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The integration of AI into global supply chains is poised to sever the traditional entry-level roles of the corporate ladder as companies move beyond simple automation toward autonomous decision-making systems.
A report released this week by Gartner indicates that the shift toward agentic AI—systems capable of taking independent action to achieve goals—is fundamentally altering workforce strategies.
More than half (55%) of the 509 supply chain leaders surveyed expect advancements in agentic AI to reduce their need to hire for entry-level positions. Furthermore, 51% of respondents believe the technology will drive a shift toward overall workforce reductions.
The findings highlight a deepening bifurcation in the corporate world. As geopolitical tensions and economic shifts pressure margins, companies are turning to machines not just to analyze data, but to execute tasks previously reserved for junior analysts and logistics coordinators.
By Nikolaos Doganis, Business Architect AI & Data Centers 02.25.2026
By Andy Jaros, VP of IP Sales, QuickLogic 02.25.2026
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Rise of the autonomous workforce
The survey, conducted between July and October 2025, identifies the advancement of AI as the single most influential driver redefining supply chain strategy over the next two years. It outpaces other significant pressures, including economic policy, de-globalization, and evolving customer expectations.
Unlike earlier waves of digitization that focused on visibility or simple process automation, agentic AI represents a leap toward systems that can negotiate, procure, and schedule logistics with minimal human oversight. This capability is leading executives to rethink the composition of their teams.
However, analysts warn against viewing this transition solely as a cost-cutting mechanism. Marco Sandrone, VP analyst specializing in supply chain operations at Gartner, cautioned that successful organizations are distinguishing themselves by how they deploy these tools.
“The highest performing supply chain organizations are using AI to reinvent how work gets done and how talent is developed. They are not treating AI as a blunt instrument for headcount reduction,” Sandrone said. “The priority for chief supply chain officers should be redesigning roles, skills, and workforce processes, so people and machines can create value together.”
Redefining the talent pyramid
The report suggests that the traditional pyramid structure of supply chain organizations—broad at the bottom with junior execution roles—is eroding. In its place, a more diamond-shaped structure may emerge, prioritizing mid- to senior-level employees capable of managing AI outputs and complex stakeholder relationships.
Gartner’s analysis found that 86% of respondents agree that the adoption of agentic AI will require entirely new processes for developing future talent pipelines. If entry-level roles are automated, the industry faces a long-term challenge: How to train the next generation of senior leaders who historically learned the ropes through the very operational tasks now being automated.
Sandrone noted that while junior roles as understood today may fade in importance, supply chains will still need emerging talent that is highly adaptive. He argues that organizations must identify and attract talent capable of sustaining new working models, which include reskilling current staff to take on higher-value roles.
Productivity gap
The data reveals a stark confidence gap between industry leaders and their peers. Gartner identified a cohort of high-performing organizations—those exceeding expectations in revenue growth, lead times, and sustainability. Among respondents who view AI-driven changes as a top transformation driver, 81% of these leaders expressed confidence in their ability to address their impact. In contrast, only 54% of other respondents reported the same level of confidence.
These high-performing organizations are adopting agentic AI at significantly higher rates across procurement, logistics, and planning. Crucially, they are redesigning the work itself rather than simply layering technology on top of existing inefficiencies. The report notes that organizations that redesign work are twice as likely to exceed revenue goals and achieve sustainable competitive advantage compared to those that do not.
The divergent approaches to workforce investment are evident in the data. While cost reduction remains a factor, high-performing leaders are prioritizing reinventing their talent strategy. Sixty percent of leading organizations are prioritizing upskilling talent for the AI era, compared to just 46% of other respondents.
Machine-to-machine commerce
Beyond internal workforce dynamics, the rise of agentic AI is reshaping how companies interact with their trading partners. As supply chains become more automated, the need for strategic collaboration with suppliers increases. The report indicates that 76% of supply chain leaders have already implemented or plan to implement capabilities to automate interactions with “machine customers”—non-human economic actors that independently negotiate and purchase goods.
This shift necessitates a realignment of trading partner relationships. Routine interactions are increasingly automated, freeing up capacity for human professionals to focus on designing out supply chain complexity through product and material innovation. The report advises leaders to support strategic trading partners in developing the digital capabilities needed for machine-enabled collaboration, effectively building a digital ecosystem where data structures and incentives are aligned.
As the industry marches toward 2028, executives’ consensus is that the status quo is untenable. With 88% of leaders utilizing agentic AI in procurement alone, the supply chain sector is rapidly becoming a testing ground for the broader integration of autonomous intelligence in global business.
“As organizations identify new ways of working through the use of AI, they will also have an advantage in identifying and attracting the kinds of talent that will sustain these new working models,” Sandrone said.
See also:
Supply Chain and Digital Sovereignty Face AI Triple Threat