Toni Pisano is the Chief Customer Officer and a Board Member at PortPro Technologies, Inc.
AI may be the most powerful transformative technology we witness in our lifetime. But amid all the hype, how do we make it practical in our day-to-day business processes? With new models and breakthroughs constantly emerging, it’s easy to get lost in the noise. And besides, who really knows the difference between GPT-4.5 and Claude 3.7 Sonnet?
Unless you’re a techie, it may not matter. The key is for business leaders to look beyond the buzzwords and the alphabet soup of model types to realize the use cases of AI. Doing so can be an important part of keeping up with the competition, as a McKinsey study has found that 78% of organizations already use AI in at least one business function.
My company has embraced AI, but as a tech company, that’s not too surprising. What is interesting is the fact that our customers are starting to use AI, unearthing some real productivity benefits. These are trucking firms that haul shipments to and from seaports and railyards—a sector known as drayage. It’s an old-school industry that often relies on traditional methods like phone calls, emails and spreadsheets.
If an old-school industry like drayage can start to embrace AI, I am confident that you can find value in it, too. You just have to take a few steps to move past the hype and identify how AI works specifically for you and your business.
Use Cases: How Trucking Companies Are Using AI
Raise your hand if your inbox can get … a little messy. Now imagine you manage a trucking business and your email fields hundreds of queries a day from current or prospective customers, sharing details on shipments, where they’re going, where they’re coming from, negotiating rates, status updates, etc. Managing that manually takes a huge amount of time, which is why many are adopting AI tools that integrate with their Gmail or Outlook to help with inbox management.
Planning, routing and dispatching truck shipments is another area that is like putting together a giant puzzle piece. Dispatchers have to do a ton of manual work to figure out which load to move when; which driver is best suited for the load; and how to manage the schedule to accommodate weather delays, traffic congestion, equipment failures, etc. Dispatchers often spend hours and hours doing this. With AI, however, some of the trucking companies I’ve worked with can now generate a schedule and route plan identifying which drivers are best suited for each trip. Suddenly, a job that took hours can be done in minutes.
As you can see, none of these examples feel pie-in-the-sky or overly futuristic. I’m not talking self-driving trucks—these are actual use cases happening today, and the benefits are already coming to fruition.
Three Ways To Make AI Work For You
AI is a versatile tool, which is what makes it so powerful for many different types of businesses. Maybe you can draw inspiration from the way our drayage trucking customers are using AI. If your inbox is full of customer inquiries, could AI manage it? If your industry deals with frequent, last-minute changes, would an AI-based system help?
Here are a few steps you can take to figure out the best ways to apply AI tools that suit your business’ unique needs.
1. Talk to end users to find the pain points.
In my experience, AI works best when it’s used to solve an existing problem, so pinpoint your business’ biggest challenges. The best insights often come directly from the people who handle tasks daily. They know where the hiccups and inefficiencies are because they deal with them every day. A lot of the AI applications my company offers came about because of conversations with our customers, in which they noted the difficulties with replying to customer emails or scheduling appointments on time.
2. Clearly define metrics.
If you use AI to save time, there’s one sure way to know if it is working: calculate the time saved. For example, drayage teams can measure how long a manual process took before AI versus after to calculate how many hours or days of work they are saving each year. Defining key performance indicators (KPIs) before an AI project, and then checking in with the metrics along the way, can make it clear if AI is solving your challenge or if it’s just creating more work.
3. Communicate how AI changes things.
One of the biggest misconceptions about AI is that it’s a job replacer. I’ve found that this sentiment is beginning to lessen, but 32% of workers in a Pew Research Center survey still think the tech will lead to fewer job opportunities. Yet, in my experience, AI can actually make us more productive and free us up from monotonous tasks.
When employees and customers understand that AI is a collaborator, not a competitor, they’re more likely to embrace the technology. Eventually, you may find your team wondering why the company didn’t jump on the AI bandwagon even sooner.
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