The Reality Check: AI’s Second Act in Supply Chain
The AI in supply chain revolution isn’t coming—it’s already here. After years of inflated promises and “AI washing,” logistics leaders are finally moving beyond buzzwords to practical, value-driven transformation. Aaron Hatfield, Director of Sales at Arvist AI, has a front-row seat to this evolution, helping warehouse operations use computer vision to solve real problems instead of chasing hype.
The Current State: Volatility as the New Normal
Volatility has made AI in supply chain management more than a trend—it’s an operational necessity. Before diving into solutions, it’s important to understand the environment AI is responding to. Labor shortages persist, tariff uncertainty disrupts planning, and consumer demand keeps shifting.
“We’re shifting, and it’s uncomfortable,” Hatfield admits. “Everyone wants the right answer, but the truth is, the market keeps changing.”
This turbulence is reshaping operations. Tariffs are spurring a quiet resurgence of American manufacturing, while rising international shipping costs push consumers back toward domestic sellers. That volatility fuels innovation—from reverse logistics to upcycling—as companies reimagine efficiency and sustainability.
According to Gartner’s B2B Buying Journey report, decision-makers now expect partners to prove value fast. For supply chain operators, AI isn’t a novelty; it’s a necessity.
Computer Vision: The Practical Face of AI
Arvist AI exemplifies the new wave of applied intelligence. Rather than forcing companies to rebuild their tech stack, it layers computer vision onto existing infrastructure—cameras, sensors, ERP, and WMS systems—to capture and analyze operational data.
“We overlay on existing hardware,” Hatfield explains. “We augment cameras on pallet wrappers to pull labels, detect damage, and document issues before goods even load onto the truck.”
Two key modules lead adoption: safety and quality. Cameras spot near misses or safety violations in real time, generating automatic OSHA documentation. On the quality side, they verify labels and packaging, catching costly errors early.
Results are measurable: one customer reduced a three-person quality-assurance team to one, reallocating talent to revenue-producing roles. It’s not job elimination—it’s job elevation.
The Human Element Remains Critical
Even the smartest systems depend on people. “We don’t do facial recognition,” Hatfield emphasizes. “We gather context, not personal data.”
That distinction matters. Transparency and gradual onboarding prevent the perception of surveillance. “Technology adoption is like the tortoise and the hare,” Hatfield says. “Go systematically, educate, and evolve.”
At Virago Marketing, we see the same principle in communications: change only works when people understand the “why.” The best AI adoption strategies, like the best marketing strategies, combine empathy with execution.
Learning from Past AI Failures
Early hype around AI in supply chain technology created inflated expectations and inevitable disappointment. “There were a lot of false promises,” Hatfield concedes. “It was a race to the bottom—everyone wanted to be first.”
That rush to market bred deep skepticism across the industry. But today’s leaders are taking a different path. Modern AI companies are rebuilding credibility through education, transparency, and proof—not hype. “People don’t want to be pitched,” Hatfield explains. “The value should reveal itself in conversation.”
It’s a shift that mirrors the evolution of B2B marketing in logistics itself: trust is now earned through clarity and expertise, not volume or noise.
The Sales Evolution in Technical Markets
Selling AI solutions requires a different approach than traditional supply chain sales. Hatfield looks for “technologist translators” who can bridge the gap between complex AI capabilities and practical business needs.
“I want earners, I want people who are curious, and I want people who are able to get down in the trenches,” he explains. “Some of my favorite sellers are the ones that can throw on a pair of boots and go talk shop.”
This represents a broader shift in B2B sales toward relationship-building over transaction-focused approaches. “Relationships bring customers for 25 years. Transactional check-a-box brings customers for five years,” Hatfield notes.
The technical nature of AI sales also requires deeper product knowledge. “Read, learn, sit with your engineers. People hate being pitched. You have to get past this pitch-slapping mentality.”
The Partnership Imperative
In today’s connected supply chain, point solutions don’t cut it. “We’re seeing partnerships,” Hatfield notes. “Instead of stepping on each other’s feet, work together in the ecosystem.”
That same mindset shapes successful client relationships. “We invest together—we’re only successful if they are.” Collaboration, not competition, fuels long-term adoption.
New Models, New Categories
Rapid innovation is blurring old boundaries. “Do we really need a TMS,” Hatfield asks, “or is there a platform that covers that functionality?”
He envisions service-based frameworks—“logistics as a service” or “computer vision as a service”—reflecting AI’s ongoing evolution. The theme: specificity over spectacle. “AI has to fill a real need,” Hatfield says. “Otherwise it’s just a cool toy.”
The Education Gap
Technical hurdles aren’t AI’s biggest barrier—understanding is. “There’s not as much fear of technology as confusion,” Hatfield says. “What is computer vision? What are LLMs?”
That gap creates opportunity for informed partners who can educate without overselling. “If an AI company won’t say, ‘We’ll have to think about that,’ run.” Honesty is the new differentiator.
Lack of education—not fear—is slowing AI in supply chain adoption.
Practical Steps for AI Implementation
For companies exploring AI in supply chain, Hatfield advises starting small. Define one clear, valuable use case—like damage detection or near-miss reporting—and expand gradually.
“Incrementally update and educate,” he says. “Connect with people on the ground and mitigate fears.”
Pro Tip: Treat AI rollout like any transformation initiative—align leadership early, communicate consistently, and measure outcomes in business terms.
The Bottom Line: Value Over Hype
As the hype cycle fades, AI’s future looks refreshingly practical. Companies succeeding today solve specific problems, empower workers, and prioritize trust.
“I have no desire to be mediocre,” Hatfield says. “When I wake up every morning, I’m going to give it all I’ve got.”
That mindset defines the real revolution: not algorithms, but accountability. In the end, AI in supply chain isn’t about replacing people—it’s about freeing them to do what humans do best: think, create, and build relationships that last.
Learn how Virago Marketing helps logistics brands translate complex technologies into measurable market impact.
Watch Aaron Hatfield’s full interview on YouTube.
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A podcast where freight, logistics, and supply chain leaders come to talk real marketing.
