Adam McElhinney, the CEO of Uptake Technologies, a predictive analytics company, said he expects more companies will turn to the power of AI over the next decade to optimize data, leading to more informed decisions.
Speaking with FreightWaves CEO Craig Fuller on Thursday at FreightWaves’ F3: Future of Freight Festival, McElhinney discussed the future of AI in logistics. McElhinney’s company helps businesses transform data into insights that help them make better decisions to minimize unexpected downtime.
McElhinney, who has been working in machine learning for 20 years, said AI is here to stay and will be even more deeply integrated into logistics companies within the decade. He recommended companies that are curious about AI consider what problems they hope to solve and determine if AI would be the best solution.
“You’re going to see a lot more chat interfaces, voice interfaces,” he said. “You’re going to see all that unstructured data that we’re all sitting on — work orders, random Excel files, documents — become queryable, identifiable, and all that will have a positive impact on the industry in general.”
He pointed out large language models (LLMs) as an opportunity for fleets. Important data about trucks can be hidden in the comments, notes and messages that go back and forth in a company, rather than just work orders themselves. The LLM can examine and structure that data in a searchable way, which McElhinney said enables customers to use their own data to predict failures or breakdowns — leading to big savings by avoiding unexpected costs.
McElhinney also said AI can be handy for search. Large organizations have data scattered across the entire company, from emails to Excel spreadsheets to Word documents. AI can unify and organize that data in a central location, giving employees the ability to search all the documents.
An example of this is how Uptake Technologies merges truck data with work order data and uses it to determine truck issues and how to streamline maintenance. The company has been performing substantial analysis on tire failures. The insights gleaned identify and address tire-related issues, which the company said had led to an 83% drop in significant tire failures among clients.
McElhinney said the company is excited about analyzing asset life cycles and how fleet owners determine when to retire trucks.
“We solve one problem for our customers, and that’s we reduce unplanned downtime,” he said. “So how we do that is by leveraging AI. … Typically, we can reduce unplanned downtime 10 to 40% — something in that range.”
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