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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteAugmented reality (AR) can guide workers through warehouse tasks, while artificial intelligence (AI) can help decide which tasks to do, in what order, and with which resources. Used together, they can connect planning software to work on the warehouse floor—but reported gains from individual DHL pilots and deployments are examples, not a guarantee of results elsewhere.
How can augmented reality improve warehouse picking?
In vision picking, a worker wears smart glasses that display instructions in their field of view. The display can guide the worker to an aisle or item location and show the quantity to pick, leaving their hands available for the task. The workflow described by DHL also relies on capabilities such as barcode reading, object recognition, indoor navigation, and connection to a warehouse management system (WMS); glasses alone do not provide the full system.
What DHL’s vision-picking pilot found
In a three-week pilot in Bergen op Zoom, the Netherlands, DHL worked with Ricoh and Ubimax on vision picking. DHL reported a 25 percent increase in picking efficiency. Ten order pickers handled more than 20,000 items and fulfilled 9,000 orders during the pilot. These are results reported by DHL for that trial, not an independent benchmark or a typical expected improvement for other warehouses.
DHL’s 2014 Augmented Reality in Logistics: Changing the Way We See Logistics report also outlined possible AR uses in transportation optimization, last-mile delivery, and value-added services. Those were proposed use cases and a forward-looking view, not proof that such workflows are routinely deployed.
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How can AI optimize logistics and supply chains?
AI and optimization software can work behind the scenes to organize warehouse activity: grouping orders logically, choosing routes through the facility, allocating staff, balancing workloads, and prioritizing work. Those decisions can then be delivered to workers through existing screens, scanners, or an AR display.
What DHL reported about IDEA
DHL Supply Chain described its IDEA software as supporting route optimization, order clustering, staff allocation, workload balancing, and priority handling. In the first commercial deployments in DHL-operated e-fulfillment warehouses, the company reported up to 50 percent less employee travel distance and up to 30 percent higher productivity at individual locations in 2020. Both are DHL-reported, site-specific results; “up to” is important, and the figures should not be treated as a single test or a cross-industry forecast.
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Emerging AI uses
In its September 24, 2026 announcement about Logistics Trend Radar 8.0, DHL Group described AI analytics and agentic AI as emerging capabilities for anticipating inventory shortages, rerouting around disruptions, and adjusting transport capacity. That is a trend description, not evidence that autonomous AI systems are already routine across logistics operators. DHL also emphasized workforce skills, safety, governance, and employee experience as important considerations.
Where AR, AI, and robotics fit
| Approach | Best-fit role | Worker interaction | Key dependencies |
|---|---|---|---|
| AR | Present task instructions and item-selection guidance to a worker. | Hands-free, in-view guidance through a wearable display. | Accurate item and location data, recognition or scanning, indoor navigation, and WMS integration. |
| AI and optimization software | Improve routes, order grouping, staffing, workload balance, and priorities. | Recommendations or assignments are delivered through the operation’s interfaces; the cited reports do not prescribe one interface. | Reliable order, inventory, location, and labor data, plus links to warehouse and planning systems. |
| Robotics | Physically move, sort, or manipulate goods. | May operate alongside people or within a human-supervised workflow. | Equipment, facility layout, safety controls, and integration with warehouse processes. |
AR and AI are complementary layers, not a single proven package: AI can help determine a route or task sequence, and AR can show a worker what to do next. The cited DHL reports describe these functions separately and do not establish a measured result for a combined AR-and-AI system. Robotics addresses physical transport or manipulation rather than simply presenting instructions or optimizing assignments.
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- Experience True AR with 6 DoF, Spatial Anchor Anytime: Pairing with XREAL Eye, anchor your screen anywhere in your room, so it stays perfectly fixed in place—even as you walk around, lean in, or change your position. Unlike 3DoF, which keeps the screen at a constant distance relative to your head movements, 6DoF keeps your virtual screen locked to a real spot in your space for true spatial freedom and a more natural, immersive AR experience.
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Why warehouse picking matters—and what the cost figures mean
DHL’s 2014 Trend Research report, citing de Koster et al. (2006), estimated that warehousing accounted for about 20 percent of logistics costs and that picking represented 55 to 65 percent of warehouse operating costs. These are estimates reported in that 2014 publication, not current universal cost shares. They help explain why reducing unnecessary travel or improving picking workflows can matter financially, but they do not establish the savings a particular operator will achieve.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What a logistics operation should evaluate before adoption
- Task fit: Decide whether the bottleneck is worker guidance, route and workload planning, or physical movement. The technology should address that specific problem.
- Data and integration: Check the quality of item, location, inventory, order, and labor data, and confirm how the system will connect to the WMS and any order or workforce-planning tools.
- Work conditions: Assess lighting, network coverage, shift duration, device durability and charging, and compatibility with gloves and required personal protective equipment. Test how workers handle exceptions when recognition, connectivity, or instructions fail.
- People and governance: Involve workers in evaluating ergonomics and usability; provide training and clear oversight for automated recommendations. Define who can override a decision and how safety issues or exceptions are escalated.
- Evidence and measurement: Separate pilot results from sustained commercial operation, and company-reported results from independent validation. Set a baseline and measure the operation’s own outcomes rather than assuming that published percentages will transfer.
- Total implementation effort: Include software and WMS integration, process redesign, training, support, and ongoing data management—not just the cost of wearable hardware.
What the reported results can—and cannot—tell you
The concrete performance figures discussed here come primarily from DHL reports about DHL trials or operations. They show that particular workflows have produced promising reported outcomes in those settings; they do not establish typical return on investment across logistics providers or independent validation of the gains. DHL’s 2019 announcement described smart-glasses rollout status at that time, and its 2015 pilot named Google Glass and Vuzix M100. Those historical references identify a device category, not a current product recommendation or confirmation that those models remain available or suitable for industrial shifts.
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