full, it represents a massive productivity boost in the firm's operations. And so these are things like intake automation, document generation, contract review against playbooks and knowledge bases,

matter prep, and the results are real.

There's no doubt about it. Lawyer time

dropped. The entire process speeds up and and the payback period is fast. And

that's often calculated by looking at the hours that they're not paying employees to do that. And the

opportunity cost of employees being able to work on other tasks, other higher value tasks. But that all said, I've

value tasks. But that all said, I've been thinking about something lately based on my observations within legal team, but it's become very apparent to me that the firms and legal teams that

are seeing the largest productivity gains overall are not those that have just invested in one or two big processes to be automated, which as I said can deliver tremendous productivity

gains, but that's often dwarfed when you have your whole team that knows how to use AI and there is a AI literacy foundation that's built. And so in this video I want to talk about that because

that is a different conversation altogether. Now here's what I'm seeing a

altogether. Now here's what I'm seeing a lot. Typically a firm or an in-house

lot. Typically a firm or an in-house legal team they've invested in some form of AI. It could be a legal tech platform

of AI. It could be a legal tech platform like Harvey or it could be getting everyone an enterprise seat on claude so they can use claude co-work maybe it's a chatbot for client intake.

Regardless, the technology is solid. The

technology works. But after a period of time, maybe it's a couple of months, maybe it's six weeks, you know, half the team or more has quietly gone back to how they were working before they bought

in that AI solution. And so the tool is there, but it's just not sticking. And

that's not a technology problem. The

technology is proven. I see firms leveraging it almost every day to a very high degree and seeing exponentially increased productivity. But what it

increased productivity. But what it really is is what I call an AI bedrock problem. And the stat that I think backs

problem. And the stat that I think backs that up and there's a lot of stats out there and so I don't say this without actually having seen this with my own eyes and believing this to be true, but

75% of law firms predicted AI would improve their workflows last year. But

this year only 37% said that it actually did do that. And that's a about 38 point gap between expectation and reality. And

when you look at why, it's almost never the tool. It's always the layer

the tool. It's always the layer underneath the AI bedrock literacy and foundation. So what do I really mean

foundation. So what do I really mean when I'm talking about AI bedrock? And

what do I mean when I make the claim that firms that have an AI bedrock will experience greater productivity throughout the entire company? Thinking

about it like a pyramid is a helpful visual reference. And so at the top

visual reference. And so at the top you've got custom builds and these are the big stuff, right? the proprietary

systems, complex automations, these departmentwide workflows that we talked about before. Below that, you've got

about before. Below that, you've got your AI workflows that are essentially automated processes that run without anyone having to think about them. Often

times, they're triggered automatically or they can be manually triggered. There

can be a human in the loop. They can be even developed by your team once they have some AI literacy and they have that AI bedrock. Below that, you've got your

AI bedrock. Below that, you've got your connected environment. And so the

connected environment. And so the connected environment is really important as it implies in this diagram.

You can't really do your custom builds and your AI workflows unless you have your connected environment. And so these are things like MCPS, API keys. But what

I want to talk about in this video is the foundational layers. So you've got your AI fluency and your AI literacy.

For the past year, most legal teams that I've encountered have been focusing on layer four and layer five. And there's

value in that. But what I've started to realize is that the productivity to be gained from layers four and five is limited. It's isolated and it doesn't

limited. It's isolated and it doesn't spread across the entire organization.

Quick break in proceedings. I promise

I'll keep this quick. But this is exactly what we do here at Cyberactive.

If you want this bedrock built for your firm, we typically do it one of two ways. We run inerson workshops where we

ways. We run inerson workshops where we come to your office. We set up your team's environment. We set up all the

team's environment. We set up all the infrastructure. We get your lawyers,

infrastructure. We get your lawyers, your parallegals actually fluent and connected. And we also run these

connected. And we also run these workshops remotely as well. And on top of that foundation, we build the big custom workflows, intake automation, document generation, the kind of thing that cuts multi-hour processes down to

just minutes. If that sounds useful, if

just minutes. If that sounds useful, if you're interested at all, there's a link in that description. So, let's unpack what the bedrock actually looks like.

Starting with the skill side, AI literacy is the floor. It's your team's understanding of what AI can and importantly can't do. not at a technical level per se. They don't need to know

how a model works, but they need to know that it can be confidently wrong, that it needs specific context to get useful output. Context is so important, by the

output. Context is so important, by the way. I've got a video coming out on

way. I've got a video coming out on that. Context is one of the biggest

that. Context is one of the biggest determiners in the quality of output.

When we're talking about context, we're talking about reference documents, a firm's internal proprietary information combined with the data that the model has been trained on. But anyway, let's get back to talking about AI literacy.

And a lot of firms skip this or they focus on it very little. They maybe hand people a tool whether it's cla code or a legal tech platform and they assume they'll figure it out. Maybe they do a

few training sessions and the reality is that lawyers be it associates parallegals partners even they do figure it out to a degree but they're still only extracting just a small proportion

of the total value that can be getting from these tools. AI fluency is the next layer up. And honestly, this is where it

layer up. And honestly, this is where it starts to get pretty interesting and exciting as a user because you're not just using AI, you're starting to work with it. You know how to give it

with it. You know how to give it context, how to iterate, how to build on a previous output rather than starting from scratch each time. You've built

habits and AI is your first move, not your last resort. And the research seems to back up what I'm actually observing inside of law firms and legal teams. The data here says that organizations with a

mature AI upskilling program get double the significant ROI from their AI investments compared to organizations that don't have one. And so just think about that. Double the ROI, same tools,

about that. Double the ROI, same tools, same budget. The difference is just that

same budget. The difference is just that AI bedrock. And for a legal team, this

AI bedrock. And for a legal team, this looks like a parallegal who knows how to prompt for a first draft research summary, then review it, then push back on the gaps rather than just copy pasting the output into a document. or

it looks like an associate who's built a weekly habit of using AI for matter prep before a client call. It even looks like a partner who knows what to delegate to AI and what still needs their judgment.

To me, that's fluency and that is trainable. The third layer of the

trainable. The third layer of the bedrock is the connected environment.

And so, what I'm talking about here is the infrastructure side. Your AI is genuinely only as useful as the context that it has access to. And so, when we're talking about context, we're talking about its memory. We're talking

about what proprietary internal information it can combine with its training data. So if your team is using

training data. So if your team is using AI in isolation the same way that we all started using chat GPT or clawed chat and we just pasted things in and out of the chat window or may maybe they're manually copying from your case

management system that disconnects every time they close the tab then they're working harder than they need to be. A

connected environment means your firms are talking to your AI native integrations where they exist. tools

like Cleo and Net Documents, I manage, they all have these built-in native integrations with tools like Claude.

Then you've got your no code bridges or your low code connections. And so here we're talking about the likes of Zapia or Make or N8N. And essentially what these allow you to do is connect your tech stack, your tools, your contract

management system, whatever you're using, your SharePoint to AI even if they don't have an integration in the native environment. So it really opens

native environment. So it really opens up the possibilities for workflow automation and for efficiency and productivity gains without needing IT or engineering support. And then the level

engineering support. And then the level three, the third layer is a bit more advanced, but this is where we start to talk about MCPs and APIs. You don't

really need to worry about what that means. Essentially, what they both do is

means. Essentially, what they both do is sit between your AI platform, let's say Claude, with the tools that you're already using. And it's a way to connect

already using. And it's a way to connect and bring data and send data between them. And so the effect is you're giving

them. And so the effect is you're giving your AI platform real-time access to your firm's actual data environment.

Now, I'm not saying that you as a lawyer or a partner need to really understand these things at a technical level, but it's important to understand what they are and what the capabilities allow for you and your team to achieve. But once

you have some of these things in place and your tools are starting to talk to each other, your AI isn't a standalone tool anymore. It's woven into how your

tool anymore. It's woven into how your firm works. A lawyer can ask you a

firm works. A lawyer can ask you a question and it already knows what matter they're working on, what documents are relevant, what the client's history looks like. That's when

you start getting the kind of productivity gains that compound. Here's

the picture that I want to leave you with. A firm with the AI bedrock in

with. A firm with the AI bedrock in place looks like this. Every team

member partner associate parallegal ops member has a baseline of AI, a fluency. They know what they're doing.

fluency. They know what they're doing.

They trust the output. They know how to verify. and they've built habits that

verify. and they've built habits that mean AI is part of how they work every day, not just something they try out occasionally or feel like they need to do. On top of that, the environment is

do. On top of that, the environment is connected. The tools talk to each other.

connected. The tools talk to each other.

The AI has context and when we come in or someone else comes in and builds a custom workflow, be it intake automation, document generation, whatever the highest ROI process is, it lands on a team that's ready for it.

They adopt it, they build on it, they start suggesting improvements, and they start suggesting the next automation that can help them. That's the

compounding effect. The bedrock makes every build better and it makes every individual on the team more effective, not just by through the processes that a company comes in and automates for you.

Now, finally, if you want to start building this for your team, I've put together a free guide as per usual. It's

called the law firm AI fluency starter kit and you'll find it over at legal ai.com.

ai.com.

It covers the prompts, the habits, the environment setup, the steps to get your bedrock in place from day one. The link

is in the description and if you want us to come in and build it with you, perform a workshop, set up your environment or do a full custom build, there's also a link to book a call with me or a colleague. We work with firms of

all sizes, small and large. And if you found this useful, appreciate a subscribe. I put out a new video every

subscribe. I put out a new video every week trying to really break down AI and show practical AI use cases for legal teams. And so I will see you in the next