RELEX Report: AI Moves Into Core Supply Chain Decisions as Volatility Persists

Why It Matters

Embedding AI into core supply‑chain functions enables firms to mitigate demand volatility, cut safety‑stock costs, and boost margins, delivering a clear competitive advantage. Accelerated AI investment also marks a sector‑wide pivot toward data‑driven, agile operations.

Key Takeaways

• AI adoption in supply chain rises to 47% for inventory.
• 67% of leaders more confident using AI for decisions.
• 54% prefer AI recommendations, humans finalize decisions.
• 71% plan generative AI investments within five years.
• Consumer demand volatility cited by 44% as top challenge.

Pulse Analysis

The RELEX State of Supply Chain 2026 report underscores a decisive shift: artificial intelligence is no longer a pilot project but a foundational element of supply‑chain planning. With 67% of retail and manufacturing executives reporting higher confidence in AI, firms are leveraging predictive models to smooth inventory fluctuations and streamline logistics routing. This momentum is fueled by ongoing consumer‑demand volatility, which 44% of leaders identify as a primary threat, prompting a move away from traditional safety‑stock buffers toward real‑time, algorithm‑driven decision support.

Retail and manufacturing sectors are applying AI in distinct yet complementary ways. Retailers focus on demand agility, using AI‑enhanced forecasting to react swiftly to sudden purchasing trends while protecting margins. Manufacturers, meanwhile, deploy AI to link demand signals with procurement and production, mitigating raw‑material disruptions and regulatory risks. Across both domains, sustainability has risen to an operational constraint, with 63% of respondents emphasizing greener supply‑chain strategies, a goal AI can help achieve through optimized resource allocation and waste reduction.

Looking ahead, the report reveals that 71% of organizations plan to invest in generative and agentic AI within the next three to five years, signaling a deeper integration of autonomous decision‑making capabilities. Executives should prioritize building robust data foundations, fostering cross‑functional AI literacy, and establishing governance frameworks to balance AI recommendations with human oversight. By doing so, they can unlock faster response times, higher forecast accuracy, and sustainable growth in an increasingly unpredictable market.