New research from Info-Tech Research Group finds that transportation and logistics organizations are struggling to turn AI pilots into measurable results.
According to the study fragmented systems, legacy technology, workforce resistance and unclear ROI continue to limit progress.
Michael Adams, senior research analyst at Info-Tech, said organizations often face difficulty determining which AI use cases matter most and how to scale them beyond isolated pilots.
“AI has emerged as a compelling enabler in this shift. As capabilities mature, they offer transportation companies new ways to address long-standing operational challenges, from network optimization and asset utilization to risk management and customer experience,” he said. “However, while interest in AI is high, many organizations struggle to determine where to begin, which use cases matter most, and how to scale initiatives beyond isolated pilots.”
The research outlines a four‑phase plan to help identify capability gaps, match pain points to AI use cases, assess maturity across governance, data, people, process and technology, and prioritize opportunities based on business value and feasibility.
Info-Tech says the approach can help transportation organizations shift from disconnected pilots to AI portfolios that support network optimization, asset utilization, risk management and customer experience.
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