In 2025, are logistics leaders still sceptical about automation and AI? What’s changed?
Five years ago, many logistics executives doubted that automation would deliver ROI. I’d be at trade shows and hear, “Why risk my job on a risky step toward automation?” That mindset has flipped. Over the last two years, leaders recognise their jobs are at risk if they don’t automate. It’s become a mandate: automate or fall behind.
Today, we’re seeing executive sponsorship across the industry. Companies need flexibility to handle seasonal peaks—5x or 10x the usual volume—that are almost impossible to handle with labour alone. Automation and robotics make it scalable, reliable and fast, which is why adoption has accelerated so sharply.
How do you help companies automate?
We bring “physical AI” that transforms warehouse operations. Our fleet—three robot types working together—fully automates key workflows by integrating with the customer’s WMS, ingesting orders, and orchestrating robots and people so tasks get done faster and more accurately. It’s how brands move from manual processes to an e-commerce scale they could never reach otherwise.
At a high level, robots handle travel and transport while humans handle value-adding tasks, and the system continually optimises the collaboration. The result is higher throughput, better SLA performance, and the ability to scale globally. We’re deployed at more than 350 sites worldwide, with customers expanding from the U.S. to Europe and APAC on a common platform.
What is Locus One, and how does it use live data to balance work across zones and sites? Where do customers see performance gains?
Most customers see around a 2x efficiency uplift right from the start—if an associate was picking 60 units per hour, we’ll take that to roughly 120, with some sites seeing 3X+ increases, depending on their baseline. The gains come from reducing human footsteps, sequencing work more intelligently, and orchestrating robots to do travel-intensive tasks so people focus on picking.
Locus One is our orchestration AI that shifts warehouses from reactive to predictive. It pools orders, decides pick sequence, assigns work to robots, guides associates to the next best pick, and manages workflows like picking, putaway, replenishment and returns. It also handles slotting—re-positioning items (think “socks near shoes”) based on order co-occurrence—and uses AI for object detection so robots reroute around forklifts and obstacles. In short, it doesn’t just tell robots what to do; it teaches the network how to think.
You mentioned a new robot, Array, that removes most labour from a building. What problem does it solve?
Labour scarcity is a persistent constraint—many former warehouse workers have moved to gig roles, and sites can’t find enough staff to ship what they sell. Locus Array, launching early next year, is designed to automate up to 95% of repetitive fulfillment activity, helping operations overcome labor constraints and focus their people where they add the most value. by automating end-to-end flows. It lets operators scale without relying on incremental headcount.
Ultimately, customers want to meet SLAs dependably at a lower cost. By drastically reducing manual touches, Array boosts throughput while maintaining consistent performance during peaks. It extends the same principle we’ve applied with our fleet: robots take on travel, transport and repetitive motion; people do targeted tasks with far less fatigue and error.
How does Robots-as-a-Service (RaaS) work for rapid scale-up and scale-down?
We pioneered RaaS in logistics because it turns fixed automation into elastic automation. Customers pay a subscription; we own, maintain and upgrade the robots over the air—like updating a smartphone—so the system gets better over time. During peak season, we ship thousands of robots for temporary capacity, then sites can scale down when volume subsides.
Deployment is fast and easy. When robots arrive, you power them on; they automatically download the site image map, localise in the building, and begin working within minutes. With RaaS, customers buy an outcome, not equipment, and they can right-size capacity in near real time—something that’s hard to do with human staffing or fixed mechanical systems.
Competition is heating up. What will separate winners from the pack as AI becomes ubiquitous?
It comes down to delivering measurable value, not “AI on a slide.” We’ve used AI for years; what matters is using it to hit SLAs, cut errors and lower costs. For example, our associate-level AI agent minimises footsteps by directing each worker’s next move in their preferred language—Spanish, Japanese, Chinese, Portuguese and many others—automatically via a Bluetooth tag. That reduces errors and speeds picks.
At the manager level, predictive algorithms and dashboards forecast the day’s trajectory and recommend staffing changes to meet targets at the lowest cost. Our digital twin lets customers simulate adding robots, re-slotting, changing headcount, or altering aisle layouts before they commit. The players who consistently convert data into customer outcomes—and ROI—will win.
Will AI and robotics reduce warehouse jobs, or just change them?
Jobs will change. We already see new roles around managing data, agents and dashboards—there are more than two dozen reports and dashboards available to help our customers proactively manage and optimize their operations. Labour won’t disappear, but tasks become more efficient and more rewarding, and higher productivity can translate into higher earnings for associates.
Some products, like Array, intentionally remove a lot of labour from the building process. But that creates roles focused on orchestration and oversight. Many traditional picking jobs are hard to fill—night shifts, repetitive work, minimum wages—so automation relieves pressure while creating higher-skill positions around systems management.
Where do you see the biggest misunderstanding about AI in warehouses, and what should leaders know now?
Many still underestimate how to leverage their own data. Our fleet produces a tremendous stream of real-time data—powering the intelligence that allows Locus to optimize productivity, predict maintenance needs, and continuously refine site performance. Leaders at large firms—think DHL—push hard and understand the upside, but smaller facilities are earlier in the journey and haven’t fully seen the benefits yet.
My message: AI today is about converting data to insights that drive decisions before problems occur. If you’re not on this bandwagon in the next five years, you’ll be left behind. We’re expanding APIs so customers can ingest our telemetry into their systems, run their own analytics, and compound the gains. The future is proactive, data-driven operations—not reactive firefighting.
Circling back to scepticism: what finally changes minds in Europe or elsewhere?
Results. Executives used to ask why they should risk their jobs by automating; now they see their jobs at risk if they don’t. When they experience 2x efficiency, on-time SLAs through peak, and the ability to spin capacity up or down in days rather than quarters, scepticism fades quickly.
The other unlock is flexibility. A network that thinks—re-slots intelligently, routes around obstacles, allocates tasks in real time—lets sites handle volatility without breaking. Once leaders see that automation is elastic, improves the human job and pays back fast, the conversation moves from “why automate” to “how fast can we roll it out?”
In one line, how would you define the value of Locus One and your fleet to an operations leader?
We turn warehouses from reactive to predictive using physical AI and orchestration to double productivity, hit SLAs through peak periods, and give you elastic capacity that scales with demand while continuously improving over time.
