The Hackett Group's 2026 Supply Chain Key Issues Study found that 83% of organizations have deployed or are piloting artificial intelligence (AI) in supply chain intelligence and analytics, with 79% reporting data visualization capabilities. AI adoption is advancing most rapidly in analytics-intensive, data-rich areas of the supply chain.
Supply chain planning is also a leading area of adoption, with 74% of enterprises reporting AI capabilities in sales and operations planning (S&OP) or integrated business planning (IBP), and 72% in advanced planning and scheduling. This shift is enabling speed to decisioning, as well as the ability to more precisely analyze cost, service and performance. Supply chain leaders are balancing two realities: sustained cost pressure and the need to modernize. The 2026 Supply Chain Key Issues Study highlights a clear shift—AI is becoming embedded in analytics and planning, enabling faster, more informed decisions.
Organizations are accelerating transformation across the supply chain: network design optimization (67%) and increased transactional automation (66%) lead initiatives reported for 2026, followed by inventory optimization (59%) and core platform upgrades (57%). Advanced inventory optimization has the deepest pipeline of any use case, with only 15% of organizations having implemented AI capabilities but 68% piloting. Gartner's separate research confirms that 83% of supply chain organizations are either applying AI incrementally to specific use cases or gradually scaling it into integrated processes.
Note: This summary draws on Supply Chain 24/7's publicly visible headline + subhead and on sector background on AI adoption dynamics.
Key Takeaways:
1. 83% of organizations are deploying or piloting AI in supply chain intelligence and analytics
2. Adoption is strong in planning: 74% use AI in S&OP/IBP, 72% in advanced planning and scheduling
3. Network design optimization (67%) and transactional automation (66%) are top 2026 transformation priorities
4. Advanced inventory optimization has the deepest pipeline: 68% piloting, only 15% deployed
5. AI is scaling rapidly where cost pressure and modernization needs converge
