AI for Business Operations

-- by Jessie Gabriel

AI. That’s all people are talking about right now. And I’m not just saying that because I’m writing this from a coffee shop in San Francisco (where, literally, everyone is talking about AI . . . or being “ex-Yahoo” . . . or their tech stack . . . or enneagrams). I’m saying it because this is also the conversation we’re having with our clients and fellow entrepreneurs. There are two pieces to this. Let's start with piece number one: how to use AI to support business operations. 

We love technology around here. When I launched All Places in 2020, we were already more tech-enabled than my former Big Law employers. That is not an exaggeration. How is that possible? Two reasons. First, the Big Law model incentivizes inefficiency. Why use a tech tool when you could instead bill the client for 25 hours of associate time? Second, management at most law firms is, ahem, mature. They are not what we would call early adopters. The current way of doing things made them rich, so why change? 

We don’t have either of those problems. We want to be efficient and we want to be effective. If technology can assist with that, fantastico. Great. Now, how do we find that technology?  

Know when to ask for help. Earlier this year we engaged a brilliant consultant to do just that. Lara’s scope was as follows: learn our pain points, assess the available AI-based solutions, support us in trialing those tools, and then support us in implementation. The pain points part was easy. We had already been tracking how we thought we could be better, faster, even more precise. The assessment of the tools on the market is where things became interesting. 

There is no shortage of bad options. The first thing you should know about AI-powered operational solutions is that there are a zillion of them. It doesn’t take a genius (or much time or money) to create an idea and lay it on top of an LLM. You could probably vibe code your way into a purported new product launch in a month. Slap a logo on a simple website, and there you go. Who wants to subscribe?!?! 

But not many good options. The challenging part (and where expert guidance was particularly valuable) was identifying which tools were viable—which ones truly had the functionality, were likely to work properly, and would still be in business two years from now. As Lara explained, there’s a difference between a great demo and a tool that will work just as well on our systems. She came from the product side, so she knew what to look for. As much as we liked the idea of a flashy, new solution, we only looked at tools that already had customer review history. Onboarding a new tool is a significant investment—of time more than money—and we didn’t want to waste time on a shoddy product or one that didn’t have good customer service. 

You have to invest the time. While it’s tempting to rush through and just sign up for something, we have taken our time. We must be confident before we move forward. It’s easy to create new accounts, but hard work to fully integrate a new way of working into our company (and we are a team of 6—integration only gets harder as your team grows). We identified a few contenders, Lara signed us up for trial accounts, and we are doing that work. Is this something that we will genuinely use and will actually make us better at our jobs? Both of those things need to be true. 

Where are we now? We have pulled the trigger on one tool. It is user-friendly, comes from a reputable company, and will generate immediate value for us and our clients. The next piece is to start creating our standard operating procedures so utilization across the firm is consistent. We are also in the middle of trials with two competitive tools and will select one by the end of this month. Neither one is perfect, but both have potential. 

What else did I learn? It’s better and worse out there than I thought. There is no shortage of AI-based products being sold. At the same time, there are things on our wish list that don’t exist yet. 

Jessie: Amazing! We’ll just build it ourselves!  

Lara: Uh, that would be a lot of work. Do you have time for that?  

Jessie: Right. No. 

That means we can either wait for someone else to build it, or we can find the closest solution and offer to partner with them to create the tool we think the market needs. TBD on that one, although we don’t even have bandwidth for the latter at the moment. 

Parting thoughts. Nothing meaningful is easy. Admittedly, there was part of me that thought we could just find the products of our dreams, sign up, and immediately be made more amazing. But that’s not how this works. Making a meaningful change of any kind in your business is a commitment. If you want to go down this path—which I think everyone should—you need to set aside the resources to do it properly. None of us has time or money to waste on tools that we don’t really use or don’t use well. If you’re going to do it, do it right. 

I said at the beginning that this is just the first piece of this conversation. What is the second piece? How to use AI on the product side rather than the operations side, and what the legal implications are. That’s a harder one that we will start tackling with you next month. Stay tuned. 

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