The AI conversation in logistics has shifted from hype to hard reality, according to a prominent industry CTO. In the latest installment of the Lean Quarterly Dive with FreightWaves and Lean Solutions Group (LSG), Alfonso Quijano, chief technology officer and co-founder at LSG, said the era of unchecked experimentation with artificial intelligence is finished, and companies that lack mature technology foundations are paying the price.
The End of the Experimentation Phase
For much of 2025, frontier AI labs promised that agentic workflows would remake entire job categories, but Quijano said that promise didn't land as pitched. According to FreightWaves, Quijano observed: “I’m seeing that the experimentation phase is mostly over. You tried it, you went into it without a lot of experience. Companies that didn’t have technology teams found themselves investing a ton of money into AI to see if it worked for them.”
Broad access to AI platforms such as OpenAI and Claude did not eliminate the need for operational basics. Quijano told FreightWaves: “Even if the technology had democratized access and everybody could download OpenAI and Claude, it doesn’t mean that you’re an AI company. You actually need good project management. You need good change management. You need to have good control of your costs. Who knew?”
The ‘Vibe Coding’ Cautionary Tale
The rise and fallout of “vibe coding” — using AI to generate software with minimal traditional development — served as a stark warning. Quijano cited a published statistic: “An independent publisher put out that 99% of vibe coded apps are in the garbage. [These apps] are not making any money. They get published and then get unpublished from the infrastructure platform.”
The lesson, he said, is that speed of creation does not equal business value. “Garbage in, garbage out. Even if it’s faster to create technology, that doesn’t mean that you’re going to create more businesses,” Quijano stated.
Brittle Applications and Hidden Damage
Applications built hastily during the AI wave often proved fragile under real-world conditions. Quijano described them as appearing to work “but in reality it’s very brittle. When you apply it in real life and in production, it can cause some pretty important damage within your business.”
Rather than chasing AI-first branding, Quijano argued for a more mature approach: treat AI as one component within a broader automation strategy, deployed only where it adds value. “It’s better for AI to be present but not talked about than the other way around,” he said. “You kind of have to make it invisible for it to be adopted as it should within organizations.”
AI Used for the Wrong Problems
Many companies, according to Quijano, have wrapped AI around problems that once had straightforward, rules-based solutions. “You’re taking something that would have otherwise been pretty simple and now using AI for it, and the unpredictable nature of the outcome is causing issues. You’re kind of better off saying, ‘I’m going to bring automation into my company’ rather than being an AI-first or AI-native solution. That automation can have AI components when it’s necessary, but no more than that.”
Treat AI as an Employee, Not a Tool
Quijano offered a conceptual shift: treat AI not as software to configure, but as personnel to onboard. “I don’t think it’s a tool. I think it’s an employee. What do you do with a junior employee that joins your company? You train them. You ensure that you give them a very defined job description so that they know exactly what they need to do.”
That means documented processes, exception handling, and ongoing training. “You need a very defined SOP. You need to ensure that your process is well-documented and that you account for potential errors in the process. Exception management. You need to have continuous training. You need to close the loop,” Quijano said.
Lean Solutions Group has been building that closed-loop infrastructure directly into its own technology stack, though specific product details were not disclosed.
Implications for Logistics and Supply Chain Technology Leaders
For CTOs and digital transformation leaders in supply chain and logistics, Quijano’s message is clear: AI is a powerful but limited tool that must be embedded within disciplined automation frameworks. The experimentation phase that consumed 2025 has given way to a focus on fundamentals — project management, change management, cost control, and robust process documentation. Companies that treat AI as an employee with clear SOPs and exception handling will outperform those that chase the next frontier AI promise without the underlying operational maturity. The shift from “AI-first” to “automation-first with AI where needed” aligns with the practical realities of global trade technology, where reliability and predictability are paramount.
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