# Where Is AI in Planning Today - and Where's It Going?

## Метаданные

- **Канал:** SupplyChainBrain
- **YouTube:** https://www.youtube.com/watch?v=H4bGipqZLyI
- **Дата:** 11.05.2026
- **Длительность:** 8:36
- **Просмотры:** 39

## Описание

AI is transforming supply chain planning faster than ever — but where are companies really today, and how should leaders get started?

In this episode, Bob speaks with Mike Landry, CEO of Ketteq, live from the Gartner Planning Summit to explore the evolving role of AI in planning and decision-making.

Mike breaks down:
• What AI agents are and how they differ from traditional automation
• How agentic AI is changing supply chain planning
• Why AI should augment — not replace — human planners
• The importance of trust, guardrails, and avoiding AI hallucinations
• How organizations can distribute decision-making across the business
• The future skill sets planners will need in an AI-driven world
• How companies can prepare for disruption and “black swan” events

The conversation also explores how AI is moving supply chain planning from a back-office function to a strategic driver of growth, customer service, and business agility.

Mike also shares the story behind Ketteq and how the company is building cloud-native AI agents for demand, inventory, and supply planning — integrated directly into Salesforce to empower teams across the enterprise.

If you're interested in AI, supply chain transformation, planning technology, or the future of enterprise decision-making, this interview offers valuable insights into where the industry is headed.

#AI #SupplyChain #SupplyChainPlanning #GenerativeAI #AgenticAI #BusinessTransformation #Planning #MachineLearning #EnterpriseAI #Salesforce

## Содержание

### [0:00](https://www.youtube.com/watch?v=H4bGipqZLyI) Segment 1 (00:00 - 05:00)

Where is AI in planning today and how do you get started? I'm joined today by Mike Landry. He is CEO of Caticu. Hello Mike. Hi Bob. Welcome. Thank you. — Thanks so much for being with me today. — Thanks for having me. As you point out, you know, here at the Gartner Planning Summit, AI is the word of the day. It's everywhere in planning. Where is it? I mean, in your estimation, where is AI? What role is it playing really right now? — I think right now we're just getting started and it's going to be a learning path as companies test and try and implement AI in the form of agents or generative AI. There's a lots of flavors of that, but as they look at their business through that lens and they try things, there's going to be a lot of learning. Some missteps perhaps even, but the next few years are going to be pretty exciting as people figure out what makes sense for their business. — So much has happened in the last few years, even in the last two years we've come so far. Generative AI exploded on the scene and then after that, agentic AI as you just described, AI agents. Explain to me how AI agents, first of all, what are they and what role are they playing in planning? — So agents are essentially with intelligence doing the job that a person might do. And so it might not replace a person, it might augment what that person does. Instead of having five planners looking for answers and solutions, imagine a world where you had like a thousand planners. No one would hire a thousand planners, but a computer can do that. And so agents can kind of can help companies find and it scale their jobs and the answers that come out of that in a very efficient way. And a back end in terms of automating that work. On the front end with the generative AI, that's where the user interface might change to make it more conversational and natural versus, you know, clicks on a screen. Agents of course, any number of agents can be a discrete agents can address this. You There's no limit to the number that you can employ for various discrete tasks. And it's really taking robotic process automation, which is around for 10 years, RPAs, which are more of a script, and that would automate work, but this is brings intelligence into it. So, it's making decisions along the way. That's the difference between an agent and an RPA of what was implemented maybe 10 years ago. — An RPA is just telling you it's doing what you tell it to do. — Yeah, that's right. — And these agents are developing the point where they can actually make decisions on their own. Word we all [clears throat] like to use these days is autonomous. — Right. A little bit scary. Uh, if you're a supply chain planner, you go, "Wait, am I actually taking my hands off the wheel? Is this model doing my work for me? " What would you say to that? — Yeah, I'd say that there is some autonomy, but it's also augmented in terms of the person plus the machine to get the best answers. Because the reality of the world that a company is trying to address isn't always found in the data. So, the person to bring that context in combination with what an agent's doing with your data will get to the best answers. How is this changing the whole role of supply chain planning in the greater organization? I think people will have a chance to re- revisit how they do planning, and it might not be a center of excellence, that's how a lot of companies have It might be a distribution of excellence if you start to almost turn it upside down, and you say, "Where are decisions being made that could be made better and faster with the intelligence and the support and the help of an agent? " So, instead of a handful of planners, and everyone's got to go to that center of excellence, now you bring the decision-making tools to where that's being made, whether it's in sales or marketing or in a manufacturing organization, supply chain can be the heartbeat, and it can really connect the rest of the company to do the best job possible to grow revenue and serve customers. Feels like it's taking a function that was essentially relegated to the back office back in the day, and it's bringing it forward, so allowing you to step forward and play a greater role in the organization. All because of this? Is that AI making that possible? Well, I think it's a big factor. It's enabling it. But also, I think companies are ready for this. You know, the world is um is a smaller place. It's a very interconnected now, as we see with the any disruption in one part of the world, it tends to disrupt the other side, as well as adjacent industries that rely on each other. So, we're very, very well connected now, and because of that, um we have to look at the how we manage and run these different supply chains differently, and AI is going to enable that. You referred earlier to missteps. I mean, any new technology is going to be is not going to be deployed in a perfect manner. What kind of missteps might there be, and what mistakes do companies make in approaching AI the wrong way? I think they have to build trust. And we talked about, you know, people are talking about that here at the conference. Even going back to the keynote from today this morning. So, building trust in these agents that people can rely and believe what they're doing, there's no hallucination that's happening. So, that has to happen first. So, the change management isn't so much adopting new processes as trusting and believing and following

### [5:00](https://www.youtube.com/watch?v=H4bGipqZLyI&t=300s) Segment 2 (05:00 - 08:00)

what the agent's doing, but also being able to put your hands back on the wheel, should the need arise. Well, GenAI is definitely subject to hallucinations. We've seen that many cases. Is that the case with agentic AI as well? I mean, I thought you were developing these discrete, purpose-built agents. Is it possible that they too can hallucinate? If not, I think so. I think because it's relying on data, and if that data is incorrect or incomplete, then it may come to the wrong conclusion because, you know, of the input that's there. So, there's machine learning, and it's always and things get better, just like people get better. Um but, at the end of the day, you still have to put the guardrails around it, particularly in the early stage where companies are learning and Well, you talk about learning, and does it is it not the case that an AI model that you employ for the first time has to get up to speed on your own organization? Has to learn your organization. How long does that take? Yeah, I think it each case is going to be different based on the learning curve, just like a you know, a subject might be different from another in a person's learning curve. Um but as it sees what it decides or the things that it assumes, how it really plays out, it'll be able to factor that into the next time it's coming up with a decision based on what happened the last time it saw a similar data uh pattern. And it must also be able to deal with things it's never seen before, you've never seen before or a company's never seen before because new stuff's always coming up. Smart enough to do that? Yeah, in some cases, I think so. You know, these black swan events are unique, but in some way they're also the ramifications, the impact of those black swan events are they can we can find a similar pattern. So, there'll always be something unique in these different things that happen, but there's some some similarities that we can draw on. And the profile of an individual human planner, how will that change in terms of the skill sets they need, what they're doing on the job? I think that they're if they can rely more and more on the agents and the intelligence of AI, their value will be really knowing their business, knowing from the executive strategies and goals and where they're trying to get, what the competition's doing, the landscape of customers and customer expectations, how to compete in the marketplace, all the contacts that's outside the data and bringing that to AI, being the domain experts of their business and their marketplace will be, you know, where they're adding the most value, I believe. Great. Mike, thanks again for your insights into the just where AI is in the planning world and where it's going. Thanks very much for your time on that. However, I would like to you to take a moment to tell me about Ket IQ. Who are you guys? — Yeah, thanks. So, well, we started on the heels of about 30 30-plus years of experience of building and implementing supply chain planning solutions way back when the internet was the new technology. Well, now the new technology's AI and when we started in 2019, we're were to say we're going to be cloud native. It gives us great advantages in how the cloud computing horizontal scalability can be leveraged cuz you really have to have a lot of computing power to run agents on behalf of people doing work. So, we built agents to run demand inventory and supply plans and to be able to generate more answers than a person could ever do with the current or legacy technology that's out there. And then we take it and we bring it into Salesforce. So, like I talked about the people in the access to this intelligence and these insights aren't just the core supply chain planners. It's people across the business that are customer-facing from sales and marketing and customer service. They all need these kinds of insights so they can do their job better and faster as well. And in that case, the whole business can uh move forward in the best possible way. Mike, thanks again for your time. We appreciate it. Thank you, Bob. I've been speaking with Mike Landry of Kittyhawk. Thank you very much for watching.

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*Источник: https://ekstraktznaniy.ru/video/50727*