Focal Point CEO Anders Lillevik on Automating Procurement with AI Agents

Hello and welcome to the latest edition of the Techstrong AI Leadership Insight series. I'm your host, Mike Bazar. Today we're with Andrews Livic, who is CEO for a company called Focal Point, and we're talking about, well, how AI is gonna be used in procurement.

Andrews welcome to the show. Pleasure to be here. Uh, Michael, how are you doing?

I'm well, I'm well. There are clearly all kinds of manual toil, thankless tasks that have to do with procurement. So will AI kinda automate all of that?

And to what degree can we expect to see maybe that whole procurement process become, well, I don't want to say enjoyable, but you know, less tedious? Well, I think we're already starting to see some impact of AI in procurement. So it's started couple years back.

Now we have large language models where consumers of procurement services can interact with procurement in the large language model manner to say, I need something from procurement. And the, and the large language model say, well, what do you need? Like, do you need services?

Do you need goods, do you need it? Stuff like, whatever. And they kind of chat them down to the, to the right path and, and, and get them in the door, so to speak, for self-service.

And that's, that's been adopted quite heavily, certainly in the mid-market enterprise is getting there. And now we're starting to look at things that are, like you said, are, are just thankless tasks like in invoice reconciliation and entering in invoices and entering in contract information that typically gets done manual poorly and people fill in the least amount of information they can to get in the door. And, um, so we're starting to see a lot of that as well.

So I think we are, while the adoption is still nascent, that players are really coming to the fore now with great solutions and, uh, I think the future is here today. One of the things that has always kind of perplexed me about this whole rise of AI agents is how this is might actually play out in the real world. So in theory, as the procurement agent, I'm gonna create an AI agent that I might train to go buy things at the best price possible.

That AI agent is likely to encounter AI agents created by a seller who's trying to sell something at the highest margin possible. Will these two AI agents meet somewhere and negotiate, or will they just kind of like ground each other to a standstill? Well, I think if procurement agents are trained to be procurement people, they will ask more than one place will go to more than one place for, to sort of fulfill their needs to make sure that there is competition still.

So while the agents are kind of battling it out, I still believe that there will be, and the procurement will prevail, so to speak, where they will try to look at multiple places for the same stuff to ensure that they get the best value from money. But yeah, we, we, as procurement professionals, we have a lot of funders sort are thinking about the fact that you have two bots going at it negotiating, uh, and, and trying to come up with, with the best solution. And, uh, it is a little funny to think about, but I think you're absolutely right.

I think there will be some of that. I think vendors will tend to maximize their revenue or maximize their, their margins and procurement agents will try to do the opposite. And, and, and I think it will be the tolerances that are built into both models.

So they'll dictate where we actually end up. What does the procurement organization of the future look like then? Is it basically, uh, uh, a a small number of humans trying to manage a army of AI agents, or how do you kind of envision all this playing out?

So what I've seen for some of our customers is they actually have the same amount of people that do more value added stuff. And the other interesting part I've seen is you have some, um, individual companies now that are assigning agents to be owned by procurement people. So they're responsible for the training and the execution and the outputs of these agents to try to maximize what they do.

And let's be honest, right? Like no one really wants to do invoice, invoice reconciliation. Using a VLOOKUP in Excel like that is a tedious task, doesn't add a lot of value, right?

And if you can get an agent to do 95% of that work and you only manage exceptions, and even you can train an agent to do a lot of exception processing too. But if you, if you start figuring out that people can need to only work on the stuff that the AI agent can't solve, a lot of free time is gonna get spent on more value added stuff like thinking about strategy diversity and inclusion, carbon footprint reduction, all the other stuff that procurement has to worry about. Um, so I think I'm not, I'm not afraid that there will be no more procurement people doing procurement work anymore.

I think we're just doing a lot more value added stuff because procurement is being asked through so much more now than they were in the past. One of the other big concerns around procurement of course, is anything to do with fraud. Um, will we see more fraud in the age of AI or maybe less fraud, Less?

I think we'll see more fraud attempts for sure. Um, but I think ultimately companies that are proactive in this space will put the guardrails in place to, to make sure that they don't do the silly stuff that they're not supposed to do now anyway. And with the a with, with the, with the age of ai, I think a lot more spend will become more controlled because people could put purchase orders in place that gets approved and then you can't ex exceed that spend once a PO is exhausted.

So I think more attempts will happen, but I also think this, there's gonna be more controls put in place to ensure that fraud doesn't go out of control. Will the whole process become faster? And I'm asking the question because there's many folks who work in organizations who want to buy something and then they go to the procurement department and they're told, you know, we should be able to sort that thing out in a matter of months.

And people are like, what? Well, I think what, what I will say is that I think procurement will be faster in guiding people to channels that can execute the tasks faster, right? So the biggest problem, no, not the biggest problem, but, so one of the problems folks have today is they don't know which of the 3000 or 10,000 suppliers that's already in the system that can meet their demands, meet their needs already, right?

And usually take months to onboard a new supplier, go through the supply due diligence, their risk assessment, those kinds of things. And what we've developed a focal point is sort of say, well, I need to buy a management consulting service from this supplier. We will say, well, that's a new supplier.

We can use one of the 10 that we have approved already, and that will speed up your process by, we'll cut it from three months to two weeks. Do you wanna use the one you have? Okay, yeah, let's do that then.

Right? So I think with more intelligence comes better decision making and I think, and a better contracting as well. So I think that's gonna be the way for the future where you've tried to get folks to the right channel to use the right suppliers for the right things, and that will inherently speed up the process.

Do you think that a lot of the compliance work will get easier as well? Because I think one of the things that holds us up in procurement is that there are a few thousand regulations that people are trying to sort through. And, um, can that whole process become, uh, shall we say, less painful than it is today?

Yeah, for sure. I think we're seeing a lot of cool technology out there. So for example, reviewing a, a SOC two for control environment, for example, we've seen solutions out there now where you can upload your SOC two and they will automatically suck down the answers to the 300 service criteria that soc two handles and say, all right, yeah, this meets our needs.

This doesn't meet our need, or whatever the case may be. So I see a lot more automation, not just of suppliers filling out, you know, assessments, but also how they get reviewed internally within the organizations as well. I still think people, you know, you have to keep a human in the loop.

That's the the thing people say now, right? Uh, to make sure that your humans review it and make sure that everything is copacetic. But yeah, we've seen incredible advancements in how, how contracts are being renegotiated, how they can pull out terms and compare them side by side and make decisions about what to do next.

So there's a lot of automation to be had there. And how will this all get done? I mean, I get that there are gonna be AI agents, but are companies like yours gonna, uh, figure out which LLMs to use and give me those AI agents and how customizable are they gonna be?

Can I build my own? Do I need to expose my own data to this? How is it all gonna play out?

That's, that's an open question, right? And not only that, but who's gonna pay for it and how are you, how are you gonna pay for it, right? So we see a variety of different models.

So right now, for example, focal Point offers our agents that we have built and trained to do certain things. But if someone comes to us and say, look, I'm importing stuff from Brazil and I'm worried about tariff impacts from day to day. I want to build an agent that looks at that specifically for my parts.

Like, okay, that's probably not something that we will, you know, build for all of our customers, but they can plug in their own AI agent and on our infrastructure using their data sets and have them be executed within our solution. The only question really is like, how open will suppliers be? How, how much infrastructure can they build to support this, uh, and how will they charge for it, right?

Because you also see some organizations aren't charging for AI at all, and then you have some that have not only, not only user based, but also token based, right? So I think a lot of these pricing models are kind of funky because the price of AI keeps going down and uh, you know, do you really want to set pricing for three years for something that you know is gonna decrease for the next, you know, next two weeks, right? Like it's, it's, it's a very interesting discussion that, you know, it's kind of like a religious discussion we're having internally.

Like, how are we gonna, how are we gonna charge for this? Well, it's curious because I think if you charge extra for the so-called AI agent add-on, uh, people will use it less because suddenly they're like, well, that's more costly and that may be defeating the very purpose of having the ai. So maybe we gotta figure out how to just embed that into the base price of the software itself.

E exactly right. And it is interesting, right? 'cause if you think about something like an invoice processing flow, right?

First thing you need to do is read the invoice, then you need to decide what to do with it. And it, it's, let's say it's a PO invoice, like gets matched over here, it's a non PO invoice that go over there. So there's a lot of work that happens behind the scenes.

And if, if you do it manually, it will be probably cost like 2, 3, 4 bucks per invoice. I'm being conservative. Um, and then you can get an AI agent that can do that in a matter of seconds and it will probably cost, I don't know, let's make, let's call it 35 cents, right?

Today. There's an inherent value there of just having it be automated. You pay 10% of the overall cost you used to by using an AI agent.

So in that case scenario, like it's a wild party all around, right? But it's, it's the large language model stuff that is kind of squishy where yeah, you would probably decrease the usage. But there are some applications of this where you just kind of like on demand for specific tasks, they're gonna be automated.

And I think people will not limit their, the usage of that just because the, the values there. As you kind of think about this for a minute, um, will the, today, there's a lot of silos in our organizations and procurement is one of them, but in the age of ai, um, might all those silos either maybe disappear or maybe they'll just become a lot more porous as we go along. But are we looking at some sort of, you know, massive business process, re-engineering workflow exercise here?

I think, I think that is certainly coming, and I think a lot of that also depends on the infrastructure that folks currently have, right? So AI inherently needs data, and if you can't get access to the data through an API or data lake, it's kind of hard to actually do something with it. And we see a lot of companies that are protective of opening up their A-P-A-A-P-I layer if there is one.

But I do believe larger companies will go, go forward and start creating AI projects and so on to try to, to get as much value out of this technology as possible. And I do believe there's gonna be a lot of process re-engineering to make sure that people fully harvest the, the use of these solutions. I think it's not much of a dirty secret out there, but a lot of procurement still revolves around spreadsheets and heck even paper and pencil.

Um, will we kinda see a lot of organizations finally, you know, apply AI to procurement and maybe one of their higher priorities, or, you know, when I go talk to folks, there's a long list of AI projects. So how far and how quickly will procurement move up that stack? Um, we see bifurcation, right?

Some folks, it's interesting when we talk to some of our larger customers, uh, they're, IT departments are very reluctant to do anything. Ai, it's kind of like SaaS was 10, 15 years ago, like SaaS was really scary. You needed to have stuff behind the firewall so that people can control it.

And now AI is the same way. They say, well, if, if you need a new application that has AI embedded, we want to try to build it ourselves before we open it up to third parties. Now, that doesn't make a lot of sense to me, having been on both sides, both on the corporate side as a, and as a provider.

But I, but I see, you know, the old school folks that are reluctant, then I see the people that says, bring it on. We can't get enough of it. And I, I think, uh, this is a lot of dangers being left behind if you don't embrace it.

And I, I see a lot of companies coming to us with the ideas to say, look, we want an agent to do X, Y, Z. Can you help us with that? And I think, uh, that is, those are the customers we really like because it helps us improve, it helps us innovate and, and people are moving up that ladder fairly quickly.

So I still think we're probably five, 10 years before we see a ton of automation where it's really impacted and paradigm shifts across the industry, but it, it, it's coming. What is your best advice then for organizations about how to get ready for that? 'cause?

Um, I don't think it just magically happens in, uh, far as I can tell. It all starts with the data. So maybe I need to get my data organized.

Well, that certainly is a very good starting point. I think companies have to find religion about what is acceptable and what is not. And just like with SaaS there, you know, there has to be sort of a reckoning of value before people are ready to sort of move forward.

And a lot of folks will say, well, you can't look at my data and you can't send my data to a large language model outside of, you know, our, our firewall. But when you think about the data that actually goes across isn't, you know, we're not gonna say, this supplier is the supplier for company X, Y, Z, and you spend this much money and here's the contract. A lot of that stuff gets anonymized before it leaves to be processed.

And I think folks have to figure that out that okay, the, the, the risk is limited. You can review the prompts that are being sent out and actually control over those things. So I think the CISOs have to sort of get their arms around it, as long as you can see what the large language model prompts are and what actually gets sent out.

Okay, that's probably not so scary. And it's their job to educate the rest of the organization that with the right parameters, that might be okay. But yeah, data is certainly paramount and we see a lot of folks actually using AI to clean up their data as well, which is actually kind of interesting, uh, especially on the supplier, uh, records where sometimes you don't have full addresses, sometimes you don't have the right, uh, you know, taxpayer id, all those kinds of things.

And you can use AI to clean it up and it just becomes that much more valuable. So I, I see a lot of cool stuff, uh, in the future for this. You, you've been at this a while.

What's that one thing you kind of see organizations still doing today when it comes to procurement that just makes you shake your head and go, folks, we need to be a little bit better than that. Yeah, you know, it's, it's, it's still interesting to me to see how procurement organizations are using Excel spreadsheets to, to fill out, you know, in, uh, questionnaire. So like, I received a, a questionnaire with 600 questions, a lot of duplications, and it's all done in Excel with multiple tabs.

And it's just, you kind of slug through it and then you realize this is a $55 billion technology organization and you realize like they're not drinking their own Kool-Aid. Um, first of all, and it is just challenging to me to sort of get my arms around it and there's no appetite for change. 'cause this, this few hundred people in the procurement organization doing this, and, and this has been the process for 20 years and it probably will be for, for another 10 at least.

So we just need to stop using spreadsheets. That's terrible. It's just not a good experience.

Right. All right folks. Well, hey, one thing to think about here with AI or everybody's casting about as to where is the return on investment gonna be, we might argue that procurement is a huge opportunity to drive some value back to the organization in a way that automates a task that well nobody on either end really enjoys doing.

Hey Anders, thanks for being on the show. Thank you, sir. Enjoy the rest of your day.

And thank you all for watching the latest episode of the Techstrong AI Leadership series. You can find this episode and others on our website. We invite you to check them all out.

Until then, we'll see you next time.