While retail and supply chain executives widely view AI as essential for resilience and cost optimization, most do not see AI as a total replacement for frontline labor. Instead, they struggle with an “enablement gap,” where they trust algorithms for autonomous decision-making versus upskilling workers to clean up and act on AI output.

Meanwhile, there are diverging views from executives and employees about where and how AI is used. And even when they expect to invest in AI, executives are not sure they will see the full value of it.

The tension is real, especially as shareholders pressure management to deploy artificial intelligence, including predictive and generative AI as well as agentic AI. Rising logistics costs, shrinking margins and persistent supply chain volatility, in particular, are pushing leaders toward agentic AI and machine learning for demand forecasting and inventory placement.

According to data from the Federal Reserve Bank of Atlanta, investments in AI have accelerated this year. “Overall, companies report divergent experiences with AI,” researchers from the Federal Reserve said in a recent report. “A majority invested in AI in 2025, and a much larger share expect to invest in AI in 2026. On average, business executives report labor productivity gains and anticipate further increases.”

“Strikingly, especially in light of recent slowing aggregate job growth, we find little evidence that firms have experienced or anticipate near-term AI-driven employment declines, even as AI could reshape task allocation,” the report’s authors said.

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