The report found that while over half of companies surveyed have active gen AI implementations, they tend to be limited and focused on a few aspects of the business. Core operational areas, such as supply chains and strategy and operations, have received the most attention.
Many also report implementations in sales and marketing, but this varies widely across subcategories within transportation.
Nearly all transportation executives surveyed (99%) expect the technology to transform their industry—but more than two-third (71%) expect this transformation to take more than three years, which is slower than several other industries.
While the focus of Gen AI backed insides varies by company type, the most common are improved traceability (75%), enabling dynamic supply chain decisions (74%) and improved inventory efficiency (67%).
The transportation use cases seeing the highest adoption and impact are asset management, route optimization and warehouse operations.
Even with these various use cases nearly all respondents report feeling unprepared to adopt AI from risk, compliance, and talent perspectives. Most lack even limited implementations for back-office functions such as IT, HR, and legal.
Significant barriers to adoption include technology infrastructure, risk and governance, and talent. At the same time, data-related pitfalls represent the biggest risks on executives’ minds, as 40% cited misuse of data as their number one gen-AI-associated risk. Risk management (39%) and governance (33%) are among the largest barriers to Gen AI adoption in transportation, even in large companies. Data also stands out as a top risk factor for 4 in 10.
Deloitte found higher success rates reported for more qualitative goals – such as uncovering new ideas and insights and encouraging innovation and growth. More than half of companies surveyed are running gen AI initiatives within each of these use cases, and roughly 80% of adopters report extremely high or high economic value in each use case. Meanwhile, more financial-oriented benefits, such as improved efficiency and reduced costs, still lag.
