Artificial intelligence and automation have become daily talking points in supply
The broadening use of AI and automation in distribution has continually pushed the idea of dark warehouses, those that are fully automated and require minimal to no staffing to operate and fulfillment orders. Yet the drive toward a fully automated dark warehouse is still years away at best – and for many businesses isn’t even a reality at this point. This is mainly due to the high-cost of entry with automation for small and mid-sized businesses.
Most warehouses continue to add robots, automation and controls piece by piece, while humans still handle many day-to-day tasks, supervision, management and complex exceptions. DHL reports around a 30 percent jump in operational efficiency after rolling out autonomous mobile robots. These gains highlight both the promise and the limits of automation.
This article takes a balanced look at where AI and automation are making measurable progress in warehousing and distribution, and where hype outpaces reality. It sets out to help you separate genuine value from marketing buzz, and to encourage you to make decisions based on data, not fashion or hyped-up trends.
Robots are being introduced into warehouses at scale. Autonomous mobile robots travel the aisles, carry bins and reduce walking distances. As previously stated, DHL reports a 30 percent lift in operational efficiency after adopting AMRs.
This number sounds impressive, and it is. But it does not mean people are gone. In fact, the company still brings in seasonal workers to handle spikes in demand. Robots do not pack every box or solve every problem. They take over repetitive tasks, such as moving carts and picking standard items. People still handle exceptions, operate forklifts, maintain equipment and manage customer service.
The bigger story is collaboration. Cobots, or collaborative robots, work side by side with staff. Names like Locus, Geek+ and 6 River are just a few of the names people are familiar with in this category. They guide pickers through orders and carry heavy loads. They reduce strain and increase productivity without eliminating jobs.
Employees appreciate these aids because walking distances decrease, accuracy improves and overall throughput increases. It is important to measure success through both productivity and worker satisfaction. The days of not worrying about worker satisfaction are gone, the high cost of labor, loss of productivity and HR costs associated with employee turnover make this an important metric.
But even with these benefits, consider the following statistics:
This is in no way to diminish the accomplish of these companies, they should all be celebrated for their accomplishments. But consider the following statistics:
The number of sites in the US, over 100,000 sqft, utilizing various forms of robotics and cobots is relatively low. This speaks to several aspects, including rate of adoption, cost of entry, usability and applicability in different operations, etc.
If you are evaluating robotics, or cobots, look beyond claims of labor elimination. Ask about training, maintenance and how the system handles errors. Compare the cost of leasing or buying robots against improved throughput and lower turnover. Plan for a mix of human skills and mechanical power.
Every vendor now seems to claim AI. Surveys show wide adoption, yet adoption at depth remains limited. Research found that about forty percent of startups claiming to use AI have no AI at all. Many companies simply rebrand older automation routines as intelligent agents. This tactic, known as AI‑washing, misleads investors and customers, and slows progress.
Regulators are starting to respond. The U.S. Federal Trade Commission warns vendors to be honest when advertising their AI capabilities. The Securities and Exchange Commission recently fined two investment firms for making false claims about AI. These actions signal that hype without substance carries risks.
How do you avoid being fooled? Ask vendors to explain their models. Do they employ data scientists? What data is used to train the system? Does it adapt to new information? Request proof of performance, such as error rates or predicted versus actual outcomes.
Be skeptical of generic statements about self‑learning or human‑like reasoning. Look for openness about limitations and human oversight. It is easy to be swept up by the promise of AI. Take time to verify. A balanced approach will protect your investment and support honest innovation.
A dark warehouse is a facility run entirely by automation. Workers only enter for maintenance and inspections. The idea sounds futuristic. Yet industry experts note that we are still several years from full realization.
Operators are introducing automation piece by piece. They add palletizers, robotic unloaders and smart conveyors. They integrate these with warehouse management systems. They do not switch off the lights overnight. For small to mid-sized businesses, the reality is that some goods to person technologies are difficult to achieve a reasonable ROI.
Consider the following assumptions. Let’s say a smaller ecommerce operation employs 35 people throughout all aspects of the distribution center. This would be everyone from receiving, shipping and inventory control functions.
At $28 per hour, including all benefits and overhead, it is roughly $58,000 annually. Popular goods to person technologies from Opex and AutoStore for example are no less than a $2,000,000 entry point when factoring in equipment, engineering, onboarding, integrations and annual support.
To achieve a 3-year ROI, the ecommerce company in our example would need to reduce headcount by 10-11 FTE’s beginning in year one. This just isn’t financially achievable.
A 5-year ROI would require reducing FTE’s by at least 6 to 7 in year one – this still is not achievable, and with the cost of money these days, businesses do not have the appetite for a five-year payback.
Many warehouses handle varied product lines, which makes complete automation hard to justify. The workforce factor matters too. Labor shortages push automation forward, but most companies still need people. Workers maintain equipment, solve exceptions and provide customer service.
For your business, start with targeted warehouse automation. Consider automation and robotics for the functions where you invest the most in labor costs and those areas where errors and customer service impacts erode margin and customer satisfaction. Measure benefits and challenges before expanding. A fully dark facility might be an end goal, but a hybrid approach allows you to adapt to change and manage costs. Ensure that the warehouse automation ROI is sound and realistic.
AI thrives on data. Without consistent, accurate information, machine learning models falter. Warehouses these days utilize a wide array of sensors, barcode scanners and connected devices to gather data on every movement. IoT trackers, such as FedEx’s SenseAware, let shippers monitor shipments with real time updates on location, temperature and security status. These sensors feed alerts if conditions shift. This type of visibility is important for pharmaceuticals, food and other sensitive goods.
Inside the warehouse, IoT sensors track stock levels, temperatures and humidity. They help prevent spoilage and maintain compliance with storage standards. Fleet management systems use sensors to monitor vehicle location and engine health. This information supports predictive maintenance, reducing downtime.
Good data infrastructure involves more than silos of data captured by devices. It requires integration across systems. Warehouse management, transportation management and enterprise resource planning systems must share data in near real time.
Data must be cleaned and standardized. Perfect data is not required but neglecting quality leads to false insights. Avoid relying solely on spreadsheets or manual entry. Invest in middleware or cloud platforms that connect devices and systems. Build a small team to manage data quality and analytics. Your AI analysis and results will only be as insightful as your data foundation.
Many people become enamored with various technologies and the potential for improvement. They tend to rush in headfirst without considering different aspects. Before you jump in, think about the following:
These questions push you to think critically. They help you avoid adopting technology for its own sake. They ensure that each investment supports your unique business needs.
AI and automation are transforming warehousing and distribution. Adoption is broad on the surface, yet deep integration is still limited. Robots, AI and automation improve efficiency, but people still drive decisions. Good people, with strong leadership and proper training will push your company forward in significant ways.
F. Curtis Barry & Company has decades of experience in warehouse and supply chain consulting. Our team helps you evaluate warehouse automation options, design data strategies and select vendors. We work with your staff to build processes that fit your business. We focus on practical results and measurable gains. Connect with us to discuss how we will help you move forward with confidence.