HITT – Strategies for Selling to AI Buyers and Driving Business Outcomes

So please join me in welcoming Sam Nelson, our vice president of CX and AI. Sam, welcome back to the Tuesday call. What’s going on, everybody? Very excited to be here.

Thank you, Cass. I will take it from As usual, everybody, we treat this kind of as a livestream. So we’ve got mister Brent Wilford and mister Michael Bayajon here in the chat. Yes.

I did that right this time. Right? We are stirring up the chat. So, folks, please, please, please be sure to put all the questions, all the commentary into the chat, and we will get right I’m gonna share my screen here.

But today, this is a really, really interesting topic, folks. Over the last couple of years, it’s like every single conversation has become about artificial intelligence. And, yeah, every single supplier has an AI story now, and every customer is asking the question. So when you go to any conference now, typically, AI is in the keynote.

And because of that, a lot of you are asking me the same question, which is simply how do I sell AI? And so that’s why I wanted to bring this up for today’s Tuesday call because I actually think that is the wrong question. Selling artificial intelligence is not actually the difficult part. The difficult part about the interaction is selling to specific AI buyers.

Because AI has not only introduced kind of this newer technology category, but it’s actually kind of changed who gets involved in technology decisions. And think about it. Like, for years, right, we knew exactly who to call. We built relationships with IT.

We spoke their language. We know their procurement. We learn how to position all these different features, integrations, you name it. But now the AI conversation might involve someone different like the CEO, the COO, HR, legal, security.

I’ve had conversations with accounting in there. Right? And so the technology is not necessarily harder, but what’s gotten difficult is the actual buying process. So today, I’m just gonna spend a lot of time talking about what’s changed, why it matters, and then how you all can kind of change that approach to become just much more strategic in the conversations.

So let’s start by framing the story.

Let’s start with what most of us grew up selling into. This is the buying journey that I would say is pretty linear. Let’s say a technical problem existed. You then evaluated solutions, procurement, kind of negotiated the pricing. The organization then made the purchase.

And there were some exceptions, but generally speaking, we knew who owned the project. And if someone needed, let’s say, new, networking equipment, IT. If they needed a phone system, IT. If they needed infrastructure, IT. Right? And our discovery questions naturally went a little deeper. Like, how many users, what locations, say current provider, any security requirements.

And we became really, really good at that motion because we repeated it thousands and thousands and thousands of times. And that sales motion, honestly, is built into this industry, and it’s built the industry. But AI just does not fit this model anymore. In fact, it’s just completely changed everything.

So when you look at an AI buying committee, this is kind of what it looks like. So check this out. Right? Like, humor me for a moment.

Everybody believes that AI belongs to them. I have been in so many conversations with so many end customers, and every single one has something to say, when it comes to an AI initiative. The CEO, Yeah. I wanna grow the company.

The COO says, hey. Efficiency. Yep. That’s what we’re all about. Finance is now involved more than ever.

Where can we save? How much is this gonna cost me? HR. How can I speed up employee onboarding?

Marketing. Hey. We wanna personalize more interactions for our customers. Customer service. Lots of automation. Security.

Don’t forget about the risk, folks. Right? Legal is like, hey. From a compliance perspective, are we good?

It, of course, is like, hey. Does it integrate with everything? So I’m not saying anyone’s wrong. I’m actually saying that every single one of these stakeholders in here is absolutely correct.

And the challenge is not convincing one particular decision maker. The challenge is helping multiple executives align around one initiative. And that is dramatically different, folks, than selling a phone system or firewall or SD WAN. Let’s be honest.

Alright? You’re not just selling the technology anymore. You’re actually helping these companies navigate through organizational change, and this involves a very, very different skill. So let me dive a little deeper into this.

You have to understand that these buyers think very, very differently. So let’s compare two totally different conversations. If I walk into an IT leader’s office and they ask about AI, they’re gonna ask questions like, can it integrate? Does it support the existing environment?

Which LLM is underneath? You might start going down this rabbit hole of, okay. Let’s talk about the data. Is it secure?

What’s what do the APIs look like? And these are all really good questions. Now if you step out and walk down the hall and go visit the COO or somebody in operations, those questions are going to look very, very different. It’s going to be things like, hey, are the employees actually gonna use this?

Are we going to eliminate repetitive work? Like, how quickly are we going to see value? What’s the ROI on this? Are our customers gonna actually notice a difference?

Right? How do we measure success here? So you’re selling to see the same technology, but from two completely different lenses, where one person with the technology buyer is evaluating architecture, but the other is actually evaluating business impact. And you can start with either one.

In fact, one may morph into another.

And so the advisers who succeed here are understanding how to tackle both conversations. And that’s what I wanna bring to light today. Because AI is actually forcing us to bridge a technical strategy with a business strategy. Now the good news, if you’re not too technical, that’s okay, because then you can start on the business strategy side.

Absolutely nothing wrong with that. Now let me go back to this, and I covered this in my last one. But one of my favorite statements is truly this. It’s customers are not buying artificial intelligence.

They’re actually buying outcomes. I want you to change it up. Right? Nobody wakes up but let’s say it’s Tuesday.

Okay. So nobody wakes up on a Tuesday morning saying, hey. You know what?

We need more artificial intelligence today. Right? I mean, hey. If you do, you do you boo.

But look, not everyone is saying that. Right? So instead, they’re saying things like, hey. Our our customer satisfaction is declining, or maybe, like, our employees are overwhelmed, we can’t hire fast enough, or the costs are going up, or these these processes are taking way too long.

Well, AI just becomes one possible solution. This is a really important distinction because if we lead with AI, we’re selling technology. However, if we lead with outcomes, we’re actually solving business problems. And that’s where you as advisers become much more valuable.

If you can nail this down, gold. So let me kinda walk you through a simple project. Let’s imagine one. Alright?

So let’s say an organization wants to introduce, let’s take an AI assistant for employees, for example. It seems pretty straightforward. Right? But success means something completely different depending on who is sitting in the room.

So just imagine goodness gracious. I would hope that you would have every single leader listed on here in one room because it would just suck all the air out of it. Right? And that would be a mess.

However, just imagine you’re all sitting at this huge round table.

And the CEO, they’re saying, hey. You know what? We want, you know, customer loyalty. I want people coming back, reduced churn.

Right? That’s a big thing for us. We want growth. The CFO is like, look. I want measurable ROI, efficiency.

I’m sorry. The the CFO wants, yeah, measurable ROI. The COO wants operational efficiency. Hr, for example, wants employee adoption, reduce any turnover, security, governance, IT, seamless integration, like, name it.

And look. It’s the exact same project, but every single executive is going to measure success very, very differently. And that’s why discovery has just become significantly more important than the demos, folks. Because if you do not know what’s super important to every single one of these, then you’re wasting your time with a demo that may not be even relevant to them.

So before you start recommending technology, you have to understand what success truly looks like for each person involved. And it does not need to be technical folks. Find out what’s important to these leaders and then hone in on how the technology fits into that story. Now talk about big mistakes.

So this is probably the biggest coaching point I can leave everyone with today. Too many AI conversations start with these things. Which AI platform are you using? Which chatbot do you want?

Which model? Which vendor? How accurate is it? How many languages do you support? It’s like, look.

These are not bad questions, but they’re just really premature. Instead, start higher. So ask questions like, look. Where do employees waste their time, or where are they spending the most time?

Where do customers get frustrated? What repetitive work is out there? What information is really difficult to find? What processes are creating bottlenecks for you?

These types of questions are going to uncover real opportunities because the technology is gonna come later. Right? The best advisors selling artificial intelligence today are not rushing towards products. Now I know.

Trust me. I am a very impatient person, and I suspect many of you all are. As salespeople, we want the deals to close faster. Right?

But stay in discovery longer because the more that you can uncover, the stronger your opportunity is going to be to get them to close amongst the AI world. So I wanna point out a a really interesting misconception. One of the biggest in our industry right now is that AI creates AI revenue.

Like, we’re gonna put AI here, and there’s gonna be a ton of revenue as a result of implementing it. No. No. No. Alright. That’s actually rarely what happens. So what AI does is it becomes I want you to think of AI becoming more of a catalyst.

So the conversation starts with AI. But then the customers realize they need something else. They might need better networking. They might need identity management or a cybersecurity plan or better cloud infrastructure or knowledge management, managed services, governance, professional services, you name it.

But the beauty here is that AI touches every part of the technology stack, which is why you all are so, so well positioned because very few organizations have someone capable of connecting all of the dots. See what I’m saying here? So, essentially, AI is exposing different parts of the organization from a technology standpoint. And, folks, this is what you do.

So let me give you a really simple example. Okay? So I’m a put this one out. So manufacturing company reached out because they they wanted a, quote, unquote, AI chatbot, and that was literally the request.

So, quote, unquote, we think we need artificial intelligence. And upfront, you’re like, cool. This sounds like a chatbot project. No big deal. But before we jump into any demos, we ask things like, hey. What do you want the chatbot to do?

And they said, well, our employees spend too much time looking for information. This was really interesting. So we went a little deeper. Where is the information? And it turns out it lived in multiple places, like over six different places. Some of these documents were on SharePoint, some were in Teams, some were on another server, some lived inside an ERP system.

And in fact, some of it wasn’t even documented at all. They were like, yeah, they live in, like, you know, the employee’s brains. Like, for example, Brent and Mikey B. I don’t know where they store all this information, but they’ve got a separate, like, server internally.

Right? Or the yeah. There you go. In the coffee. I love it. Right? So suddenly, this was not an AI problem.

It was actually a knowledge management problem because we we kept the conversation going. And then, of course, security over here is like, hey. Like, sensitive engineering documents could be exposed. Right?

And so IT also came in and was like, hey. How, would AI authenticate employees to get access to this documentation? Operations was like, oh, by the way, the documentation is super outdated, guys. We have to update it.

And then leadership over here was like, oh, we need governments. Like, who’s allowed to, to to publish new information? And so by the end of the project, this was really interesting, is it started with data cleanup, then it went to knowledge management, then it went to access management, security controls, then it went to professional services, and then it went to training. And, yeah, eventually, it came to an AI assistant.

So ironically, the AI software represented kind of one of the smaller investments at the end of the day. But here’s the thing. Everything else that happened in this deal is what made the project successful, and that is the opportunity that you should be looking for. So I think the adviser playbook has completely changed, and this is it.

It’s technology used to come first, and now it comes so much later. Like, you have to consider all of these stages very, very differently. Everything from discovery to executive alignment to AI readiness, the road map, the selection, the implementation, the optimization.

Look. If you can guide customers through those early stages, the technology, folks, is going to sell itself. Customers are not looking for product experts. They’re actually looking for you.

They’re looking for this for these technology advisors who can actually help them make sense of this crazy landscape that we live in. I cannot turn on the news every morning and avoid artificial intelligence. It comes up, whether it’s in the small ticker at the bottom or it’s a story that someone has about something. It’s unavoidable.

So companies are truly looking for all of you to come in and help them make sense of this. I’ve said it before, folks, but here’s the thing.

Nobody knows, which is actually a good thing because you can be there to help guide them. You are the experts here. You have every right to go in and say, hey. Here’s where I think it’s going.

Here’s what we’ve done in the past. Here’s how we navigate this. So let’s talk about maybe some better questions that are kind of creating more opportunities. And I mentioned a few of these.

Right? It’s, hey. What’s slowing people down? Where do customers experience delays? Because instead of asking, hey.

Are you looking at artificial intelligence? You’re actually going to put yourself into sort of this rabbit hole where you start going into the technicalities. And if you, in fact, approach an AI I don’t wanna say an AI nerd, but someone who is an AI enthusiast, you can go way down that rabbit hole, and you start talking about LLMs and all of this crazy stuff. What’s happening here?

What’s happening there? Folks, that is all a distraction. Again, it is a distraction. You have to be able to guide your customer into these particular questions because they will go down a rabbit hole that they don’t even realize they’re traveling down.

So ask things like, hey. Where is work happening manually? Right? Or, like, look. If you have AI now, who owns that internally?

Figure out whose plate it’s on. How do you measure success here? What business outcomes matter most to you in the next six to twelve months? And I will tell you that one question at the end around the business outcomes, a lot of people pause because they don’t actually think about what they’re looking to achieve with technology over time.

I’m telling you, just the other day, I was talking to someone who was an enthusiast, and I kept trying to cut him off to say, yeah. But what are you looking to do? What is the output? Define what the output looks like.

And it took us thirty minutes to get there. Right?

So the last thing, like, notice something. None of these questions really mention technology with the exception of, hey. Who might own it internally? They’re primarily business questions. And what these do is they create sort of these executive conversations, and then those become much larger opportunities. So let’s talk about your advantage because I really wanna hit home on this. Is why are you all positioned very uniquely right now?

Because very few people can bring these three things together. It’s the business understanding. It’s the ecosystem knowledge. And then, of course, the trusted relationship.

Now think about your competition. Right? General consultants, they often understand the business. Vendors or suppliers, they understand the products.

The customers usually understand their their own kind of operations, but you can actually connect all three. And this is incredibly valuable in the world we live in today when it comes to AI because organizations do not need another AI expert. They need someone who can actually help them make really good technology decisions.

So, again, when we look at just kind of AI creating more than just AI revenue. Right? I really want everyone to stop measuring AI by the AI software by itself. Measure everything that AI actually unlocks.

Things like cloud, networking, security, professional services, or even things like automation or or knowledge management or infrastructure or even, folks, governance. But security is a big, big deal right now. If your customer spends one dollar on AI software, but ten dollars modernizing the surrounding environment, that’s an AI opportunity. Right?

Some of the largest projects we’re seeing today start with a very, very simple sentence, which is we are looking into AI.

Great. So AI is not replacing your existing conversations with them. It’s actually expanding the conversation. So I kinda wanna leave you with this final thought. Okay?

So selling AI, again, it’s not hard. And there are incredible technologies in our ecosystem. Great suppliers. You’ve been hearing about them for weeks, if not years.

Right? Great platforms. Really spot on fantastic demos. But what’s difficult is helping these organizations navigate change.

It’s helping all of these different executives align with each other and helping the departments work together. My favorite analogy is think of think of Thanksgiving dinner where mom is mom or dad or whoever is not the only one creating all the dishes. Imagine ten people in a small kitchen creating a different dish for Thanksgiving, and everybody’s dish needs to come out fresh, warm, hot by six PM on the same day. Now it sounds like a nightmare, folks, but it is what it is.

So you have to help customers really define success, right, before going there and choosing the technology itself. And the advisers who win kind of over the next five years won’t necessarily know the most about artificial intelligence, if I’m being completely honest and looking in my crystal ball. They’ll be the ones who ask the best questions. They’re the ones who understand the business outcomes, how to get there, who, to build executive relationships with, who connect the technology to real strategy, and they’re the ones who become sort of these trusted guides through one of these kind of biggest technology transformations we’ve seen in decades, right, as you put it.

So as we wrap, I want you to remember kind of just four ideas. Right?

One, AI has changed the buying committee the the buying committee completely, not just the technology. Business outcomes matter more than the technical features.

Every AI conversation expands into multiple technology opportunities. In other words, it’s a horizontal sale across the business folks. And the last thing is your greatest value as a technology adviser today is not actually selling artificial intelligence. It’s helping customers navigate it. Alright? So with all that said, I hope this gives you a very, very different perspective on the opportunity in front of us.