EvoluteIQ On Rethinking ROI In The Age Of Enterprise AI

[00:00:04] - [Speaker 0]
What if the biggest thing slowing down AI adoption inside your business is not the technology at all, but the way you're being charged for it? On today's episode, I wanna talk about a topic that doesn't always get the spotlight it deserves. Pricing. Because, hey, let's be honest, it's hard to get excited about licensing models and procurement conversations. Nobody ever leaned over at dinner party and quietly whispered in ear, tell me about user pricing.

[00:00:35] - [Speaker 0]
But when those pricing models quietly punish success, that is a moment that things get quite interesting, not to mention expensive. And my guest today is the CEO and cofounder of Evolut IQ, and he's gonna be joining me today to unpack why so many enterprise AI and automation projects all look promising in a pilot and then suddenly become far less attractive the moment someone tries to scale them across a business. And we'll also get into why the old per bot and per user model and price per seats can create a strange situation where the better your automation works, the more painful the bill becomes. That's a tough way to win at anything. And I also wanna get into an even bigger issue that should resonate with business leaders listening today, And that is how many companies might think they have an automation problem when in reality, they have an orchestration problem.

[00:01:36] - [Speaker 0]
In other words, the issue is not whether a single tool can do a clever thing. The issue is more about whether all the moving parts across the business can actually work together without creating friction. More vendors, more cost, and more headaches for the CFO. Nobody wants that. Well, my guest will guide us through the noise, bring a clear and practical view to this conversation, and talk about why AI alone will not magically repair broken processes and why end to end process automation matters far more than shiny features, and why outcomes based pricing is starting to get serious attention in the boardroom.

[00:02:17] - [Speaker 0]
So there is gonna be a lot in this conversation for CIOs, CFOs, transformation leaders, and frankly, anyone who has ever sat in a meeting where somebody says, hey, the pilot was a success, while quietly avoiding the question of what happens next. So if you've ever wondered why so many AI projects still stall after early promise or why scaling automation can feel like stepping in onto a treadmill that changes by the minute, you should enjoy this one. So if you're ready to rethink what enterprise AI adoption should actually look like, hold that thought because I'm gonna introduce you to my guest right now. So a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do?

[00:03:09] - [Speaker 1]
Neil, thank you so much for having me on your, podcast. My name is Samid Gupta. I'm the CEO and cofounder of a company called Evolut IQ. We are a end to end, deterministic, deterministic agentic AI platform. We've been around since 2019.

[00:03:29] - [Speaker 1]
But, you know, this is life's work for me and my founding partners. We have been working on this for a for a very, very long time. Evolut IQ is based headquartered out of Stockholm in Sweden. We have global operations. We have our R and D centers out of Menlo Park in California and in Bangalore, India.

[00:03:52] - [Speaker 1]
And then we have offices in, obviously, Stockholm, in London, as well as in in New York City. As a company, we've been around, I said, for seven years, but, you know, we've been thinking about this since 2004. We sort of conceptualized Evolut IQ back then. We put pen to paper in 2007, 2008. And, you know, we've been building this in stealth for, I think, about ten years, working with some very close partners and prospective customers, getting feedback.

[00:04:27] - [Speaker 1]
And we incorporated it in 2019. And, you know, since then, it's been a fun ride. We started Evolut IQ to address a very, very simple problem, which is, you know, focusing on the process rather than parts of the process. And, you know, so we we've been around, as I've said, for now seven years since we started. We've been growing hundred, hundred plus percent on our subscription and licensing revenue since we started.

[00:04:56] - [Speaker 1]
A 120% net retention run rate for our customers across across the world. Our customer base is predominantly Fortune 500 customers. And the most important thing is, you know, we've been EBITDA positive since our second year of operations. So a very disciplined way of growing the company. You know, we have a very, very unique position and a platform that we have built, which is recognized by pretty much all the tier one analysts globally.

[00:05:30] - [Speaker 1]
So we have made it to the leadership quadrants. We have made it to, you know, the the fast growing quadrants, and we feel very privileged, you know, to have earned that that position as a company. In terms of the problem and what we solve and what Evolut IQ is all about, see, we we build the company to solve one very simple problem, which is the process. If you look at any organization in the world, you know, the the consist the reason they actually deliver consistent outcomes is because they have good or consistent processes. And for any organization to become more efficient and productive, you need to automate these processes.

[00:06:17] - [Speaker 1]
And so we when we started Evolut IQ or we conceptualized Evolut IQ rather, what we wanted to do was we wanted to build a technology that can essentially think for itself, learn by itself, solve and make decisions, and do everything that is needed between an output sorry, an input and an output that every process needs to have. And so it's essentially minimize the need for a human intervention, but have the intelligence built in where you could extract the data, you could have workflow, you could have event flow, you would have task management. So whatever that is needed in any kind of a process to get automated, that's what we built. So, you know, we hear all these words of agent take and intelligence and cognitive and artificial intelligence. I think for us, all those were, you know, table stakes.

[00:07:09] - [Speaker 1]
Because when you say that I'm going to solve the problem of the process and I'm going to do everything that is needed to ensure that the process is automated, then that's, you know, that sort of becomes the basic fundamental of the technology. And that's what what we bring to the table as EIQ.

[00:07:27] - [Speaker 0]
I love the journey that you've been on and that mission that you set out upon. Long before, everyone was talking around AI and agentic AI, and you've arrived now at the perfect moment. And you've set off my radar as well, and I was reading how you argued that the traditional per bot and per user pricing models that we've seen back in the day are actually one of the things that's holding AI adoption back. And adoption is one of the most important aspects of the success of any technology. So can you tell me a little bit more about where that model breaks down, especially in real enterprise environments that you're seeing out there?

[00:08:07] - [Speaker 1]
I think, you know, it it comes down to solving the problem rather than parts of the problem. Right? And what I mean by that is if you look at it, you know, if you take a simple KYC process in a bank, right, there are multiple things that need to happen for that entire process to be automated. I mean, when you give the documents, you need to extract the data because, you know, there are multiple approvals involved. There needs to be a workflow.

[00:08:33] - [Speaker 1]
The data that has been extracted needs to repeatedly be put into a database. You need, you know, certain approvals trigger certain events, so you need to have an event flow. While all this is flowing, you need to run some analysis to see what kind of people are doing the KYC. People need to know have reporting dashboards to see, hey, where is this process? You know, what's really happening at this point in time?

[00:08:56] - [Speaker 1]
So what I just rattled out is six, seven, eight different technologies that need to happen. And what was happening in the past was a lot of great organizations were solving one part of it. You know, there have been fantastic organizations that have just built data extraction as a tool, and they charge, you know, per per document or they charge per per bot or sorry, per seat license. Right? There have been great organizations that have built RPA tools, which essentially are just taking this extracted data and, you know, doing a simple repetitive task of putting it into a database, appending it, updating it, whatever is is, you know, that is there that they need to do.

[00:09:39] - [Speaker 1]
And that is you know, you price it on per bot. So similarly, you have a workflow tool, which is, again, you know, hey. How many people are using this? And so they are per per user or per per seat again. So multiple different technologies, multiple different licensing models.

[00:09:56] - [Speaker 1]
But all of this needs to come together for the end customer so that they can say, hey. Listen. You know, I have put these five, six different disparate technologies together, and now I have automated this process. And so now let me, you know, see how this process or how the costing of this process works. And so then they start identifying, you know, what is the spend that they have on each of these different technology.

[00:10:22] - [Speaker 1]
It's a very complicated and a very subjective model. Right? Because you're using five, six disparate technologies. All of them have somebody does a per bot, somebody does a per license sorry, per seat. It's very complicated.

[00:10:35] - [Speaker 1]
But the most important thing where this whole thing fails is the fact that when you have a per bot and a per user pricing, it works very well when you're addressing one process or maybe two processes. The minute you expand and want to do this across the organization where you have thousands of processes or, you know, you want to take it enterprise wide, the whole per bot or the per seat or per user license model completely breaks down. Because the whole ROI for that business case becomes prohibitively expensive even if you're signing up with five, six different vendors on their different licenses and enterprise licenses and all of that. And I think what therefore happens is you get these pockets of efficiencies. So people look at, you know, certain processes where, you know, they can buy these four, five different technologies, make it work, and the ROI can be defined.

[00:11:34] - [Speaker 1]
And so, you know, the while the model works, it cannot be expanded across the organization. And that's where, you know, the adoption gets stalled. And I think when we looked at, you know, pricing Evolut IQ and the EIQ licensing model, we said, you know, what are the things that are restricting an enterprise to exploit or or sort of drive automation across? And one of the things was, hey, this licensing model because all of a sudden, you know, you have the CFO getting you know, because people, once they like a technology, they start using it, you know, they they go ahead and do that. And all of a sudden, you may, you know, have an unpredictable invoice come up and, you know, demand because your user went up or your number of bots went up or, you know, those kind of things happen.

[00:12:24] - [Speaker 1]
And so the promised ROI sometimes gets reduced. Sometimes, there is no ROI at all. So there's a lot of lot of those things happening. And so adoption is very truncated. And when we put Evolut IQ, you know, when we looked at the pricing for Evolut IQ, we said we want to make it as simple, as predictable, as transparent as we can so that when people are using the system, you know, they know that, okay.

[00:12:51] - [Speaker 1]
You know what? These are the four modules or these are the four engines that I'm using. This is what I'm using for this particular process, and it's gonna cost me x. And irrespective whether five people use it, 50 people use it, or 500 people use it, you know, my cost is gonna remain constant as long as it is, you know, this particular process and this particular instance. So when so we drove it from the thing of, you know, we want to we want to move to the outcomes base.

[00:13:18] - [Speaker 1]
Right? So that's what we are doing with most of our clients. And so the whole idea was, hey. Let me focus on what is the ROI that you are looking for, and let's put that ROI down in stone and then, you know, sort of work with that and make sure that the adoption increases.

[00:13:35] - [Speaker 0]
It's so refreshing to hear you talk about ROI in this way because I think over the last twelve to eighteen months, we've seen countless examples of early adopters of AI and other emerging technologies that have struggled to find ROI on those expensive tech projects. And I've got to ask, why does success in an automation pilot often make scaling harder for a cost perspective? And how does that maybe trap organizations into what many increasingly call pilot purgatory, which I I know there's so many that that find themselves in that that space. But tell me more about that.

[00:14:11] - [Speaker 1]
You know, one of the things is, you know, everybody wants to dip their toes in before they, you know, sort of do the big bang change. Right? Yeah. And one of the things that we've seen is, to demonstrate an ROI, using any automation tool or multiple automation tools in in most cases, What ends up happening is you are looking at four, five different tech, you bring it together, and, you know, you have identified a low hanging use case because you want to show success. And, you know, you do show that success, and it kinda works.

[00:14:48] - [Speaker 1]
And then just what I said in the previous, question that you asked me. Right? What happened is when you expand that and you say, okay, you know, I tried it for a very small use case, the low hanging fruit. Everything works out. Everything checks out.

[00:15:01] - [Speaker 1]
This is great. Now let me take this and expand it to, you know, a medium to complex process. Let me expand this to a very complex process. The minute you go to that, you know, the the plethora of options opens up in terms of, hey. This is this needs to be licensed.

[00:15:19] - [Speaker 1]
This needs to happen infrastructure, all of that. And all of a sudden, the pilot which was very successful doesn't seem to be very viable in in the big end to end model or, you know, with multiple processes. And so what ends up happening is, hey, you know, this worked very well for me for this one process. Let me just expand it a little bit. And I'm making, you know, good amount of productivity.

[00:15:46] - [Speaker 1]
I'm I'm saving some money. I'm getting some efficiency. I'll just find low hanging fruits like these and keep doing it. So what happens is you may have ten, twenty processes more of, you know, pilots with a little bit extension post the pilot, but they never really go full fledged enterprise wise. I mean, very few customers, do that, but I think most customers end up with this whole, you know, vicious cycle of one pilot, then extend it a little bit, and then keep finding similar kind of processes where they can show success and then stick to that rather than, you know, really genuinely transform where you can get bigger bigger impact, bigger efficiencies, and productivity.

[00:16:30] - [Speaker 0]
And at Evolu IQ, you take a a more outcomes based approach with unlimited users and unlimited bots, and that alone feels incredibly refreshing, and I I would imagine fundamentally changes the way that enterprises think about our our eye. Is that what you're seeing and hearing there?

[00:16:49] - [Speaker 1]
Yeah. You know, Neil, when we started Evolut IQ, one of the things I wanted to be very, very conscious of was why would somebody buy from Evolut IQ. Right? I mean, you know, we we are a startup or we were a startup. We, you know, we people don't know us.

[00:17:09] - [Speaker 1]
Why why would a customer want to buy? And we said, we will only sell to Fortune 500 customers. And the reason was, hey, if you're selling to Fortune 500 customers, they have all the reasons why not to buy from you. Right? I mean, they they pretty much have access to every technology out there.

[00:17:25] - [Speaker 1]
They bought things. They understand they're fairly mature. They have mature procurement processes. They have all sorts of territorial and people issues where, you know, they have contracts and stuff. So there's all the reasons why they they don't need to buy.

[00:17:39] - [Speaker 1]
And so when we said, hey, you know, we need not only have to build a technology which is superior, we need to focus on adoption and distribution. Now how do we do that? Right? How why would somebody buy this? And we said one of the things that demonstrates our faith in our technology is when we are willing to share the risk with the customer.

[00:18:01] - [Speaker 1]
Right? When a when a when a customer says, listen, if I am to implement a platform like EIQ, I'm going to improve my EBITDA by 2%, or I'm going to save 22 hours, or I'm going to save these 46 steps in this process. Right? And these 46 process steps will amount to savings of four hours. Saving of four hours will amount to x number of dollars.

[00:18:24] - [Speaker 1]
Right? And we said, okay, you know what? We will share the risk with you because we believe in the platform. And more importantly, we want you to know that we believe in your ROI that you have made, and we want to either succeed with you and, you know, fail with you, hopefully not, but succeed with you. And I think that philosophy and thinking sort of drove that we will, you know, make it outcome based, where it gives you know, where the ROI is defined upfront, it is contracted upfront, and then, you know, we are focused and we are paid on delivery.

[00:18:59] - [Speaker 1]
So I think that's sort of what we wanted to do. The other aspect of it is when you are selling to Fortune 500 customers, especially most of them are public listed, you want the CFO and the business to have, you know, a fixed cost or a visibility into what is the forecast of the cost, what is coming. Nobody likes surprises, good or bad. And I think an outcome based thing is completely aligned to, hey, if we spend x, we are going to save this much and hence it self funds this or this is what happens. And if you're sharing that risk, you're demonstrating that, you know, we will do it together.

[00:19:38] - [Speaker 1]
So I think that's sort of how we focus on the outcomes based model. That's how we have licensed the product. That is what we are taking to market.

[00:19:47] - [Speaker 0]
And you mentioned the CFO there. And, again, I'm curious. You've mentioned a few, reasons there. But any other from a CFO's perspective that that makes outcomes based pricing easier for them to approve compared to those traditional licensing models. Anything else stand out there that that makes that that process easier?

[00:20:07] - [Speaker 1]
I think, you know, a CFO is a very, very important, what can I say, profile of buyer that we have? Right? Because, you know, automation is is not a automation and AI, especially in today's world, it is not a project or a program. It is the way business will be conducted by companies and organizations. And I think that has been accepted and, you know, that is something every organization understands today, which makes the the role of the CFO, the role of the chief risk officer, and CIO Very, very important along with the other business users and the business owner and the CEO and everybody.

[00:20:53] - [Speaker 1]
The reason is because the CFO wants to know what, you know, what is my cost, what is my exposure, what is my liability in terms of doing what I'm doing? Right? And I think one of the things we find we get a lot of support from stores is because it's the pricing for Evolut IQ platform is is very, very transparent. It is very predictable. We outline the sit with the customer and, you know, structure the baseline of where we are starting, where we have to go to.

[00:21:24] - [Speaker 1]
All everything is committed right upfront. And it's very clear if we don't get to that, what what what is the spend? If we get to that, what is the spend? And once we get to that, you know, the future of the next two years or three years is contracted and signed off. So it's a solid line of cost for the CFO and everybody likes that, especially in today's world.

[00:21:45] - [Speaker 1]
Right? So I think that's one of the reasons why I feel the CFO is super important. And it helps the CIO as well because having a a partner in the CFO who understands, you know, how you're choosing the platform and why you're choosing it and how the cost of that platform, can be structured as an OpEx or a CapEx and how does it work in the p and l. I think all those things also matter. Right?

[00:22:12] - [Speaker 0]
Really do. And I think as as enterprises also look to reduce vendor sprawl, which is something that we're seeing a lot of now, I've got to ask, what are you seeing in terms of demand for more integrated end to end automation platforms? Feels like there's a real desire for it now, and it also feels like there's a big opportunity there. But what are you seeing and hearing?

[00:22:33] - [Speaker 1]
You know, Neil, we we were born at end to end. I mean, when I said at the beginning of the of the conversation, right, that we wanted to solve the problem rather than parts of the problem. Right? And so we have always been this way. We've we've we've built the platform this way.

[00:22:51] - [Speaker 1]
We architected it this way. We priced the platform in a way that, you know, it is always addressing the problem rather than parts of the problem. And so what what we have always said is, you know, for for me, this is not a new thing where people are saying, listen, I have bought these five, six platforms. I need to consolidate it into one or two. And I we we always said, hey, if you are a retail company or if you are a bank or you're a health care company, what what is it that you really do?

[00:23:24] - [Speaker 1]
Are you building the best RPA solution or the best workflow solution? Or are you building, you know, an efficient process to, you know, for KYC? Or are you building an efficient process, you know, to distribute your, you know, your goods that you are doing as an FMCG or a retail. If if you are a business and your business is to, you know, sell food or if your business is to sell airline tickets or your business is to, you know, give mortgages and loans, then focus on that. Right?

[00:24:02] - [Speaker 1]
And to do that, you don't need to have the best RPA platform, the best, workflow tool, the best whatever. Right? I mean, there's always the argument of best of breed versus do you want to put everything in one basket. And and, you know, people have different opinions. But more and more, what I'm starting to see is, especially with Gen AI and the advent of what we are seeing in the marketplace with the adoption of AI, people are understanding that, hey, you know what?

[00:24:33] - [Speaker 1]
I want to build a technology and a platform where, you know, I I don't know why I'm paying six, seven, eight different disparate technologies and solving parts of the problem when my focus as a business is to have the most efficient process. And so instead of going to five, six, seven, eight different technologies, why don't and and, you know, get I focus on one single stack, which gives me all of this, integrates into my homegrown systems, and is, you know, got all these connectors. And that's sort of what we are seeing. I mean, one live example I have is one of our retail customers is consolidating seven different well established platforms who have been around for, I think, anywhere between, you know, ten to thirty years. They're consolidating them down to two platforms, and one of them is EIQ.

[00:25:23] - [Speaker 1]
Right? And we see this happening more and more. There is always also the debate of best of breed versus one single technology, and you will have people who vehemently believe in saying, listen, I'm not gonna put all my eggs in one basket. And that's fine too. But I think more and more, we are seeing people understanding the benefits of having that instead of, you know, the best in class or the best breed because in reality, you're not building the best RPA or the best workflow.

[00:25:54] - [Speaker 1]
You're actually building the best process for your business. And when you say best, you essentially have to ensure that, you know, it is efficient, it is productive, it is the fastest path to output, and more importantly, it is economically much more, viable than, you know, something else. So I think that understanding is sort of happening with a lot of prospects and customers that we see out there. And so we so I think, you know, we will I believe we will see more and more of this.

[00:26:28] - [Speaker 0]
And when I was doing a little research on you, I was also reading that you've said that many organizations out there don't actually have an automation problem. They actually have a orchestration problem. I love that line. But for for listeners out there, can you just tell me a little bit more about what that means in practice?

[00:26:45] - [Speaker 1]
So, you know, it's it's it's something as simple as, you know, you you build all these different I mean, an organization is a living being. Right? I mean, you're constantly building something, you're solving some problem, you're, you know, addressing some compliance, so you're building something to be compliant. So constantly, you're either building different applications or you're upgrading different applications. You're integrating to different systems internally, externally.

[00:27:15] - [Speaker 1]
At any point in time, you're doing that. And every time you you build something or you update something or you integrate something, you're essentially, you know, it's always a part of some process or something within the organization. Right? And so the truth is you need all of these different aspects of the organization's applications, tools to work in harmony so that the input and the output has the first, you know, the fastest path or the most smoothest path to execution. And I think that's where the whole orchestration comes in.

[00:27:54] - [Speaker 1]
I mean, you you if you take any organization that has been around for more than thirty, forty, fifty years, you will see or even some new organizations. Right? But you will see that, you know, it will have everything. It will have an IBM mainframe. It will have, things which people have written in, you know, visual basic.

[00:28:13] - [Speaker 1]
It will have so many different things and so many different generation of things which need to work in simple harmony. Right? And to do that, it's not just about automation, it's it's about actually about orchestration, getting all of this together to work in harmony. I mean, my simple example to this is, you know, if you have an orchestra, you know, you you can have an electric guitar and you can have a a a instrument like a sitar, which is thousand years old. Right?

[00:28:44] - [Speaker 1]
And for all of that to produce good music, you need to have an orchestrator who's sort of doing it and a conductor who's sort of managing it at the same time. Right? And I think that's what that's what most organizations miss and have realized and now putting that together.

[00:29:02] - [Speaker 0]
Love that. Such a great example. And I think anyone scrolling down their news feeds over the last few years will have noticed there's a lot of hype that surrounds AI in general. But you've suggested the real opportunity lies in the end to end process automation. So where are businesses getting this wrong today?

[00:29:21] - [Speaker 0]
Are they getting distracted by the shiny AI and shiny agentic AI tools, or or is it something else? What are they getting wrong?

[00:29:29] - [Speaker 1]
No. I don't think anybody is getting anything wrong, Neil. I think, we are going through a process of evolution. Right? I think, see, it's also a case of, what can I say?

[00:29:42] - [Speaker 1]
It's also a case of what is available. I mean, you know, thirty years ago, certain kind of technology and tools were not available. And so we would only solve one type of a problem. As I said, organizations are living beings. I mean, you know, things are happening all the time.

[00:29:57] - [Speaker 1]
And if you are an organization that has been around for a long time, you you you're always trying to solve a problem and doing it. So you're as the technology evolves, you are also trying to adopt. And, you know, the truth of the matter is any new technology will become a legacy at some point in time. Right? That's just how it works.

[00:30:16] - [Speaker 1]
And so I don't think organizations are getting anything wrong. It's just that, people never thought about doing end to end automation. Okay? They they did not think about looking at the entire process as a whole because there there wasn't a technology or there were there weren't too many technologies out there that were looking at it as a whole. I mean, giving you the Evolut IQ example, I remember back in 2019 when we started the company, myself and, one of my other founding partners, we we were at one of the largest telecom providers in the world presenting.

[00:30:57] - [Speaker 1]
And, you know, they they said, hey, we don't believe in doing an end to end automation. We will do that in 2030. You guys are trying to tell us I mean, we would rather focus on, you know, having an efficient task management tool, an efficient workflow tool, whatever. That doesn't mean that they were wrong. It's just that at that point in time, that seemed to be the right thing to do because the technology had not evolved.

[00:31:20] - [Speaker 1]
Gen Gen AI was not there. What we were trying to sell as Evolut IQ was a vision for them rather than a a technology which existed. For us, we have been talking end to end from day one since the time that we were born. For many of our peers and competitors, it is something that they have evolved to over a over the past few years. And that is because the customer has started looking at it and saying, listen, why am I paying five, six different licenses for different people?

[00:31:52] - [Speaker 1]
Why am I paying for integration? It is costing me so much money. It's so much easier now to do it with, you know, AI. It is so much more easier for me to write my own Gen AI scripts. So I think the buying pattern has changed.

[00:32:06] - [Speaker 1]
Technology has evolved. And today, the customer has become smarter where the customer is saying, listen, don't solve for the problem sorry, part of the problem. If you are gonna solve, solve for the whole problem. And I think the smarter customer is actually saying, listen, solve the whole problem and share the risk with me by pricing it based on the outcome of what you're going to solve for me. I think that's what is happening, and I think that's where the world is moving.

[00:32:34] - [Speaker 0]
And for any business leader that's listening today, trying to look for takeaways, tips, or learn more about what could be waiting on the road ahead for them, what what urgency do you see for enterprises to rethink in their approach for AI pricing, automation strategy, and all those things, and avoid risking falling behind their competitors? Anything that you'd you'd offer to anyone listening there on on what what they can expect on the road ahead and what they should be thinking about?

[00:33:04] - [Speaker 1]
I think the first thing I would tell anybody listening to this podcast or any of my customers, and I say this is, you know, just take a pause and genuinely think about what do you want AI to do for your business. I mean, you know, it's it's extremely important to understand that this is the way you will be conducting your business moving forward. How can it help you? Right? It's like that.

[00:33:31] - [Speaker 1]
I mean, I think the very important piece is, first, the the executive team and the board sort of understanding that this is what we want to do. And then spending a significant amount of time coaching the, you know, the the employees and the and the stakeholders to understand what AI can do for them. Right? Getting them to understand how it is going to impact the processes and what they can look forward to or why they need it and getting them to buy into it. Right?

[00:34:04] - [Speaker 1]
I think that is very, very important before anybody even starts looking for a technology or a tool. I think understanding what this is going to do. Then the next thing is all about, hey, you know, okay, so this is what we want to do. What is the governance that we need? What is the operating model that we want to use for implementing this?

[00:34:24] - [Speaker 1]
And how will this change our life? And I think start from there and then go into, you know, identifying what kind of a tool do you need, how is it going to automate, train your teams, and do that. I think there is just way too much noise right now in the marketplace. We see a new AI company popping up every day, with so many changes happening. There's just so much so much noise that, you know, my thing would be take a step back.

[00:34:54] - [Speaker 1]
First, understand and identify your own needs. Once you have done that, then embark on the journey of what is the best tool for me or what is the best technology for myself? How is what am I looking for? How does it work? How will I train my people?

[00:35:10] - [Speaker 1]
How will I scale with my people? I think that's the one thing I would say. I mean, you know, this this this chain this is this is not a change. This is, I would say, you know, the new way of life. Right?

[00:35:24] - [Speaker 1]
I mean, it's it's just going it's it's here. It's happening, and it will be here forever. So it is very important to be true to your business and then get a tool that adopts to your business rather than going the other way and trying to get your business to adopt to some tool and then getting confused about what's going on.

[00:35:47] - [Speaker 0]
And I think that is a powerful moment to end on. But before I let you go, for anyone listening wanting to carry on this conversation with you or your team or just find out more information about all the work that you're doing there. Where would you like me to point everyone listening?

[00:36:01] - [Speaker 1]
So, you know, Neil, the the simplest place is, you know, evolutiq.com, our website. I think we'll be very happy to you know, there's there's an email there which says collaborate@evolutiq.com. We'll be very happy to answer any questions or reach out or speak to people. And then also, you know, we are going to make a few announcements and, you know, a few good things in the next few weeks where people can leverage those as well. And, you know, we are always happy to happy to respond to any questions, queries, or share our experiences.

[00:36:35] - [Speaker 1]
You know, we'd be very happy to do that.

[00:36:38] - [Speaker 0]
Well, I will add links to everything that you mentioned, Aldo. To everyone listening to check you guys out. We covered so much there, so many big takeaways from my point of view as well from AI pricing models, why the per bot and per user model is killing adoption in many ways, how enterprises don't have an automation problem. They often have an orchestration problem, and AI doesn't fix broken processes too. The real innovation isn't AI.

[00:37:04] - [Speaker 0]
It's actually that end to end process automation. I'd invite everyone listening to let me know their experiences, their insights, having listened to you today. But more than anything, just thank you for joining me.

[00:37:15] - [Speaker 1]
Thank you, Neil. It's a pleasure. Hopefully, the weather stays the same and you get to enjoy the sun more.

[00:37:23] - [Speaker 0]
So having listened to my guest today, where does that leave you after today's conversation? For me, the big takeaway is AI adoption is still being held back by a lack of ambition. Yeah. Of course, most organizations have plenty of ambition. No shortage there.

[00:37:40] - [Speaker 0]
But what gets in the way is a gap between a promising a promising proof of concept and a model that actually works across enterprises without creating cost anxiety, vendor chaos, or internal resistance. And Sumeet made a strong case today that the pricing model matters far more than many people would like to admit Because it does shape behavior, trust, and determine whether a project ever gets beyond early applause. And I also liked his point that businesses need to stop obsessing over isolated tools and stop thinking much harder about process. If a company is still stitching together disconnected systems, teams, and workflows, and then adding AI on top, then adding AI on top can obviously sometimes feel like just putting a a very smart sat nav in a car with three wheels. Yeah.

[00:38:37] - [Speaker 0]
It looks impressive in the brochure, but you're not gonna get very far in it. I also wanna thank him for his timely reminder here for leadership teams listening. Because buying into the next wave of AI promises means that you need to take a step back sometimes and ask a simple question. What exactly do we want this technology to do for our business, for our people, for our customers? And yet, it sounds incredibly obvious, but as we all know, obvious questions are often the ones that are skipped when everybody gets excited about the latest trend.

[00:39:11] - [Speaker 0]
But if today's conversation got you thinking about pricing, orchestration, automation strategy, all that real ROI, what it looks like in an AI era, please make sure you check out the links in the show notes. Let me know your thoughts on this episode. Techtalksnetwork.com too. And have a think about whether your company is still buying too many AI tools without fixing the process underneath. So let me know your thoughts.

[00:39:40] - [Speaker 0]
Other than that, it's time for me to go now. I will return again tomorrow in your podcast feed ready to speak directly into your ears again, but hopefully, you'll join me again then. Speak with you soon. Bye for now.