The AI Skills Gap Is Slowing Down Supply Chains

The term "AI-ready workforce" is frequently used, but what does it truly mean in the supply chain industry? According to Abe Eshkenazi, CEO of the Association for Supply Chain Management (ASCM), it signifies professionals capable of critically analyzing, interpreting, and acting upon AI-driven insights – a skill that's far from plug-and-play. This article explores the urgent need for AI-literate workers in supply chains and the potential consequences of a skills shortage.

From Trendy Term to Essential Requirement

Over the past three years, AI has transitioned from a boardroom buzzword to a crucial operational necessity. Consequently, skills like prompt engineering, predictive analytics, and digital supply chain literacy are rapidly becoming standard expectations for professionals across logistics, procurement, and planning.

However, a significant gap persists between AI tool investment and workforce preparedness. Experts continue to question the return on investment (ROI) of AI implementations, and a global Randstad study reveals that while 75% of companies are adopting AI, only 35% of employees have received related training in the past year. This disparity isn't merely inconvenient; it's a serious risk.

Untrained users risk misinterpreting AI outputs, leading to distrust, disregard, and ultimately, forecasting errors, inventory discrepancies, and widespread inefficiencies within supply chains.

The Skills Gap Threatening Supply Chain Stability

The AI talent shortage is worsening as AI technology accelerates. Bain & Company research indicates an 21% annual growth in demand for AI skills since 2019, coupled with an 11% annual increase in compensation. The firm further highlights a 44% executive concern over internal AI expertise as a major hurdle to generative AI implementation, predicting the talent gap to persist until at least 2027.

This is particularly concerning for the supply chain sector, where a single AI-related error stemming from a lack of understanding could have devastating consequences. Consider a mid-sized logistics company investing in predictive demand AI, yet lacking personnel trained to interpret the results. The technology becomes underutilized, decision-making reverts to less efficient methods, and the ROI is completely lost.

To address this, ASCM launched an AI-focused Technology Certificate program. This initiative not only teaches the mechanics of AI but also emphasizes its integration into professional roles, encompassing data analysis and insights-driven business operations. The aim is to foster a workforce that collaborates effectively with AI, not merely coexists with it. Eshkenazi emphasizes that technology is useless without skilled personnel, and certified professionals have demonstrably accelerated adoption, reduced errors, and improved strategic decision-making, leading to faster ROI and more robust operations.

The Importance of Resilience

AI's greatest value in supply chains isn't cost reduction; it's agility. Imagine real-time logistics rerouting based on weather events, labor disruptions, or port delays, or inventory planning that simultaneously considers sales velocity, supplier reliability, and macroeconomic factors. These aren't theoretical; they're active use cases globally.

A 2024 McKinsey report on AI in operations confirms that companies effectively utilizing AI in their supply chains saw a 15% improvement in logistics efficiency and a 35% reduction in inventory costs. However, the report also cautions that these benefits were primarily observed in organizations that invested in parallel workforce training. This highlights the critical need for human expertise to ask the right questions and challenge inaccurate results.

AI: Augmentation, Not Replacement

Concerns about AI job displacement are valid, but Eshkenazi clarifies that AI augments, not replaces, human workers. ASCM frames its certification as a tool for professional growth, not job elimination. AI handles routine tasks, while professionals focus on strategy, problem-solving, and interpretation.

Bridging Global Gaps

Global AI adoption varies, with North America and East Asia leading, but developing markets are rapidly catching up. ASCM adapts its training to local contexts, offering foundational digital literacy and targeted AI upskilling. In regions with limited infrastructure, the focus is on raising awareness, recognizing that AI is interdependent with data, people, and processes.

The Need for AI-Savvy Professionals

The key takeaway isn't the need for more AI, but for people who can effectively utilize it. Being AI-ready requires a workforce that can rigorously test outputs, collaborate across departments, and identify AI's limitations. IBM's report on the AI skills gap underscores that even advanced AI requires human interaction.

In conclusion, the most successful supply chains will be those with individuals trained to critically evaluate AI insights, not just those with the most advanced technology. ASCM's approach suggests a path forward that other companies may find beneficial.

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