AI's Impact on Supply Chain Workforce Development

Artificial Intelligence (AI) is fundamentally reshaping the landscape of supply chain workforce development. As industries increasingly integrate AI into their operations, the need for a new breed of skilled professionals is becoming apparent. This transformation is having profound implications on the workforce, particularly regarding the types of roles that are emerging and those that are at risk of becoming obsolete.

AI Optimization and Operational Changes

AI's ability to optimize operations and tasks is a key factor in its increasing adoption across supply chains. Agentic AI systems can proactively identify and fix issues, leading to more efficient and resilient operations. As a result, the traditional roles within supply chains are evolving. The need for roles such as operations managers and integration architects is growing, as these positions are crucial for overseeing AI integration and ensuring smooth transitions from legacy systems to AI-driven processes.

Structured apprenticeships are being emphasized to provide critical hands-on experience, given the erosion of entry-level roles which traditionally offered such experience.

The erosion of entry-level roles poses a strategic risk for organizations. These roles have historically provided a foundation for hands-on experience and learning within the supply chain industry. To address this, there is a push towards structured apprenticeships that can offer the necessary practical experience to new entrants in the field.

Skills and Knowledge Requirements

The evolving supply chain landscape demands new skills, particularly in software knowledge. Currently, 54% of positions within the supply chain sector require some level of software proficiency. This trend underscores the necessity for the workforce to adapt to the digital tools and platforms that are becoming integral to supply chain operations.

Feedback loops are essential for AI oversight, ensuring that AI systems operate effectively and are aligned with organizational goals. As supply chains increasingly rely on AI, the importance of these loops becomes more pronounced, highlighting the need for skilled professionals capable of managing and interpreting AI-driven insights.

Security and Third-Party Risk Management

Security remains a significant concern as AI transforms supply chains. A 2024 survey involving 1,800 IT leaders from industries such as financial services, healthcare, and retail revealed that 97% of organizations had been impacted by supply chain breaches, with 81% reporting breaches within the survey period. The survey, conducted in September 2025, included participants from countries such as the US, UK, Germany, and Japan.

In response to these challenges, 45% of organizations are collaborating with third parties for remediation, while 23% work directly with third parties and 22% provide support for third-party solutions. Furthermore, 46% claim to have mature Third-Party Risk Management (TPRM) programs, though 60% cite a lack of internal support as a significant challenge. Notably, only 16% prioritize risk reduction in their TPRM programs.

The frequency of security briefings varies, with 24% of organizations briefing senior leadership monthly on security matters, while 59% hold briefings every three to six months.

Emerging Trends and Future Outlook

The future of supply chains is poised to run on AI, leading to the development of next-generation supply chains that manage complexity through digital twins and other advanced technologies. These systems enable flexibility and intelligent modeling, allowing organizations to better navigate supply chain volatility. Cross-functional intelligence enhances decision-making, providing a more holistic view of operations and potential disruptions.

Despite the promise of AI, leadership turmoil poses a threat to supply chain resilience. Building adaptive supply chains that can withstand disruptions requires cohesive leadership and strategic planning. Moreover, legacy systems continue to hinder end-to-end visibility, with data often being siloed, unstructured, and underused. Traditional supply chains, which frequently rely on intuition for decision-making, are increasingly vulnerable to disruptions.

As AI continues to redefine motor freight performance and decentralize teams across multiple countries, the focus is shifting towards overcoming these legacy challenges and fully leveraging the potential of data and automation. Organizations are tasked with dismantling silos and fostering an environment where data can be effectively utilized to drive intelligent and informed decisions.

In conclusion, AI is transforming the supply chain workforce, necessitating a shift in the skills and roles required to navigate this new landscape. While the challenges are significant, the potential benefits of a well-integrated AI system in supply chains are substantial, offering increased efficiency, resilience, and adaptability in an ever-evolving global market.