AI Fluency Over AI Tools: Kristie Grinnell on Transforming TD SYNNEX

0:00Everybody's got access to AI, so how do we really reimagine how we use AI in order to get ourselves differentiated in the marketplace?

0:09Peter High: Welcome to Technovation. I'm Peter High, president of Metastrategy. My guest today is Kristie Grinnell. Kristie is the executive vice president and chief information officer of TD Cynics, a leading global distributor and solutions aggregator for the technology ecosystem that earned more than$62 billion in revenue in 2025. She leads the company's strategic initiatives, digital transformation, and AI integration. Prior to joining TD Cynics, Christy served as Chief Information Officer of DXC Technology and as Global Chief Information Officer and Chief Supply Chain Officer of General Dynamics Information Technology.

0:42Peter High: In this conversation, we'll explore why Christy believes AI is not simply a technology initiative, but an opportunity to operate the entire business differently. We'll also discuss her vision for Intelligent IT, TD Cynics' enterprise-wide AI fluency program and the rise of citizen agent builders, among other topics. Christy, welcome back to Tech Innovation. It's great to speak with you today. Thank you so much for having me, Peter. It's great to be back. Today's episode is brought to you by Tynes 3B. Organizations are pushing teams to move faster with AI. That's creating a wave of AI-generated code and unsanctioned automations, leading to rising costs, security risks, and huge IT burdens.

1:19Peter High: Meet Tynes 3B, a single, secure environment that enables employees to build with AI while giving IT and security complete control to run and govern that work. 3B enables effortless building. Describe what you need in plain English and 3B builds a fully functioning workflow. It uses IT authorized connectors, meaning credentials, state protected, and non-technical teams can innovate without taking on unseen risk. Also, with full visibility across every workflow, IT gets total governance, while features like auto-tune and auto-fix ensure workflows improve and self-heal continuously over time. Employees get the freedom to build while IT gets the control to govern.

1:56Peter High: No shadow AI, no data leaks. Tynes 3B moves IT and security from blockers to enablers, giving teams the speed to innovate without compromising control. Visit the Tynes website at tynes.com. That's T-I-N-E-S.com to learn more and try 3B for yourself. And now on to the interview. Oh, it's always a pleasure to speak with you. Well, I thought we'd begin with the company that you help lead, TD Cinex, to some certainly known, but to others, maybe a little bit esoteric. And I would love to have you fill in the gaps for everyone as to the business that you're in, if you would. Yeah, absolutely. I'm so glad to, because we're probably one of the biggest companies you've never heard about.

2:36So TD Cinex, we're a global technology distributor. And what that means is that we get technology into those hands that need it. And we do that around the globe and we work with vendors, specifically OEMs, to get their hardware all the way up the technology stack to software and make sure that we get that into a reseller who gets it into the customer's hands. So we're a big part of the technology supply chain.

3:06Peter High: Excellent. And for a little less than two years now, you have been the executive vice president and chief information officer. And you can certainly relate to this having held the role several times. No two CIO roles are exactly the same. What's within your purview in this context? Yeah, they're never the same for sure. And that's, you know, largely based on what the company does and how they're structured and what they need from you. Here at TD Cynics, I am responsible for being the executive sponsor of our AI fluency strategy. And I'm sure we'll talk quite a bit about that. But also all of our IT operations for our coworkers?

3:43How do I make sure that they have the technology in their hands in order to do their jobs every day? And then also from a digital perspective, making sure that we are integrating with our resellers and our vendors in a digital way to make sure that we are bringing the future of distribution to a digital landscape. So, you know, an exciting wider aperture of what I'm doing here and loving the challenge.

4:13Peter High: That's fantastic. I would love to talk to you about the AI fluency strategy. But before we do, I know from our past conversations, you've emphasized that AI is not fundamentally a technology initiative. And in fact, those organizations that believe it's such actually take some risk in framing it that way. Talk a bit about your own perspective on that and the kind of counterpoint to perhaps some of that inherited wisdom that a lot of people are using. Yeah. I mean, when I look at AI, It's a great technology. It's new and you're automating with intelligence and fantastic. But the hardest part of this has nothing to do with the technology.

4:51It is absolutely a change management piece that we're getting to. And what I mean by that is that it's not just opening up people's minds to use it, although that is a piece of this. There's fear in using AI. I don't want to take away my job or my co-worker's job. and I don't want to do something that might put our company at risk. So you got to take away that fear. But the change management side of this is really about open up your mindset so that you can reimagine what can you do with AI. And that is something that, you know, typically, you know, you have a phone. Can you get along without it?

5:30Sure. But like it kind of sells itself. With AI, you're like, oh, I don't know. Like what does work look like without with AI? And I don't know if I can push myself that far to be thinking about new ways of making decisions, new ways of doing work, new ways of operating your business model, new ways of making decisions that you haven't done before. So I think it's a really exciting change management problem, not really a new technology problem.

5:57Peter High: Yeah. And I want to double click on a point you made there. A lot of organizations are using AI to make existing processes faster, but you're challenging your teams to reimagine those processes, as you know. And I wonder, how do you determine whether a workflow should be improved, redesigned, or even eliminated, as the case may be? Yeah. So when we think about the processes that we're looking at, you know, I go back to the analogy of, you know, when the car was invented, the original ask was, we need a faster horse, right? You wanted a faster way to get from point A to point B. And somebody was like, we need a faster horse.

6:32And somebody's like, I have a better idea. How about we do a car, right? So I actually use that analogy. And I'm like, hey, like when we think about this process, do we need just a faster horse? And that might be OK. And you can make that process more efficient. Do we need a car? OK, we need to reimagine that like somewhat like let's think about it end to end and what that looks like and what we can do with automation intelligence. or do we need even a rocket ship at this point? Which is mean we need to just rethink the entire way of looking at this, where we're saying this is something new and different and in ways of working.

7:07And for us at TD Cynics, that's about where do we really differentiate ourselves, right? When you're thinking about re-imagination, you need to be in an industry that moves as fast as the technology supply chain does. if we don't have what the customer needs, if we can't get it to them fast enough, if we can't get the quantities that they need at the price that they want fast enough, they're just going to go and turn and go to the next guy, right? So we have to be able to find a way to differentiate ourselves that it's not just about faster, quicker, cheaper, although those always mean something, but how do they know that they truly have a partner that is worth sticking with for the long run that nobody else can just go buy?

7:51Nobody else can just do off the shelf. Everybody's got access to AI. So how do we really reimagine how we use AI in order to get ourselves differentiated in the marketplace? And that's something that, you know, AI is at everybody's fingertips, whether it's, you know, my kids in college or, you know, the kids in the elementary school or, you know, all of our business coworkers. Everybody has access to it. But now it's a matter of what we do with it.

8:21Peter High: That's fascinating. I'm also fascinated by your AI fluency strategy. Let's cover that now, if you would. Talk a bit about, I love the word fluency as the key point there. Describe what you mean by that and also how you gauge progress towards that end. Yeah. So we purposely call it AI fluency and not just an AI strategy because we are truly thinking about getting our company future ready. And we believe future ready means that everybody needs to speak AI. If you don't, you will be left behind. And that's, you know, other companies that are working with us, we know that they're all using AI. Other, you know, vendors and resellers and customers, all of our partners, they're using AI.

9:03So if we are not prepared ourselves, we're going to be left behind. So that means every coworker at TD Cynics needs to have the same fluency, much like you would learn another language, Spanish or German or whatever the case may be, you need to think about there's a basic intermediate and basic level of fluency of, you know, knowing my name is and, you know, where is this, you know, and, you know, sometimes I like to say like, another beer, please, right? So like, how do you say the basics in that new language? And then there's the intermediacy of it, right? That, you know, you're advanced and you want to get directions and you want to be having, casual conversation.

9:43And then there's the advanced where you're having deep technical conversations in a language that's not native to you, but you're able to keep up and really have a different conversation than you normally would. And that's how we view AI fluency. Everybody needs to speak that language and everybody needs to do that so that AI is at the forefront of what we do. So if we all speak that language, then we all know that we're getting a good outcome from AI, how to use AI, how to think about better decision making, how to think about new operating models, how to think about new business structures, all of those things that can truly reimagine how TD Cynics does business and differentiate us in the market.

10:25Peter High: And you've noted to me that every member of TD Cinex's executive leadership team has been asked to develop a plan for applying AI with their organization as well. Really interesting sort of consequence of increasing the level of fluency. Talk a bit about some of what you can, at least, about that application and the value you're beginning to derive as a result of that. Yeah, so our AI fluency, like just to step back for one second, when we think about it, we're doing it across the skill set, the tool set and the mindset. of all of our coworkers. That means we need to give them the skills, not just of the technology skills and how to use it, but how your data is ready, how your process is ready, how to think about how to use it.

11:06Then we give them the tool set. Okay, you do need to know how to use these tools and here's everything we're giving you access to from a no-code, low-code, pro-code way. And then we're giving them the mindset training, right? Thinking about how to think about it, those change management pieces, but also how to reimagine process and how to think about your team differently. And so each ELT member came at it from that place. How do I create the skill set, tool set, and mindset within my region's strategy of where we need to go in order to drive AI fluency in our workplace and in order to transact and interact differently with our partners?

11:46and doing so, what was really great is every ELT member eagerly came back with this is where I want to go and what I want to do and using our fluency levels and things like that. But also, they came back with some core areas that they believed were going to be high impact to the business. So thinking about things like, where is it that I have a lot of people doing manual things today that if I could automate those or use artificial intelligence in some way, that I can then turn them to focus on more value-added work, interacting with the customer more, creating a better relationship with the vendor, understanding the market needs more, whatever that might be.

12:30Or areas where it's really costly to get something out. So how could we reduce that cost to get it out by using agentic ways of working. Or third is looking at ways of getting faster throughput, because this is all about how fast you can get technology through the supply chain. So anything that could create that speed for us becomes something that could create a differentiation in the marketplace. And so as they started, each ELT member started talking about what they were doing, we started to see those commonalities come at it. So then we could say, oh, okay, and what areas are those across the business?

13:09And even though we have four regions that operate very different maturity levels, just because of the regions they are, some are growing and some are very mature, we still found really five core global themes that they're going after. And those five core global themes are things that, you know, by creating an AI factory that we're setting up so that things can become repeatable, if one region can do it for themselves, then all of a sudden we can reuse that and scale it faster across the company. So things like credit, things like customer support, things like quoting, pricing, you know, all of those things that really help to move our supply chain and provide that support that TD Cynics is known for are things that we really want to focus on.

13:56Peter High: Fascinating. Great framing there, Christy. Thank you. And I love this skill set, tool set, mindset. When you got to mindset, you mentioned we provide mindset training. And I wonder, is there anything you can share in terms of what's worked well in providing or changing those mindsets in the way that you've described? Yeah. So we're approaching it really in two different ways. One is we're using the traditional change management methodology of ADCAR, right? Making sure that people are aware and then have the desire and the knowledge and all of those things as they begin to drive the change of we need to be AI fluent and we otherwise would be left behind.

14:34So that's the traditional way of doing change management. And we're making sure that everybody understands that. And we have change management plans in every one of our regions and our functions, and we're driving that. But the change management piece of the mindset is the harder part. And so that's where we're really thinking about reimagining workshops. And so So we're starting this with looking at different levels in the way that we're working. So as an example, when you go to any random coworker who's never used AI before, you can't imagine them to start reimagining processes and how they're going to work.

15:10But what you can do is get them using AI in their own personal productivity and saying, look, if you would use this at home in order to create your meal plan or your workouts or whatever you like to use it for, then think about some areas like that that you could use it at work and build that personal productivity that you have in your own job. And let's just experiment and let's get used to it and think about ways of working with AI as your assistant. Great. Everybody says, okay, I can do that. I'd love an assistant. Most people wouldn't turn down having an assistant. It helps them out. So then you start going, okay, great.

15:45So that's for the everyday common worker who just needs to become part of this. But then we had special change management ways of working for our leaders because we do believe that AI fluency starts at the top. And the best way to do that, number one, is to ensure that every AI leader was making it safe for people to explore with AI. We want you to practice. We want you to get your hands on it. We want you to be creative and see what you can do to change your work and become more productive. So giving them that safe place to work. The second thing was leading by example. We need you leaders to do this yourself and show everybody else that you're using it.

16:26So one of the best things I saw is that during one of our town halls, our CEO was up there with our four regional presidents and he was asking them all questions about our growth plans and things like that. And one of our presidents, he stood back and said, wait a second, let me ask my co-pilot, right? And he went to his co-pilot. He just showed the entire company that he is using co-pilot to help him, you know, challenge his strategies, come up with ideas that he can make better and own. And that's what we're requiring of all of our leaders, right? And so we actually created a leader's playbook with a 30-day challenge for them to go out and really demonstrate this to their teams.

17:10Whereas an example, I myself, I have AI moments on my weekly staff calls where who wants to talk about something cool they did with AI this week so that we can talk about it, share it, and then possibly reuse it or use it, have other employees use it as well. And it's things like that that we're doing that are really starting to change that mindset. So it's really, you know, having people be aware that having that desire and that knowledge with that safe place to work, but then based on who you are, giving them very specific skills and training and ways of working. And then for the process itself, we actually created workshops where our HR team and some consultancies that we used, as well as our IT team, came together and created a workshop to really help reimagine processes that we have in place so that we can think about, do you need a rocket?

18:08Do you need a car or do you need a horse in what we're doing? And as we think about that, you know, it's like, what are your pains? Like we put those pains up on the board first thing, and then what are the gains that we could get from it? So we're thinking about what are the outcomes as well as the issues that we're trying to solve. And giving this template to them to use really starts to spark the imagination, but also give them a framework within to drive that change. So we're expecting, you know, we're getting, you know, little pieces here and there that are really starting to get some momentum.

18:42And I think it's going to be the snowball effect, right, that as it goes down the mountain, it's just growing, growing, growing. So it's exciting.

18:48Peter High: Yeah, very exciting indeed. Thank you for sharing that, Christy. You've also described a goal of creating what you refer to as intelligent IT. And I wonder if you could describe what you mean by that and some of the work that aligns with that. Yeah. So that's, you know, every ELT member had to come back with their own strategy of how they were going to use AI in the organization. And I am no exception to that. I had to do it. And so my strategy, we've now labeled intelligent IT. And the idea is how do we drive from a traditional IT shop where you have your infrastructure and you have your cyber and you have your operations and your applications and all of those things to an AI driven workshop, meaning that we are intelligent.

19:28We are not just sitting here waiting to partner with the business on things that they might need, but we're actually becoming much more intelligent and proactive in understanding where we can help the business in order to continue to grow. So an example, we're doing things like my cyber team. We are creating truly agentic cyber where we have taken our sock and we're turning that from, you know, people eyes on glass, looking at glass to saying, forget it. the agents are going to do that. They are going to triage. They are going to raise the flag on the ones that need to be monitored. And then you only have to look at the other ones.

20:06And the exciting part about that is that we then took all those people that were in the tier one of our SOC who were looking at glass. And we said, now you're threat hunters. And so now all of a sudden, we've given them a more value added job to do for TD Cynics, a way of working that they hadn't done before. So it raises up their skillset, raises up the challenge of what they're doing, adds value to TD Cynics, and we're letting their agentic teammates do the stuff that, you know, gets you a little teary-eyed sometimes.

20:39Peter High: Fascinating. Really interesting. I want to actually ask you a little bit more about your use of agents as well. As AI tools and agents proliferate, how do you think about the best way and forgive a general question, we can get into the specifics of it, of course. How have you thought about the touch points between human work and agent work and how that evolves across time as agents come online and have greater ability to assist in the work that the organization does? Yeah. So I think it's really important that we do not believe agents should run wild, right? So every agent needs to have an owner.

21:18Every agent takes on an identity when they're being used. You don't have agents just off doing their own thing without some sort of human ownership of that outcome. And so because of that, we believe that agents and humans will be on one team working together. But there is a little bit of a hierarchy in that the agents always have to have somebody over them, understanding their outcome, understanding in their performance, understanding are they trained the right way, understanding, you know, have they been onboarded the right way and are they performing? And so much like you have some of those human processes in place, you have similar for an agent, but every agent has to have an owner.

22:05Peter High: Yeah, that's fantastic. One increasingly important skill is the ability to evaluate an AI agent's output rather than simply accepting it as well. And I wonder, How are you teaching employees to exercise that judgment and identify errors and know when human intervention is required? Yeah, that's actually part of our training. So when you think about our skill set training, we have four levels of fluency. And that first level of fluency is the basics, which we believe is not just how to use AI, like, you know, how to write a prompt or how to build an agent, but it is actually how to ensure that that outcome is accurate.

22:41it? Is it using the right data source to start when it came out and it gave you something? Did you check that source? And is it the right one? Did you check some of the math that it might have used and, you know, do some of those quality checks throughout? We're actually training people to look for those things. And the great thing in our partnership with HR is that they are making it clear that these levels of certification of each one of our four levels of fluency requires certification. And it's certification meaning it's hard to pass, but safe to fail. It's okay if you fail. Just take it again.

23:19Learn some more. Take it again. Learn some more. Take it again until we know. Because our AI policy actually states that you are accountable for the outcome of the AI that you are using. And so with that, we need to give them the feeling of, well, I don't know how to know that. Okay, well, here are the rules, right? And so we actually take them through a whole training on how to look at the outcomes of AI to ensure that it started with good data, it's coming out with relevant sources, the math is correct, as an example, and it doesn't seem biased in all of those other things that are associated with it.

23:53Peter High: Yeah, it's really interesting, Christy. Clearly, you've got a very democratic thought process when it comes to AI. And as you think about no-code, low-code, professional development tools, potentially enabling more employees to build agents, how do you encourage that development while maintaining, of course, security, governance, architectural discipline so that you're letting a thousand flowers bloom but doing so in a way that's responsible? Yeah, so we have developed our AI factory here at TD Cynics. We call it Fluent Works AI. We're really excited about it. But it's the idea to do exactly that.

24:31We want AI in the hands of every one of our employees, almost 30 ,000 now. And when we think about that, not every employee needs the same level, right? So some people might just be interacting with an agent they've been giving or a bot that they've been given, and they just need to type a prompt or ask a question in their natural language, and that's okay. But they need to be responsible for that AI, as we said, in a no-code way. Some of them might start to build some agents in a guided way, and that's okay, and we'll train them on that. And we've picked solutions for that no-code and low-code way of doing it that's really good for the masses, right, that we can put out there.

25:11But we've done it in a factory that ensures that it's got the right guardrails. We create the access to the data. We integrate the data with those tools to ensure that we know they're getting it from a relevant source of integrity that's been checked and cleaned and all of those things that we are scared about with our data, right? Garbage in, garbage out. So we want to make sure that we connect it with the right ones. The other thing that we've done is by giving them those tools and saying, here's the tools you should use for no code and low code. we've also put some guardrails around it, things that help with data protection laws, things that help with cybersecurity around those agents.

25:49For example, every agent must be registered and have an identity that you build. Okay, great. That means it's assigned your name. We know what it should have access to because it assumes your identity as you're using it. So we know that it's allowed in certain areas or not in other areas. And so those guardrails really help. And then from a ProCode way, using the same factory concept, a little bit wider aperture, because we have to get the right tool for the right job. But we have a process by which we register those tools for the ProCoder in order to use that ProCode way of developing true agents that interact with some of our most sensitive data or some of our most critical business systems in a safe way, again, by creating, you know, rules around the development lifecycle and how you checking code or by, you know, again, how they register that agent and promote it to a team or enterprise level use instead of just a personal productivity tool.

26:48So we've created this factory that I say puts the bubble wrap around the AI so that it creates it in a safe way, allowing, again, our employees to feel that they have the safe way of working, but that also it gives us a view into all the AI that's being used to ensure that we are doing the right thing. Yeah.

27:14Peter High: When you joined the company nearly two years ago, Christy, you joined an organization that had great ambitions for growth. Indeed, it has, even just in your tenure, has grown remarkably. I wonder, how do you think about growing IT to drive a company that will soon look very different from what it is currently? How do you stay ahead of that growth knowing that ambition is there? Yeah. And that's the point of intelligent IT, right, that we talked about earlier, is that we have to be ahead. We have to move with velocity. We have to start co-creating with our business rather than standing at the sidelines saying, hey, what do you want?

27:47Oh, okay. This might be a good idea. Just be right there and co-create so that you're co-creating that solution and the business outcome together rather than waiting for it to come at you. So we're looking at things like forward deployed engineering models. We're looking at things like, you know, where can we apply agentic solutions so that we can move at a faster pace with our business during this time of growth and that we can scale our business without needing to, you know, wait two years in order to scale something. But we can scale it at a much faster pace. So we're trying to apply all of that.

28:24Now, I make it sound easier than it is. This is a hard fight every day. Right. You feel like you're two steps ahead to go three steps behind. But every day is a day of progress in leveraging AI and really co-creating business outcomes. And it's so exciting to be a CIO right now.

28:46Peter High: Yeah. I love your examples about how you and other leaders are showing the way in terms of your own use. You described a little bit about your own uses. I thought maybe I'd ask you, are there other ways in which you're leveraging artificial intelligence these days that have allowed you to accelerate your learning, your output, the work that you do? Anything else beyond what you've described that you would underscore? Yeah, I actually, you get to that point where you're like, how did I ever live without this, right? Like I felt that way, like when I got my phone, I felt that way when I got Google.

29:21And now I feel that way with AI. I'm like, how did I ever live without AI? I don't remember. But I find I use it a lot, you know, simple things of, hey, I wrote this email. I don't want it to sound confrontational. I don't want it to sound, you know, too assertive. Can you just proofread it for me? Right. So I use it for like silly things like that. But then I also have built agents that help me read a lot of the trade rags and analysis that's coming out and saying, synthesize it for me. What happened overnight? Because literally you can't keep up, You just can't keep up with everything that's happening.

29:57So with some of my subscriptions and things that I have, I just have it scanning and saying, I'm interested in these companies. These are my subscriptions. Tell me what's new and what happens so that I know and I'm coming into the day more informed in what I do from a workplace. And then from a personal perspective, I use it all the time. Even my kids are, you know, I have two that just graduated from college, one that's still in college. But they actually, their colleges were very good about helping them to use AI in their assignments and then actually had them judge different AI tools to see which ones were best.

30:39And so now, like my son and I, as an example, we had language wars with our, you know, chat bots the other day. And I was using Gemini and his was using ChatGPT and we had them count together. And then we had them talk to each other in different languages. And then we had them assess one another and how they knew those languages. And then we had them assess what I was as a person and what he was as a person. And so we're trying to get an understanding of like, did his chatbot do better or did my chatbot do better? And which way did it go? And those are just, they sound silly, but like you really start to understand like chat GPT is way better at Gemini than some things.

31:20And Gemini was so much better at some things than chat GPT was just by having those little words. So you get to understand them that much better. And it's great time with my son because we got a good kick out of it.

31:31Peter High: That's fantastic. Phenomenal to learn more about how you continue to learn and think about its use as well. I wonder, are there resources that you turn to to remain abreast? You mentioned that you've got an agent, for instance, that's reading the trade rags, I think you said, to keep you informed. Maybe that's part of the answer in and of itself. But I wonder what you would recommend in terms of gathering information in such a dynamic time. Yeah, absolutely. So I would say definitely pick your favorite podcasters who are doing this all the time. And I do listen to you, Peter, because I know you have a lot going on.

32:08But my friends have given me a couple others. Pick some of your favorite journals to read. I do read Wall Street Journal. I read Forbes quite often. And then I've also found myself reading from Substack because Substack has a lot of people that are truly hands-on doing things that are ways of learning that like, I just don't have time to do all this. There's one guy, Ken H, I forget his full last name, but like he's full on and clawed and he's like so deep. Like I could never learn that myself, but like I get good tidbits of information from him on things of, Hey, did you know this from a cyber perspective?

32:51Or Hey, did you know this capability is now available in here? And these are tools that my, my, you know, co-workers are using or want to use. And so I need to be thinking about those things with my own team. So it helps me stay aware of what's going on.

33:05Peter High: Yeah. Well, fantastic. Christy, thank you so much for joining me today. Just a phenomenal conversation, emblematic of this remarkable tenure that you've had already at TD Cynics and also all that you're drawing from your vast array of experiences as a multi-time chief information officer. I really appreciate you taking the time with me today and sharing more about the work that you and your team are doing. Peter, thank you so much. And I appreciate you. I learned so much from you, especially at the last Converge conference with Inspire CIO, frameworks that you put in place. We need people like you to help us synthesize our thoughts and where we want to go.

33:41So thank you so much.

33:42Peter High: Thanks for listening to Technovation. If you enjoyed this conversation, subscribe and leave a rating. It helps more leaders find our podcast. Thank you. And I look forward to seeing you next time. Thank you.