Six in 10 transportation leaders believe autonomous agentic AI will act on their behalf within the next five years, but just 37 percent of surveyed organizations have “deeply” integrated artificial intelligence and machine learning into their current transportation management systems (TMS). That’s according to data from supply chain technology company Manhattan Associates and research firm Vanson Bourne.
While transportation leaders seem to believe in the promise AI could bring to their organizations, they also acknowledge that there are adoption issues that could bar them from implementing agentic AI systems rapidly. Just under half of leaders surveyed said they’re highly prepared for AI agents to be in place by 2030, but about half of organizations expect to face skill shortages while integrating the technology. Forty-four percent of leaders said they would be likely to face integration holdups and an additional 44 percent cited questions of data quality and availability.
All of those issues are common as organizations work toward a more technology-focused future; some have already adopted simpler AI systems to help their work along, but many still lack maturity compared to those in their market. Six in 10 organizations use AI-integrated sales and operations planning systems, and more than half use predictive analytics. But markedly fewer organizations cited using quick-turnaround AI tools, like historical trend analysis (38 percent), automated booking (36 percent) and real-time demand sensing (35 percent) technology for those tasks.
But as organizations across industries continue to invest in, and rely on, transportation management—particularly against the backdrop of a consumer demanding speed and supply chain costs fluctuating because of political changes—business’ interest in transportation has started to see an uptick. While 78 percent of leaders said their organization sees transportation management as a necessity for success today, 86 percent said they know it will be a strong priority by 2030.
But transportation transformation still has competing priorities; for instance, nearly seven in 10 leaders said sustainability remains a top priority for their organization. Simultaneously, organizations continue to struggle with insight into their transportation strategies; half of respondents said they have trouble preemptively rerouting shipments as needed, and about half of respondents are actively grappling with the best way to schedule dock and warehouse workers.
While agentic AI may be positioned to help companies handle multiple priorities simultaneously, Bryan Smith, director, transportation management systems at Manhattan Associates, said the best way forward is to begin adopting helpful technology now.
“Eighty-seven percent of respondents anticipate that challenges in areas such as operational visibility, AI adoption and sustainability compliance will intensify, leaving their current transportation management systems struggling to keep pace. Failure to act now will expose organizations to rising costs, questions over long-term efficacy, and the risk of falling short of customer promises,” Smith said in a statement.
The benefits of beginning early could incentivize companies to work toward at-scale adoption; more than 80 percent of leaders said they believe that technology advances could decrease the cost of freight by at least 5 percent by 2030. What’s more, six in 10 companies indicated that stronger visibility and insight into transportation systems fosters stronger satisfaction among customers.
Smith said whether or not companies choose to change alongside it, the market will continue to shift. Manhattan recognizes that many organizations have a ways to go on implementation, but that, in order to stay relevant with customers, companies need to consider prioritizing technology before they fall behind competitors.
“Modern transportation management demands organizations balance a range of competing priorities, and the research clearly illustrates many organizations are still unprepared to meet the challenges of evolving sustainability mandates, expectations around AI and the need for more visible, actionable data insights. Looking ahead to 2030, these demands will intensify, increasing the pressure on organizations to operate transportation operations in smarter more intuitive ways,” Smith said.
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