ADOPTING AI TO AUGMENT THE WORKFORCE

AI is smart, but it can’t do everything

THE ADVENT OF artificial intelligence

(AI) platforms such as ChatGPT has led to increased interest across all industries in exploring its potential applications. In logistics, for example, AI has shown great potential to increase operational efficiency.

The main reason why many industries, including logistics, have embraced artificial intelligence on such a wide scale is its superior data processing capabilities, as the ultimate goal of the logistics sector is to deliver goods as efficiently as possible. Although “efficiency” is often thought to equate to speed, it also involves cost, maximizing capacity, and other factors.

Human error is one of the biggest detriments to efficiency, as it causes slowdowns, increases costs, and can lead to a reduction in capacity. To combat this, many industries – including logistics – are beginning to embrace artificial intelligence to eliminate potential sources of human error.

How AI helps

One of the most exciting use cases for AI in the logistics industry has been route optimization. There is much more to route optimization than finding the quickest route.

Often, drivers are dealing with multi-stop routes, where they have multiple pick-up or drop-off points that must be reached in a timely manner. AI has the power to optimize a route based on these multiple stops, ensuring the driver will complete the delivery as efficiently as possible.

AI can also automate the dispatch process in logistics. An algorithm can determine what driver can best complete the delivery based on a combination of factors, including proximity to pick-up, distance to drop-off, vehicle capacity, the driver’s performance, and more. The driver is automatically dispatched more quickly than a human dispatcher ever could.

Another application for which AI has shown great potential in logistics – and perhaps the most interesting consumer-facing use case – is the use of AI-powered chatbots for answering customer service questions and taking orders. The goal is to enhance the customer experience by reducing waiting time, while also improving efficiency by allowing human workers to focus their attention on more demanding tasks and stop wasting time on mundane tasks.

Keeping AI in check

That said, an AI chatbot does not serve as a perfect replacement for a human worker in terms of customer service. For more mundane tasks, such as frequently asked questions, a chatbot can be useful because it can answer the question without delay.

However, for more complex issues, a human worker is necessary for relationship management. When dealing with clients, the human touch can make the difference in maintaining an account.

Additionally, even though artificial intelligence is generally more efficient than a human worker, it is important to remember that these programs are not infallible. AI still makes mistakes, so it is important to have someone in place to check the algorithm’s work and ensure that no mistake is made that will have catastrophic consequences.

For example, if a delivery is perishable or otherwise time-sensitive, and the AI makes a mistake optimizing the route, that could mean the entire delivery is ruined.

Another part of the logistics process unique to human ability is on-the-spot decision-making. Although an AI algorithm can do a fantastic job of optimizing routes and dispatching based on pre-existing data, there is often a delay in its ability to process new data.

For example, if a driver is on a route optimized by AI and there is a wreck ahead, it will take some time for the AI to realize this. On the other hand, a human driver can recognize this potential delay as soon as it happens, allowing them to take immediate action and prevent a delay.

AI and your human workforce

One of the most significant steps companies must take to find an effective balance between artificial intelligence and maintaining a human workforce is embracing retraining and reskilling. Although some jobs might go away in favor of the efficiency of AI – such as dispatching jobs – there will still need to be people to oversee the AI, fix it if something goes wrong, and step in if the AI should stop working. Training workers to complete these jobs can ensure they stay relevant.

The best approach a company can take towards AI – particularly in the logistics sector – is to use it as a tool that can enable humans to do their best work. AI-powered route optimization and automated dispatch allow drivers to do a better job. Chatbots for customer service allow human representatives to pay better attention to customers with more complex issues.

When we stop looking at AI as something that can do our jobs for us, and instead as a tool that can help make our jobs easier, we will begin to empower our workers to be more effective and efficient in nearly everything they do.

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