By Eva Richardson | The Logistic News
April 8, 2025
Despite surging investments in artificial intelligence and automation across the logistics sector, a new report has revealed a critical disconnect: over 60% of companies are spending on AI—but many say it’s not working as intended.
The findings highlight a growing divide between the promise of smart technology and the realities of implementation. Nearly half of companies surveyed cited a lack of internal skills and strategic planning as the primary reason their AI initiatives have stalled or underperformed.
The Investment Surge—and the Execution Lag
The past three years have seen an explosion in AI deployment across supply chains, from predictive maintenance to autonomous inventory management and route optimization. Yet, for many firms, the ROI remains elusive.
“Logistics companies are rushing to adopt AI solutions, but without the necessary change management and training, these tools are falling short,” explained a senior analyst at the research firm behind the report.
Skills Shortage: The Silent Roadblock
The gap isn’t in the technology—it’s in the talent. AI tools require users who understand both the logistics landscape and the underlying data science principles. However, many organizations lack data-savvy teams or have not invested adequately in upskilling existing staff.
Only a fraction of the surveyed firms reported having in-house AI expertise, and even fewer had clearly defined strategies for integrating AI into their workflows.
Culture and Change Management Missing from the Equation
Beyond skills, organizational culture is a key barrier. Many companies underestimate the shift in mindset required to adopt AI—not just using new tools, but trusting and acting on algorithmic recommendations.
“Technology can only take you so far,” said a supply chain transformation consultant. “If your workforce isn’t aligned or confident in AI outputs, the adoption curve will be steep and painful.”
Bridging the Gap: What Needs to Change?
The report outlines several recommendations to turn underperforming AI investments into high-impact outcomes:
- Prioritize training and cross-functional collaboration to ensure tech teams and operational leaders are aligned.
- Start small and scale strategically, piloting AI in specific processes like demand forecasting or warehouse slotting.
- Appoint AI champions within teams to drive adoption and troubleshoot challenges early.
- Focus on data governance and quality, ensuring clean, consistent inputs into AI systems.
Looking Ahead: Rethinking AI as a Strategy, Not a Tool
AI is not a plug-and-play solution—it’s a long-term strategic capability. Companies that treat it as a business transformation journey, rather than a one-time software upgrade, will be best positioned to unlock its full value.
“Success with AI starts and ends with people,” the report concludes. “When logistics firms combine digital ambition with operational fluency, the results can be game-changing.”
Conclusion: Technology Alone Isn’t Enough
As logistics companies double down on AI to gain efficiency, resilience, and visibility, they must also invest in the human side of the equation. Only then will their digital tools evolve from costly experiments into competitive advantages.
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