Reinventing the Warehouse for the AI Era

Warehousing is entering a new age — one where AI and human labor work together to drive performance.

“It’s estimated there’ll be over one million robots operating in U.S. warehouses next year,” says Randall Guernsey.
“But even with automation, $80 billion is still being spent on labor — and inefficiency is eating away profits.”

The challenge: 55% of warehouse labor goes into picking, and 70% of that time is spent walking, not working. That adds up to billions lost annually — simply due to outdated processes.

The Hidden Cost of Inefficient Picking

Traditional WMS systems still rely heavily on manual intervention and static batching. Orders are grouped by product type or client rather than by warehouse layout — forcing pickers to crisscross the floor unnecessarily.

“Most warehouses lose 12–15% of revenue just in wasted motion,” notes Guernsey.
“That’s profit walking out the door.”

Outdated batching methods, cherry-picked orders, and paper-based processes slow down throughput and destroy margins.

AI-Powered Picking: A Smarter Way to Move

ShipHero’s AI-Driven Picking flips that paradigm.
It starts by creating a digital twin — a high-fidelity map of the warehouse that captures every aisle, rack, and bin location.

With that map, AI can:

• Algorithmically group orders by proximity, frequency, and bundling patterns

• Calculate the shortest route between picks

• Optimize the picker’s path for the fewest steps possible

“Something that takes a human hours to plan can now be done in seconds,” Guernsey explains.

The results?
✅ 30–50% reduction in picker travel time
✅ 40% increase in order throughput
✅ No disruption to existing workflows

The Human Element: Managing Labor with AI

Even as automation scales, people remain the most critical — and expensive — resource.

“Your people are your greatest asset and your biggest expense,” says Guernsey.
“That’s why managing them intelligently is key to profitability.”

Enter Workforce Hero — ShipHero’s AI-powered labor management suite.

It offers:

• Live View: Real-time visibility into who’s working where and on what.

• Autodetect Task Tracking: Automatically shifts employees between roles (picking, packing, assembly) based on system activity.

• Custom Job Tracking: Scan-based timers for special projects, enabling accurate billing or productivity tracking.

With Workforce Hero, managers can finally see — live — where time is spent and who’s driving performance.

Fair Metrics, Real Insights

Traditional KPIs like orders per hour or picks per hour are misleading.

“Those metrics reward cherry-picking,” Guernsey warns.
“They favor the easiest jobs, not the hardest workers.”

ShipHero’s Performance Dashboard replaces bias with AI-calculated objectivity.
It compares actual time on task against an AI-defined optimal time — factoring in order complexity, travel distance, and product type.

Workers are scored from 1–10, with 5 meaning “on target.”
That enables fairer reviews, smarter incentives, and data-driven coaching.

“We’ve eliminated guesswork — managers can now see if it’s a people issue, an equipment issue, or a process issue.”

Closing the Gap Between Revenue and Profit

When peak season hits, many warehouses respond by hiring more staff.
But Guernsey argues that’s the wrong reflex.

“Adding labor without fixing inefficiency just widens the gap between revenue and profitability,” he says.

With AI-driven optimization, warehouses can:

• Handle 40% more output with the same staff

• Reduce reliance on temp labor

• Cut the need for extra layers of management

The result: sustainable growth without eroding margins.

Building the Future-Ready Warehouse

To create a warehouse that’s scalable and resilient, Guernsey outlines three core pillars:

• AI Order Batching — Automate intelligent grouping for instant efficiency.

• Path Optimization — Eliminate wasted steps and cut travel time.

• AI Labor Management — Use objective performance data to manage fairly, motivate effectively, and drive profitability.

“AI doesn’t replace people — it empowers them,” says Guernsey.
“When humans and AI collaborate, efficiency compounds.”

Key Takeaways

• 55% of warehouse labor goes into picking — and most of that time is wasted walking.

• AI-driven mapping and batching can reclaim up to 15% of lost revenue.

• Data-driven labor management replaces bias with fairness and insight.

• The warehouse of the future is built on automation, accountability, and agility.

“Profitability isn’t about working harder — it’s about working smarter,” Guernsey concludes.
“AI is the key to a warehouse that never stops improving.”