91% of orgs boost AI spending but 54% can’t deploy logistics tools

A new study from AI logistics company Pando and supply chain consulting firm JBF reveals that while 91% of organizations have increased AI spending over the past two years, 54% still haven’t figured out how to actually deploy these tools in their logistics operations. This disconnect highlights a critical gap between AI investment enthusiasm and practical implementation in supply chain management, where companies are struggling with data quality issues and change management challenges despite recognizing AI’s potential to navigate increasingly complex global logistics networks.

The big picture: Companies are caught in an AI investment paradox where financial commitment far outpaces strategic execution.

• Despite nearly universal increased spending on AI technology, more than half of organizations remain in the planning phase for logistics AI deployment.
• The logistics industry faces mounting pressure to modernize as supply chains operate in real-time environments where “a single disruption can overturn a company’s entire operations overnight,” according to Abhijeet Manohar, Pando’s chief technology officer.

Key barriers: Poor data quality emerges as the primary obstacle, followed by limited technology systems and change management challenges.

• However, 92% of respondents believe AI can help them navigate complex logistics systems, indicating strong confidence despite implementation struggles.
• Regulatory compliance concerns affect 42% of companies, though AI systems are increasingly capable of adapting to evolving requirements through built-in governance frameworks.

Talent shortage solutions: Organizations are turning to AI agents to address workforce gaps, with 58% citing talent shortages as a major barrier.

• AI agents are being deployed to automate routine tasks, allowing teams to accomplish more with fewer people.
• Rather than eliminating jobs, the report suggests AI is “redefining” roles by shifting human workers toward higher-value activities.

What they’re saying: Industry leaders emphasize that AI adoption has moved beyond optional to essential for supply chain resilience.

• “Supply chains no longer operate on a nine-to-five schedule; they move in real time,” said Manohar. “In such a volatile, uncertain, complex and ambiguous world, AI adoption in supply chain and logistics is no longer optional; it’s foundational to resilience.”
• “What makes this moment different is the emergence of Agentic AI – systems that can operate autonomously within organizational guardrails, take proactive decisions and collaborate with humans in real time,” Manohar added.

In plain English: Agentic AI refers to artificial intelligence systems that can work independently within company rules, make decisions on their own, and collaborate with human workers in real time—essentially acting like digital assistants that can think and act rather than just follow pre-programmed instructions.

Enterprise response: Large companies are building dedicated capabilities to bridge the deployment gap.

• 38% of large enterprises have established data science teams specifically for developing custom logistics AI tools, often collaborating with specialist vendors.
• Leading organizations are deploying AI in targeted applications rather than waiting for perfect conditions, using early implementations to drive broader transformation.

Looking ahead: The study identifies three key themes shaping AI’s future in logistics: competitive operational advantages, human-AI collaboration redefining worker roles, and improved interoperability between networks.

• The report emphasizes that embracing AI as a core business strategy component is crucial for companies seeking resilience and competitive advantage in today’s complex global supply chains.