娇色导航

Welcome to 娇色导航leadership live. I'm Lee Rennick, VP Tech Evangelist for IDC, and I'm thrilled and honored today to have Meredith Whalen, Chief Research and Data Officer at IDC joining me today. Thanks so much for joining me.

Meredith, maybe you can just introduce yourself and tell our audience a little bit about your role.

Sure and great to be here with you. Lee. So as Chief Research and Data Officer for IDC, I oversee all of our research and data development and our vast global team of analysts who create all that amazing

now I'm gonna we have a question here, but I'm going to go back to our conversation we had in August at 娇色导航100 we were talking, we had an interview about AI, and you had also presented some of your research.

And it was really talking about 2025 being the year of AI adoption across the enterprise. So there have been a lot of there has been a lot of adoption and a lot of development in the AI space in in 2025 so far.

Where do you think now the enterprises are at with their AI adoption across the organization? Yeah.

So Lee, when we were speaking last summer, organizations were kind of stuck, if you remember, you know, they were doing a lot of experimentation with their Gen AI proof of concepts, but they weren't having as much success moving them into production.

And so since then, we have developed a five stage maturity model at looking at what does it take to move from that experimentation phase into becoming that enterprise, AI fueled organization.

And so with that, we've just completed a whole benchmark study, a global benchmark study over 1500 organizations, and measuring where they are along those five stages.

So the big reveal is that we see that 51% of organizations are at stage two, which we're really calling the AI pivot, right?

So they've moved from that experimentation phase, they've now moved, they've pivoted into this stage where they're starting to be able to identify those use cases up front and be able to move them into production. Now it's still very opportunistic, so there's still work to be done, right?

And when we talked last year, that was that certainly that was the way your research was going.

So now obviously you've you definitely are like you have that as part of our overall understanding of where the market is at but, you know, we were just talking to Rito about all the different industries, certainly in my work, talking with CIOs, I think last year, you and I talked about this, more of it was being used for sort of customer service aspect of, you know, genai, maybe.

And then it really seems to be evolving, especially the last half of last year, last quarter. So are there any industries specifically where you're seeing some differences? Yeah, absolutely.

So in the benchmark study, we actually targeted the study by industry so that we could compare and contrast.

And so what we've seen is that some of the leading industries, and the ways you can kind of think about them, is we've seen media and entertainment and retail as being earlier adopters. And if you think about why is that?

Well, because they are reacting to consumers, and consumers now are using these tools, and they have new expectations. You know, whether it's shopping, whether it's planning a trip, whether it's how they're being entertained, and so they're looking for their providers to change as well.

Then the second group you have is you have all the tech companies, right? Obviously, this big opportunity for the technology industry, they're consuming their own technology. They're getting productivity gains in their organization.

And then the third group of industries you have are industries that are really going to be disrupted by this technology.

So think about all the knowledge worker intensive industries like professional services, even in the financial services area, like investment banking, you think about all the knowledge workers in there, and so they are getting ahead of this so that they can start to redefine the industry value that they're going to be providing in an AI world.

Yeah, that's really

interesting, because we're seeing a lot of banks in Canada doing, like, partnerships with various AI startups to advance this idea of how they're doing their analytics around investment, but also how they're doing their customer service.

So it's not just staying in the customer service side now, it's branching into, you know, the analysis and those types of things so on that then are there any lessons that you know we can learn from those enterprises that are moving it forward faster and maybe being more intentional about it and having a strategy or a plan.

I was just talking to Genevieve, our CEO, about how, you know, that ecosystem, or that partnership with, you know, maybe someone like IDC, with the vendor, with other businesses, really helps accelerate Is that what you're finding? Yeah,

so what's great about the benchmark study is that what we can do is we can start to segment those that are further ahead, and we can study them, and we can say, what are they doing different than the rest of them?

And so there's really three findings we had, and really three things that executives need to get right when they're in this AI pivot to try to move forward.

And so one is, just as you said, they need to have an enterprise wide AI strategy, because it all starts with the strategy. The strategy. Strategy defines what you're going to invest in and what you're not going to invest in, okay?

And so it also gives them focus, okay? And to do that really from a top down, instead of an opportunistic way of looking at your use cases. So that's one of them. The second one is getting your workforce ready for AI.

And so we see a disconnect today where, you know, you see a lot of quotes from executives talking about all the productivity gains they're getting and all the jobs they'll be able to eliminate in the future.

Well, you've got to also start to put in place a communication plan that explains to the organization, this is where we're investing.

This is how the work is going to be different, and these are the new skills we need you to develop, and this will lead to career success going forward. And we we're not seeing that with a lot of organizations. That's really needs to take place.

And then the third one is really prepping the tech stack. The tech stack is going to be significantly transformed, especially in light of agentic workflows.

And so we see organizations investing now in areas like infrastructure, in their security and in their application space, in order to get ready for the future state here of the technology, the tech stack, that's interesting.

Can I ask one more question? Then, around that? Just around data, because some of the conversations I'm having that I had last year are very different than I'm having this year. Around data. I think many of the CIOs I speak with have really evolved.

They've had to evolve that data strategy, the purpose of their data. They're not really talking about the edge to cloud, complete computing, but they're talking more about, where are we going to host our data, and how is it so that's most effective for us.

Do you think that that's been sort of that maturity thing going into adoption of AI?

Yeah, I would agree. In fact, I think what they're the ones who are figuring this out is they're getting focused, right? So we know, like, everybody's data is a mess, right?

You know, it's not all going to be solved, but when you start to get that enterprise strategy that says we're going to focus on maybe supply chain transformation, then you start identifying those use cases, then you can start to say, Well, what data do we need to support those use cases?

And now you're not trying to boil the ocean there. Wow, fantastic.

I appreciate those insights. So just wondering if you can share any research highlights for, you know, the next few months and into the rest of the year. Yeah. So absolutely.

So, as you were saying, you know, industry is really important, and we think going to be an important differentiator going forward. So what you're going to see is that, you know, last year, when we talked it was a lot of focus on the functional use cases.

And a lot of those capabilities will be added into, like, your enterprise applications. And so organizations will have to adopt that just to, you know, be best in class in, you know, HR and finance, but it's not going to necessarily create a competitive differentiation in the future.

And so the industry specific use cases are where enterprises will be able to create unique value. They'll be able to innovate, drive greater retention, greater revenue streams. And so we expect to see more and more focus on that.

So to support the industry, we've just come out with our industry specific use case adoption study, where we've gone out to over 3000 organizations by 21 industries and ask them for the industry specific use cases. Which ones are you are using?

Which ones are you planning to invest in in the next 12 months? So we're releasing that as well this month. And then the second thing is economic uncertainty. Okay, so we have tariffs, tariff news on a regular basis.

So at IDC, we have our black book product, our black book product looks and forecasts all of IT spending around the world, all different categories. And so every month, we come up with an update on that.

And we also have been doing a baseline scenario, a downside scenario, and then an upside scenario. So we are monitoring this, and as new information comes in about tariffs and the impact on the economy, we're factoring that into our forecast as well. Wow.

That's what an exciting time for IDC and for the work that we're doing, and just being able to share that, you know, with the various consumers, whether it's a vendor or a tech buyer, a CIO, you know, to be able to share that so they can sort of learn, and we can learn with them as well, too.

Fantastic. It's

really an exciting time. I mean, there's a lot of change coming, but that's when we are best partners with our customers. Is helping them guide navigate through that change. Fantastic.

Meredith, as always, thank you so much for being on the show. I really appreciate it. Thanks. Really enjoyed it.