Why Email And Phone Automation Are Becoming Trucking’s Most Practical AI Entry Point

In trucking, the inbox often is the system. Dispatch, load sourcing, paperwork, and updates all flow through email and phone calls, not formal software platforms. That makes AI most powerful at the point of lowest digital maturity. By automating the inbox and the call queue, carriers can turn unstructured communication into usable workflows and capture efficiency before trucks ever go empty.

We spoke with two leaders on the front lines. Tapan Chaudhari is the Founder and CEO of Hey Bubba, an AI-native voice dispatch platform for carriers. He previously founded TruckX, a successful fleet management software company, giving him a dual perspective as both a technologist and an industry insider. He is joined by Gabriel Ribeiro, Hey Bubba’s Senior Director of Partnerships and Marketing, who provides the company's commercial and operational perspective with over 15 years in transportation and freight tech.

"If your business runs on email and phone calls, that’s the lowest-hanging fruit. That’s where AI actually saves time today," says Chaudhari. That reality is becoming more acute. Small carriers face a difficult economic market that demands new efficiencies while also contending with larger, tech-savvy brokers who have been using AI for years.

• Survival of the smartest: As AI begins to reshape supply chains, these larger firms can thrive in downturns, creating a competitive gap. It's a challenge well-suited for practical automation that transforms digital noise into a structured workflow. "Because the market has been so bad, carriers are focused on improving operational costs to stay profitable," Ribeiro explains. "They are becoming very open-minded towards AI, partly because they've already had to engage with it on the broker side. We're seeing a trend now where carriers are more curious and adopting it more than ever before."

• Loads while rolling: "If you're a driver on the road, your only opportunity to search for the next load is when you stop at a truck stop," Chaudhari says. "Or you have to rely on an outsourced dispatch service, or even family members to do the job for you. That's where AI comes in. It can search for and book the next load while you're still driving, before you're even empty."

• Not yesterday's LLMs: But the journey to adoption often requires addressing operator skepticism. "Many people disregard the new wave of large language models because of a bad experience they had scanning a document five years ago," Chaudhari notes. "I encourage them to revisit the technology, because it has changed so significantly."

Building confidence often comes down to seeing the technology work correctly on familiar, real-world tasks, a challenge for any organization where workers don't inherently trust AI. Ribeiro notes that the adoption journey varies, with some operators "crawling" as they build confidence before they are ready to "run" with full automation.

• The magic moment: "We had a customer whose driver took a picture of a bill of lading with a reflective metal seal on top of it. This seal has an engraved number, but it’s hard to read because of the reflection," Chaudhari recalls. "When our AI took that image and transcribed everything perfectly, including the seal number, that's the moment of disbelief. When they see that, they’re like, ‘Oh, this is crazy.’ That’s when they realize the power of the technology."

• From noise to signal: What changes first is not strategy or analytics, but the quality of information operators can actually act on. "AI converts inbound broker emails into structured, searchable opportunities," he adds. "Suddenly, those email blasts that had a 1% or 2% hit rate can jump to 60% or 80% if there's a match."

The company’s product-first philosophy is informed by its own extensive internal use of AI. That AI-native culture is a key driver of their speed, allowing them to rapidly build custom AI applications and other internal tools. Their advice for leaders focuses on asking the right questions to pierce through vendor hype and avoid a broken buying process.

• Under the rug: Chaudhari suggests leaders probe the difference between a "services" model, which automates existing messy workflows, and a "product" model designed to reimagine them and unlock true agentic value. "That services-first approach leaves you in the same messy situation; you’ve only introduced another tool on top of it," he warns. "The tool may act like a human writing an email or making a call, but your underlying processes haven’t changed."

• The AI committee: "I've seen success with companies that create an internal AI committee with representation across different departments," Ribeiro advises. He adds that you need a dedicated owner, like a project manager, who can manage the implementation, while the committee as a whole should be responsible for managing AI-related risks.

But for Chaudhari, the mission is bigger than operational efficiency. He describes the adoption of smarter technology as a moral imperative to save lives. "These crazy accidents we see today should be gone," Chaudhari concludes. "The truck cannot just go straight because the driver was sleeping; the truck should have stopped. I think there should be laws requiring trucks to have automatic stopping capabilities. It's not even about full self-driving. Just because of human error, these accidents should not happen."