For logistics and transportation organizations, automation is already delivering measurable value across warehouse operations, routing, customer communications, and disruption response. Against a backdrop of global trade instability, rising fuel and labor costs, and ongoing staff shortages, automation has become a primary lever for operational resilience.

According to a new survey of transportation and logistics leaders, 93% of organizations report increased business growth due to process automation over the past year. On average, 45% of business processes are automated today, with leaders expecting that figure to rise to 62%. Investment confidence is strong, with 82% planning to increase automation spend and budgets expected to grow by an average of 20% over the next two years.

Supporting complex transportation and logistics environments

As automation expands, the reality of how logistics work gets done has changed. Modern processes no longer run through a single platform or team. They span transport management systems, warehouse platforms, telematics, IoT devices, external partners, regulatory checkpoints, and increasingly, AI-driven tools.

Organizations now manage an average of 47 endpoints within their automated processes, and that footprint is growing by 14% year over year. More than three-quarters of leaders say the volume and diversity of endpoints are increasing exponentially. Regulatory complexity, branching logic, legacy systems, and human handoffs all contribute to environments that are difficult to change and even harder to govern.

The high risk of complexity

Rising complexity is not just a technical issue. It changes the risk profile of automation. Top contributors to automation complexity include contending with global regulatory compliance (77%), challenges with branching and conditional logic (61%), and difficulty integrating with legacy systems (50%).

As a result, 86% say they need better tools to manage how processes intersect, while 58% say they lack sufficient visibility and control once automation is running. Without that visibility, scaling automation increases organizations’ risk exposure, making it harder to build resilient  and trustworthy automated systems.

Are production-ready AI agents a far-off reality?

As AI agents move from experimentation into everyday logistics work, there’s far less room for error. AI is expected to play a growing role in demand forecasting, predictive maintenance, planning, and exception handling. Its potential goes even further. For example, AI can help logistics organizations improve routing efficiency to support sustainability goals, while integrating IoT devices and telematics to securely share real-time data across partners and networks. Adoption reflects this promise, with 74% of logistics and transportation organizations using AI agents in some capacity.

Yet progress to production remains limited. Only 11% of agentic AI use cases reached production in the past year. Three-quarters of leaders say there is a significant gap between their vision for agentic AI and the reality today.

The limiting factor is not what AI agents can do, but whether organizations trust them to do it safely. Logistics leaders cite business risk, lack of transparency, and compliance concerns as the main barriers to wider adoption. Nearly half believe poorly governed AI risks amplifying broken processes rather than fixing them.

As a result, most agents remain confined to low-risk roles: 72% say their AI today functions primarily as chatbots or assistants, rather than operating inside mission-critical, end-to-end business processes.

The importance of orchestrating AI agents

The biggest emerging trend is a shift in how leading organizations think about AI in operations. Rather than deploying agents in isolation, they are focusing on how agents participate in governed business processes alongside their existing people, systems, and devices.

Ninety percent of respondents say AI must be orchestrated like any other endpoint within automated processes to ensure compliance, while 89% agree orchestration is required to realize the full value of AI investments. For logistics and transportation organizations, this approach enables agents to adapt to disruption in real time while operating within clear guardrails.

From agent pilots to enterprise-grade logistics automation

Most transportation and logistics organizations already have adopted AI agents for simple tasks. The next phase will be incorporating these agents into trustworthy, observable, and governed processes.

Organizations that build a strong foundation will be able to scale automation safely, integrate AI into core operational workflows, and turn agentic AI from isolated pilots into durable, production-grade capabilities. When it comes to agents, more is not more. The focus should be on coordinating agents within systems that are designed for control, resilience, and change.