Artificial intelligence (AI) has moved beyond a futuristic concept to become a tangible tool in logistics operations. However, experts agree that the biggest challenge is not technological, but cultural and strategic.
In the panel “Generative Artificial Intelligence and Logistics ,” organized by the National Council of Executives in Logistics and Supply Chain (ConaLog) , Felipe Ordóñez, CEO of Promologistics , opened the conversation by highlighting that many companies already use AI in their daily lives, but have not yet managed to bring it to business processes.
In this context, Antonio Rivero, CEO of e-Kontrol , pointed out that the most common mistake is implementing artificial intelligence because it’s trendy rather than necessary . He explained that the starting point should be identifying operational constraints, repetitive processes, and areas where frequent errors occur. He also emphasized that data quality is fundamental.
“The tool will give you results based on the information you provide,” he emphasized.
For Gustavo Equihua, CIO of Frialsa , the first step is to break down mental barriers within organizations. He indicated that many executives still feel resistance or even embarrassment when using AI tools, when in reality they should see it as an assistant that enhances analytical capabilities.
“You won’t stop thinking; artificial intelligence is like a coach that helps you reflect and find solutions faster,” he said.
The panelists agreed that the biggest obstacle to implementing AI is not the model, but the quality of the information.
Gustavo Equihua explained that even with a data lake (data storage in one place), the problem usually originates from the data capture.
“If the input is incorrect, the result will also be incorrect. The ‘garbage in, garbage out’ principle still applies,” he said.
From a business perspective, Carlos Guerra, commercial director of IGSA Medical, emphasized that the key to securing funding is translating artificial intelligence into tangible results. To convince senior management, he recommended demonstrating current losses that AI can prevent, measuring improvements in time and processes, and showcasing clear economic benefits.
“When you speak in financial terms, you capture the attention of decision-makers,” he explained.
Will AI replace jobs?
One of the most debated topics was the impact on employment. Antonio Rivero pointed out that the real risk is not losing jobs, but falling behind in skills.
“The difference will be between the professional who uses artificial intelligence and the one who doesn’t. The former will displace the latter,” he stated.
In that sense, the panelists agreed that companies must promote training and cultural change to take advantage of this technology.
Paradoxically, some studies show that AI does not reduce the workload, but rather increases productivity and the level of demand.
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