AI And The Channel: Exploring The B2B Impact

Circana’s Mike Crosby talks about the impact AI is having on the channel, both as solution providers seek to deploy the technology internally and look for ways to monetize it through product and services sales to customers.

[Video Transcript]

Jennifer Follett, Executive Editor, CRN: This is Jennifer Follett with CRN, and I’m here with Mike Crosby of Circana. Mike, thanks for joining me today.

Mike Crosby, Executive Director, Circana: You bet. Always a pleasure. Thanks for having me.

Follett: No problem. We are here to talk about AI, which is a very hot topic in the channel right now. Maybe right off the top, can you give us the viewpoint from what Circana is seeing as far as what is the AI opportunity for partners? What’s sitting in front of them right now?

Crosby: Yeah, I think you have to almost look at it from a number of pieces. I think from a very high level, every opportunity is significant. I think there’s not a clear idea of really how to quantify it. But clearly there’s energy, there’s excitement around it, and I think they’re starting to understand the possibilities.

You also see a lot of businesses again looking at how do I find some kind of sustainable competitive advantage, and many see this as part and parcel to that. So they want to see what are ways that not only can I optimize my business internally to be more efficient, more effective, more productive, more profitable, but then translating that also to how do I monetize products or services or other things that’s going to help drive incremental revenue streams and margin streams across the company.

So from a higher level, general excitement, very strong. I think there’s still a lack of a real clear awareness on now how to implement. And I think what we’ve seen as is different ways and different approaches that companies are having in trying to learn and understand and test and validate. And then ultimately, I think we start to the move into the implementation, but very exciting.

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We’re also hearing again quite a bit from just the channel, collectively, on a high level of interest and just scratching the surface on use cases and really, you know, starting to think through those relative to, boy, that’s a nice opportunity both to be more efficient but also, you know, drive some nice incremental business. So early stage, but certainly very exciting.

Follett: Right. What are you hearing from the vendors, the manufacturers, as far as how big of a role do they expect the channel to play in this roll out of AI?

Crosby: I think it’s going to be pretty significant. I’ve already heard from a number of channel partners that there’s a pretty good flow of inquiries from mid-size and enterprise-level customers that are asking and inquiring about AI, the types of tools and resources, the types of configurations. So they really are leaning on the channel for advice and counsel as well as being able to provide them the effective tools and resources needed to implement some of these things.

So this is where you get a lot more of that consultative element of the channel that’s really providing guidance because it’s still so new, and I think there’s still a lack of clarity in so many ways that it’s really the sweet spot for the channel to be able to add the value like that.

Follett: So where are we as far as the adoption curve? Pretty early stages here?

Crosby: Yeah. And if you look at it kind of in the traditional, you know, bell-shaped curve relative to early adopter, maybe more of a mid-level adopter/late adopter, that ultimately where you see just kind of integrated fully into organizations. I think you’re still at a very early, early stage. It’s kind of early-middle where I think, in general and again, they’re internalizing it today.

First and foremost, how do I leverage it on my own to optimize my company’s performance? So I think those are some of those test and validate stages that are going through and understanding what that is. And I think once they have a good understanding of the ways that they can take advantage of AI and the broader technologies, then I think you’re going to see that natural evolution of how do I drive it externally and how do I figure out ways to again generate incremental revenue or margin or entanglement with our customer relative to that?

So I would say it’s still fairly early. Now, again, there are some industries that have actually been more of early adopters. If you look at it, like tech specifically, has done a very good job looking at not only from the standpoint of how do I optimize things like supply chain and forecasting. Not only the traditional things, but also how do I market, how do I target, also financially, how they can identify and be a little bit more predictive relative to how they operate their business. But you are also seeing things like in retail where retail is all about personalization and you’re going to hear more and more of that as we go relative to AI. That’s going to really be important to be able to really provide that customized kind of engagement with the consumer in many, many different ways. They are already doing it now in other ways they are targeting, they’re doing it now in the way they’re merchandising, and I think you’re going to see those things start to evolve in addition to the regular stuff that we just talked about, like supply chain and forecasting and in general operational efficiency, you’re going to start to see some collective things there.

A couple others you’re seeing some really interesting things early too is in health care, and you’re going to see this around patient monitoring. You’re going to see a lot of things around new drug discovery, which I think that’s going to be really, really exciting. So it’s going to be much more of a fast-track and a rapid prototyping as some of these medications and/or new discoveries that they’re going to have.

They’re also looking at how do they manage treatment plans and how AI can help facilitate designing custom—again, back to the personalization—treatment plans for patients and in effectiveness. So those are just some of the basic ones, but these are sector verticals that tend to lead with that. And I think they’re a little bit more agile and are going to see a faster adoption of maturity on that, on that implementation. Ones that you’re going to likely see a little bit further out are verticals or sectors that have more regulatory compliance and other things around there that they’re going to have to be a little bit more cautious.

But you look at finance and insurance, too, they’re doing a lot of things now on algorithmic trading. You’re looking at all types of, again, as these use cases come, you’re just peeling back the onion and you get a little bit deeper, a little bit deeper. And I think that awareness is happening very, very quickly, so these use cases are coming on fairly fast and fairly rapid. So, you know, there’s some, like I said earlier in the beginning when we opened, I think there’s just so much opportunity and I think it’s people just really trying to isolate how do we prioritize and how do we effectively really understand how we can benefit internally as a company, but then look externally and again, how do we make that that competitive advantage versus other people are competing with?

Follett: Can you tell yet from the solution provider perspective, using AI internally, where are they seeing the biggest, most impactful use cases for optimizing their own businesses? Is it things like helpdesk? Is it coding? You know, where are they seeing it?

Crosby: Yeah, think about even just at or early, if you look at a near term, like one to maybe three-year period and this is more of a generalization but let’s use this as an example. Think about it at a basic sense of automation where they’re going to look at what are ways that we can optimize routine kind of repetitive tasks that are there: data entry, customer service chat-botting that we see, other things that are that are able to eliminate some of those basic needs.

We’re also seeing more augmentation of AI with people like myself, the analysts, where you can leverage off AI tools that’s going to augment and integrate with what we do, and it makes us more efficient, more effective and more scalable. So those are like the early things.

You’re going to start to see more to are things like predictive maintenance. You know, if it’s a manufacturing company and they have manufacturing machinery that needs to be monitored and regulated. And if it’s trying to identify an issue before it ultimately creates a significant breakdown and a loss of productivity or higher cost or what have you. So think more basics there.

The second, maybe 2 to 3 years, maybe 3 to 5 years, let’s say, think more along the lines of like all the things I suggest around personalization, that advanced kind of level of personalization. You’re going to see a ton of the ability to really customize engagements for customers, clients, consumers, patients, all of those types of things that you’re really going to see that be embraced and be integrated more fully. Autonomous systems—now, we’ve heard about that for a little bit now, but you’re seeing smart cities, you’re seeing autonomous vehicles. You’re going to see autonomous in transportation and delivery, even down to the last mile of goods and services that are purchased. You’re going to see a lot of that the integrated in as well.

So it’s so kind of blue sky right now. But again, I think as they narrow it down, think about kind of core things that are done at a fairly simple level that can be automated and optimized very quickly. That’s the early stage. We’ll get a little bit more sophisticated, and I think as the learning comes up, I think you’re going to see a lot more use cases identified and developed and then moving forward.

You know, I did mention earlier one of the things that I’ve also been spending quite a bit of time with is with a lot of OEMs, a lot of channel partners as well. And they’re getting good level of inquiry from midsize and enterprise companies that are saying, look, I don’t know enough, as I said earlier, about this, provide some counsel and some guidance and you’re even seeing it now in the sense of as effort around development of more higher end devices that you’re going to see now in a roadmap. So it’s going to tie me in really nicely with, I think what we’ve talked about before, that we believe there’s a pretty significant PC refresh that will begin kind of mid-2024, accelerating in 2025, that’s going to be one other tailwind that’s going to help elevate ASPs and improve margins again across the board because the expectation is I’m going to need the horsepower to effectively be able to drive these things.

One other thing that I think we touched on earlier, but it’s an important designation, I think, around this recovery as we start to move toward an expansion kind of economy again, is that I think in the past we would rely on significant hiring. That’s going to be a nice add-on. Not only are we going to get refresh of existing devices, but we would get these net-new incremental employees that are going to need to have new devices deployed.

I think right now, and based on at least early indicators that we’re seeing, that unemployment number, while it’s still not going to be horrific, it’s still going to run around the 4 percent to 4.2 percent even through 2025. So as we look, I think the biggest opportunity is the refresh and the expansion with a higher-end product. And you’re likely not to see the benefit of accelerated hiring and that to contribute to the growth as much until maybe, you know, a little bit later in 2025.

Follett: What about the makeup of the solution provider? Do you see them developing an AI practice or is this more you know, I have a security practice and I have to incorporate AI into it?

Crosby: I think what’s always been a huge value is you have really keen expertise within the channel, and if there’s a way that you can still stay true to that core expertise. But again, it’s the natural evolution of how you integrate new technology, new tools and resources to make that more efficient. I think they’re always going to have that knowledge, that core knowledge, around the markets they serve or the types of solutions, but I think as you look to these, I think they’re going to lean on that. I think it’s a little bit dangerous to look at and chase the next shiny thing relative to the new technology and deviate from what really made them successful. And if it is security or if it is within health care specialization or any of those lines, how do I maintain that quality level of expertise but then integrate now the new technology into that mix that helps them help them drive it forward?

So I definitely see, though, it’s going to take some additional dedicated resources, and I definitely think it’s going to have to be, again, develop I think a key knowledge and understanding of those markets and of those businesses and best practices around how do you integrate AI, not just at the basic level, as we talked about in that early stage, but more ultimately that it becomes an AI-driven culture where AI is now integrated in strategy, decision making, all the things that operate a business kind of on a tactical level.

That’s ultimately where I think you’re seeing the finish line, where you’re going to see then you’re going to need a whole host of other experts, expertise and a range of products to be able to effectively do that. But I think that’s where it’s headed. And I think it’s not this, you know, long winding road. I think this is going to come at it at accelerated rate. And I think people that embrace it and adopt it, both channel partners from how do I integrate it into my solution offering as well as end users. I think that’s why you’re getting all the communication streams that are significantly up because they may not know a lot, but they do know that this is a game-changer, and if I’m last to the last to the to the to the chair, I may not have a chair. My business may not be able to respond as quickly, and now my competitors have an edge.

And I think that’s what everyone’s looking to understand is how do I use it internally to be better but more externally, next stage, how do I leverage it to grow my business, to entangle myself more with my customer, and how do I really leverage, you know, that power, that horsepower, that I think AI really is.

Follett: What’s the advice then to partners that are trying to figure out how to monetize AI?

Crosby: Again, I think first it’s more you do an internal focus and then an external focus. Internally I think you have to obviously increase your knowledge and understanding and awareness of what AI is, what it is not, and how does it apply within the business or business environments that you’re in, and start at the basics. Like I said earlier, early stage might be just around optimization, automation, how do I take cost out of the model, add efficiencies of effectiveness into that? But once I think there’s that clear understanding on how you’re operating your own business, then I think it makes a nice kind of transition to externally, my customers are having many of the same challenges that we’re having, and how do I leverage that knowledge and understanding on how the implementation started with us and then ultimately, how do I productize that relative to a service or product ultimately within a given market that I know and understand?

So it’s two-fold. I think it’s learning, and then it’s ultimately going to be test and validate. Then it’s going to be you designing these use cases and then look to how do I, how do I engage with my customer? But I think it’s such an exciting area and I think it’s still very misunderstood a lot of ways.

In fact, if you look, one of the things I just had this conversation earlier with a couple of people, is if you look at the consumer adoption of AI versus commercial, we’re already seeing a significant speed. B2B is certainly accelerating and understanding the dynamics of it and the benefits potentially in these use cases. There’s still a huge [segment] outside of the early adopter, within consumer, that really doesn’t understand AI. I think there’s even a little bit of a fear and concern over it relative to, you know, you’re seeing use cases where consumer is, you know, plan my travel vacation, manage my recipes. You know, they’re very, very rudimentary kind of use cases. But I think businesses already embrace that and clearly has a better understanding.

In those verticals like that I mentioned earlier, like in markets like tech, they clearly understand. One big thing, too, that I don’t think I included earlier around tech is also around software and software development: There are really ways to now fast prototype and expedite. So that’s you know time is money in every business but certainly with software and software development, if you can close that gap, lower that cost and faster to market, you know, that’s compelling for a lot of companies. So I think you’re seeing a you know, a lot of people embracing how do we be more efficient, more effective.

We’d also mentioned earlier, and I know you know, my comment around unemployment and maybe leading into 2025, I think as we go still, you’re still going to see the continued evolution that we’ve seen with technology. And what I mean by that is in many cases back in the day, a lot of financial people looked at spend on technology and it was really a cost, and it was about a cost and cost management, and what are we getting the most out of our asset. And I think during the pandemic and then post-pandemic, where you had to do more with less, I think there’s been kind of a change in just perspective relative to now seeing IT as much more investment than it cost and an understanding that the more I invest, it’s giving me higher levels of productivity and it’s giving me better return on my investment. And you’re seeing now a more willingness, I think, to invest in technology in a different way than, okay, we have to have it. Let’s buy at its cost, let’s manage the depreciation of it. Now, you see a lot of businesses really thinking ahead, going, look, if I deploy this and these types of configurations or these types of tools, what can we expect incrementally to what we’re already doing today? And it’s a big mind shift, it really is, but I think it’s there.

Follett: A lot of the channel, of course, is focused on the small businesses, maybe mid-sized businesses. Is there anything particular to those business sectors that you’re seeing as far as where will they be on the on the curve of AI adoption? Will they be a little more hesitant? Will they be jumping right in?

Crosby: I think right now and again, what we’re seeing is we’re still down teens from that IT spend perspective between small/midsize and enterprise. My belief is that we’re going to see midsize and enterprise because they’ve got the operational flexibility and the capital to be able to invest and have a longer view of ultimately where this is.

So I think you’re definitely going to see larger companies lead. They’re going to start isolated in fairly controlled environments and then look to broaden once they know and understand. Small business, I think, while the opportunity is going to be great to do more with less. I think as we’ve talked before I think the challenge is a couple of fold with small business near-term, and that’s really tied to just, again, lack of operating flexibility, still some challenges around talent and more importantly, I think near term as this kind of expansion period is expected to begin kind of mid-2024, a lot of the seed capital for their investment and spend comes from regional banks. And there’s still real concern lingering of commercial real estate of what that big exposure is. There’s like $1.5 trillion of debt that’s due to mature here by 2025, and a lot of the regional banks are significantly more invested in those areas. Why that’s important is that that ultimately could cause conflict and challenge with small businesses that are looking to gain access to funding to develop some of these. So I think small businesses likely are going to lag. When the predictability improves a little bit and economic conditions get better, I think you’re going to see the nice thing about small business is they’re so agile. They can move quickly, they can embrace things quickly, and I think they’re going to let their size be their friend, as the saying goes. But I think it’s going to take a little bit of time until I think you get a little bit more predictability in the market.

Follett: One aspect of all this that’s certainly starting to play out is the impact on the white-collar worker, right? Like the different roles that may be either dramatically changed or dramatically reduced. I know IBM, for example, has talked about replacing a large number of their non-customer-facing employees with AI products and skill sets. So how should channel partners be thinking about this within their own businesses? How is their own business makeup/complexion going to start to change as they start to incorporate AI more into their own processes?

Crosby: You know, it’s a great question and I’ve thought about this quite a bit, and it goes back to that old saying: I think is you either change or you die, being blunt. But I think it means that certain roles and certain positions and certain functions within companies ultimately will be optimized through AI adoption and those that will likely not exist. But I think this is where the opportunity is worthy: Retraining and new training and new emerging opportunities and positions that I think exist. And I think we have to look at it as there’s always going to be technology that’s going to make things faster, easier. And I think what we have to make sure of is that we’re setting a course for people obviously, to see opportunities for growth and give them opportunities for training.

But to your point, I think a lot of the more kind of core, just transactional kind of resources are likely to be early at risk. And again, it’s going to evolve. It’s going to continue to elevate more and more. And I think where businesses may want to see a faster rate of adoption or not, I think the trick will be from a competitive perspective, they may not have a choice, and it may be that I just don’t want to do it because I want to stick with my old model. And I think that’s where again, back to a point of I think you’re going to have to adapt and, you know, how do I find a way to the leverage this and reinvent my business. So I think there’s going to be a lot of that going on because a lot of the kind of transactional services, transactional products, fall within that, just that: transactional. And as we know with transactional, typically there’s not a significant amount of loyalty and you see somebody will chase the next fastest, cheapest, better thing. And I think where you have that strategic thinking around your business and where you want to take it and how do I integrate some of these leading technologies in it, you know, you’re protecting yourself is as far as the next generation of, you know, operating a business.

But it’s going to be, listen, it’s going to be interesting. There’s going to be winners. There’s going to be some losers. And I think it’s the nature, unfortunately, of technology that there is some good, certainly, that we’re expecting and planning. But there’s also going to be some challenges.

Follett: Certainly, folks in the channel are no strangers to change, right?

Crosby: No. You know what? If anybody is prepared for change. Exactly. The channel is about as resilient as you can come relative to not only identifying early where opportunities are, but also knowing and understanding what needs to be done to reinvent themselves. And I think that’s been the channel all along.

Follett: Excellent. Well, thank you so much for joining me today. Really great topic and I hope you enjoyed our time together.

Crosby: Always. I thank you and hopefully it was informative.