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4 Ways Generative AI Will Impact the Supply Chain

June 15, 2023
Stronger operational efficiency and predictive maintenance are a couple of the benefits of AI.

Logistics companies have faced persistent supply chain issues since the start of the pandemic. And nearly 60% of logistics managers are not expecting conditions to return to normal until at least 2024 – if at all.

While many of the root causes (like the war in Ukraine) are beyond control,  leaders have focused on resolving issues they can control. The problem? The technology hasn’t been there. That is until generative AI burst onto the scene.

With this technology, users can interact via conversational chatbots or microphone-enabled headsets. And behind the scenes,  AI uses technology like large language models and natural language interfaces to output text and audio that’s sophisticated, personalized, and easy to understand.

Generative AI is still an emerging technology. But it promises to impact almost every aspect of the supply chain, from operational efficiency to maintenance timelines.

Let’s look at four of the most exciting applications.

1. AI-Powered Voice Picking

Imagine a worker who’s tasked with picking a batch of customer orders for shipping. They go to a specific rack for a specific type of item, but there isn’t enough inventory in that location. So they ping their supervisor for an alternative place to look.

Except the supervisor is busy helping someone else with a forklift or pallet jack. The worker can’t get the instructions they need, which means they can’t load up all the orders before the last delivery trucks go out. What customers experience in the end is: shipping delays and plenty of frustration.

Enter AI-powered voice picking. This technology uses a natural language interface to communicate with workers via audio. Workers can ask conversational questions using a headset microphone. On the back end, generative AI can analyze a warehouse’s enterprise resource planning (ERP) software to give data-informed answers.

Voice picking already exists, but current technology relies on area confirmation codes and command-based language. The resulting interactions often feel stilted, and it can take a while for workers to adjust.

Generative AI improves on this technology by enabling more conversational interactions. What’s more, it can even translate audio inputs and outputs based on employees’ language preferences. That’s huge for warehouses that employ workers with English as a second language.

What does AI-powered voice picking look like in practice? In our earlier scenario, a worker can ask questions out loud like: “Where else do we have Product A in stock?” In seconds, the AI can communicate the right warehouse section, aisle, and rack – all without the need to wait for a supervisor. And if the worker speaks limited English, they can receive instructions in the language they prefer.

The takeaway: with AI-powered voice picking, logistics leaders can speed up the order-picking process.

2. Predictive Maintenance

Equipment failures are incredibly costly for logistics companies. If a conveyor system malfunctions or a few electric pallet jacks break down, operations can quickly grind to a halt. And if there’s a part shortage, it could take a while to complete repairs in order to return to normal operations. The downstream impact: slower order fulfillment times.

With generative AI tools, though, logistics leaders can receive real-time guidance about equipment maintenance.

For instance,  if an operations manager wants to know the status of their conveyor systems on a given day, they can query a generative AI chatbot, which will process data from equipment monitoring sensors on every conveyor system.

From here, the AI can generate…

●    A table displaying the percent of operational conveyor systems in each warehouse zone.

●     A chart that slots the conveyor systems into “green,” “yellow,” or “red” maintenance categories.

●     Recommendations for how to fit maintenance within existing operations (e.g., making repairs on weekends or after peak weekday hours).

If the manager wants to order repairs, they can ask the AI questions like “How long will it take to repair Conveyor System A?” or “What parts will we need to complete repairs?” Then,  AI can generate a predicted repair timeline or a list of required parts. It can even access external supply chain data to identify part shortages that might impact the time to repair.

Generative AI can help logistics leaders prevent equipment failures before they occur. This way, it’s easier to avoid operational bottlenecks that ripple throughout the supply chain.

3. Simple Workplace Safety Management

Worker safety is an increasingly serious challenge for logistics leaders. From 2011 to 2021, fatal work-related injuries increased by 30% and nonfatal injuries by nearly 40%.

From a human perspective, there’s a clear need to create safer working conditions for logistics teams. But there’s also an efficiency factor to consider. Each work-related injury keeps workers away for weeks, if not months. That’s something logistics companies can’t afford amid an ongoing labor shortage.

Here’s where generative AI can help. Leaders can outfit their warehouses with AI-powered computer vision cameras that continuously monitor an area for safety hazards (say, if a worker is too close to heavy machinery or dangerous chemicals). Then, the AI can push alerts to workers via a smartphone app or industrial-grade wearable.

In the back office, an operations manager can use a generative AI chatbot to learn more about safety problems on the ground. For instance, they might ask, “What are the top five safety issues we’re facing today?” Then, the AI can pull from camera data to list the specific problems on the warehouse floor – and use historical data to contextualize current problems within long-term trends.

Generative AI can also support leaders during the workplace safety training process. For example, when building out weekly toolbox talk topics, a floor supervisor might ask an AI chatbot to list eight topics that tie directly to real-time safety needs. And if a cohort of new employees needs to complete a series of digital safety training modules, an AI chatbot can respond to user questions as they come up.

The bottom line? With AI technology, logistics leaders can more easily keep workers safe and reduce injury-related downtime.

4. Stronger Operational Efficiency

Operations managers oversee product inflow, outflow, and movement throughout a warehouse. But with persistent supply chain issues and mounting customer frustration, there’s more pressure than ever to maintain efficient operations.

Generative AI can relieve some of this pressure by functioning as a personal operations copilot. For instance, an AI chatbot can communicate with managers about…

● Product movement trends. AI can flag whether there are frequent bottlenecks, say, in the loading or packing zone.

● Product heatmaps. AI can create heatmaps that display whether certain racks are being over- or under-picked.

●  Broader supply chain disruptions. AI can continuously monitor news outlets and communications channels for real-time information about disruptions. Then, it can suggest email language to notify customers about how their orders might be impacted.

One of the coolest parts? Generative AI can learn from every interaction to make increasingly helpful recommendations. Over time, this can have a huge impact on operational efficiency.

To Rightsize the Supply Chain, Think Beyond “Normal”

It might be a while before the supply chain returns to normal. But “normal” shouldn’t be the goal.

“Normal” in 2020 wasn’t enough to combat COVID-related workforce cuts. And “normal” in 2022 couldn’t keep up with the spiraling supply chain crisis out of Ukraine.

It’s time to think beyond returning to normal – and invest in emerging technologies that can help logistics companies achieve unforeseen levels of efficiency, productivity, and safety.

Generative AI can be a part of that solution. But don’t stop there. Look for ways to integrate cutting-edge sensors, mobile software, and connected wearables throughout your operations. The end goal: a smart supply chain that can weather any crisis.

Dan Giangiulio is the Senior Director, Solution Delivery at Nexer Enterprise Applications, part of the Nexer Group. Businesses around the world rely on Nexer for ERP, data analytics, internet of Things (IoT), and artificial intelligence (AI) expertise.

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