The 2026 Gartner Supply Chain Tech Report (6/9/26)

Ellie Thornton

Welcome to the show everyone! I'm Ellie Thornton, and I'm here with Steve DeNunzio. And listen, before we get stuck into the tech, we have a quick promise for you all: we are absolutely resuming our regular weekly podcast schedule very soon, so keep your eyes on your feeds! But today, Steve, my brain is buzzing because the brand-new 2026 Gartner Hype Cycle for Supply Chain Execution and Logistics Technologies report just dropped, and it has some absolutely wild projections.

Steve DeNunzio

It is great to be back, Ellie. And yeah, this 2026 report is a massive wake-up call. There's one strategic planning assumption that immediately jumped out to me: by 2028, up to one-fourth of companies will find that labor availability is actually a bigger issue than inventory availability when it comes to meeting customer demands.

Ellie Thornton

One-fourth of companies! That is twenty-five percent of businesses basically saying, "We have the stock, we have the orders, but we literally do not have the human hands to move them out the door." It's a complete flip from the classic inventory bottlenecks we usually moan about.

Steve DeNunzio

Exactly. And that labor bottleneck is the primary engine driving this massive automation boom. Gartner is predicting that by 2028, eighty percent of warehouses and distribution centers will deploy some form of warehouse automation. That is just two years from now, Ellie!

Ellie Thornton

Eighty percent by 2028 is a staggering pace! It's like a gold rush for automated systems. But the timeline gets even more sci-fi if we look further out. The report says that by 2030, fifty percent of new warehouses in developed markets will be designed as "robot-centric" facilities, where humans are completely optional.

Steve DeNunzio

Think about that: "robot-centric" design. For the last fifty years, we built warehouses around human safety, human ergonomics, and human walking paths. Now, by 2030, we are designing them from scratch for machines, with vertical space and layouts that would make a human dizzy. Humans are basically a legacy backup plan in these new designs.

Ellie Thornton

It's proper mad! And speaking of robots, we have to talk about some of the new entries on this year's Hype Cycle. Gartner added "AI-enabled tactile systems" and "polyfunctional robots" to the rise. I'm obsessed with the tactile systems because they give robots a human-like sense of touch using high-resolution tactile sensors and flexible elastomers.

Steve DeNunzio

Those flexible elastomers are crucial, Ellie. Historically, vision systems could tell a robot where an object was, but the robot couldn't feel if it was squeezing too hard or if a fragile item, like a piece of fruit or a delicate electronic component, was slipping. Tactile AI is bridging that physical gap.

Ellie Thornton

It's the difference between picking up an egg and completely crushing it! And we're seeing this play out with massive players. Gartner mentions vendors like Dexterity, Sanctuary AI, and even Boston Dynamics with their Atlas GR2 grip. But what about when a robot needs to do more than just one task? That's where these "polyfunctional robots" come in.

Steve DeNunzio

Right, the polyfunctional robots are designed to perform multiple tasks based on immediate needs, rather than being programmed for a single, repetitive function. Imagine a robot that loads a conveyor belt in the morning, and then switches over to replenishment or sortation in the afternoon without needing a complete software overhaul.

Ellie Thornton

That sounds like the dream, but the report warns about a "jack-of-all-trades, master-of-none" dilemma. If a polyfunctional robot is only mediocre at three tasks, is it actually better than three specialized robots?

Steve DeNunzio

That is the classic operations trade-off, Ellie. And it brings us to a major software hurdle that has reached the Peak of Inflated Expectations: Multiagent Orchestration, or MAO platforms. As soon as you deploy different brands of robots—say, Locus for picking and Geekplus for sorting—they can't talk to each other. They're like different players on a pitch speaking totally different languages.

Ellie Thornton

A pitch where they're constantly running into each other! So MAO is like the manager standing on the sidelines, coordinating the whole team so they don't collide or try to pick the exact same box. Gartner notes that over ninety percent of companies pursuing advanced robotics will end up using different form factors from multiple vendors. So having that independent orchestration layer isn't a luxury anymore; it's a necessity.

Steve DeNunzio

It really is. And the software shift is moving beyond just orchestrating robots. We are seeing a radical departure from traditional warehouse management systems toward "RTLS-Based WMS." RTLS stands for Real-Time Location Systems. Instead of a human scanning a barcode every time they move a pallet, the system uses ultrawideband, 5G, or 3D cameras to track everything continuously.

Ellie Thornton

So no more manual scanning! That's brilliant because scanning can take up so much time in huge yards. The RTLS-Based WMS tracks the exact x, y, and z coordinates of every asset in real time. It's basically creating a live Digital Twin of the entire warehouse operation!

Steve DeNunzio

And that Digital Twin allows you to run simulations to test changes before you touch a single physical shelf. But we have to address the elephant in the room: AI hype. Agentic AI has rocketed from the Innovation Trigger last year to right near the Peak of Inflated Expectations. Everyone wants it, but here is the cold shower stat from the report: only around twenty percent of AI initiatives in logistics actually achieved their goals.

Ellie Thornton

Twenty percent! That is a brutal reality check, Steve. Why are four out of five AI projects failing out there?

Steve DeNunzio

It almost always comes down to fragmented data and legacy infrastructure. AI agents need clean, real-time data pipelines to make autonomous decisions, like rerouting a shipment or reallocating warehouse staff. If your WMS and TMS are still running on old, siloed databases, your shiny new AI agent is essentially flying blind.

Ellie Thornton

Which means we have to clean up our data houses first! Now, another area seeing a lot of action is "Transportation Forecasting." Historically, transportation was only planned one to five days out, and companies used basic spreadsheets to guess their long-term freight needs on different lanes. But that is changing fast.

Steve DeNunzio

Yes, operations research is being rebranded as "Decision Intelligence," using deterministic optimization engines. These engines can translate product demand forecasts into specific transportation hierarchies—like mode, lane, and carrier—months in advance. It helps shippers become "shippers of choice" because they can guarantee volume to carriers when capacity gets tight.

Ellie Thornton

I love that. It's about being proactive instead of constantly firefighting. Steve, before we sign off, what is your top recommendation for the logistics leaders listening to us today?

Steve DeNunzio

I'd say don't get seduced by the sci-fi stuff like general-purpose humanoids just yet. Focus on the foundational software first. Clean up your data, integrate your WMS with APIs, and explore specialized, high-ROI use cases like AI-enabled vision systems or transportation forecasting. Build the digital nervous system first, and the robots will follow.

Ellie Thornton

Spot on. Well, that is all for today's deep dive! We'll be back in your ears next week, so make sure you subscribe. I'm Ellie Thornton.

Steve DeNunzio

And I'm Steve DeNunzio. Class dismissed, and we'll see you next week!