How AI Is Optimizing Trucking Operations

A lot can change in a year, and artificial intelligence (AI) is the perfect example.

“Artificial intelligence has been in the market for a lot of years, but it’s been the past year that the space has been revolutionized,” Jaime Tabachnik, co-founder and CEO at trucking FinTech Solvento, tells PYMNTS for the “AI Effect” series.

“The most revolutionary advance is the ability of these models to understand our language … it democratized the access to these advanced models and the use of them by the retail customer,” Tabachnik says.

This breakthrough has created high expectations for AI on traditional industries, including the trucking and transport sector, which have been slow to adopt new technologies.

“AI at its core is an optimization model, trying to optimize a set of variables … and within transport, where companies are moving goods from point A to point B, it provides a context where AI will be very effective,” Tabachnik says.

He explains that AI can automate repetitive tasks and leverage data to make better decisions, streamlining workflows and reducing costs. One significant application of AI is within freight matching, where AI algorithms can be leveraged to optimize the matching of carriers and shippers, leading to more efficient and profitable operations.

Still, Tabachnik emphasizes that within the trucking industry, most of the players are managed by very traditional people that have been in these industries for generations and have not yet implemented these advanced technologies into their day-to-day operations.

But an ongoing generational — and behavioral — shift promises to change all that.

Transformative Opportunity

The transport industry plays a vital role in global commerce, and AI can play a similarly vital role in streamlining historical frictions and removing long-standing legacy bottlenecks by applying intelligent solutions and surfacing data-driven insights in real time.

“A lot of the tasks done within the industry on a daily basis can be automated, first of all. And second, you can leverage on data to make better decisions to optimize your products,” Tabachnik says. “Optimizing efficiency and reducing waste in the system will eventually result in greater profits for everyone.”

Freight auditing, a traditionally manual and error-prone process, is another attractive area where AI can transform positive outcomes, he adds.

By automating the auditing process, companies can eliminate costs, improve accuracy, and mitigate the risk of fraud.

“Almost every company in Mexico at the moment is performing this auditing process in a manual way, literally reviewing piles of paperwork with their own eyes,” Tabachnik says. “The probability of making mistakes is huge. … With technology, we can mitigate that risk entirely.”

Challenges in Adopting AI

Tabachnik acknowledges that skepticism and resistance to change are significant challenges in disrupting traditional industries. Educating decision-makers and demonstrating the capabilities and benefits of AI is crucial. However, the timing for AI disruption in the transport industry is favorable, with a growing curiosity and awareness of AI’s potential.

Still, he adds that allowing companies to adopt AI solutions gradually is crucial to reducing resistance to change, saying that “creating a solution that is modular and can be implemented in pieces and in sequence is the right way to go to mitigate the friction and the resistance of change that we’re going to face.”

“There’s a lot of decision makers in the biggest companies that are just too afraid to change the way they’ve been working for the past 40 years or more,” Tabachnik explains.

Read more: Trucking FinTech Solvento Secures $50 Million Debt Facility, Launches AP Automation

He notes that in the U.S., using AI technology to do freight auditing and automate payments is already a mature category, and it’s “already the mainstream and the best practice,” which will in turn help push firms in Mexico and Latin America to adopt AI technology in order to streamline business relationships.

By automating processes, optimizing operations, and enhancing decision-making, AI can drive significant cost savings and improve profitability in the transport industry.

“The timing to disrupt these traditional industries with AI and automation couldn’t be better than today,” Tabachnik says.

While full automation may not be feasible in the near future, Tabachnik believes AI will act as a co-pilot, enhancing human intelligence and decision-making. He cites examples of remote driving and AI-assisted logistics, where technology and human interaction work together to improve efficiency, emphasizing that AI will be disruptive by making humans more powerful and efficient, providing advanced capabilities and freeing up time for more critical tasks.