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Artificial intelligence in the supply chain has stopped being a competitive advantage and has become table stakes. The figure that sums it up comes from international consulting-firm research: companies that have already implemented AI-based supply chain management improved logistics costs by 15%, inventory levels by 35%, and service levels by 65%, compared with competitors still on the sidelines. According to Gartner, by 2026 about 75% of large organizations will have adopted AI in their supply chain operations.
Where AI Sits in the Chain
Common applications span the entire chain: demand forecasting, end-to-end visibility, receiving scheduling, predictive maintenance, supplier risk management, and logistics optimization. A 2024 analysis by international consulting firms quantified the impact on distribution operations: a 5% to 20% reduction in logistics costs, a 20% to 30% decrease in inventory levels, and a 5% to 15% reduction in procurement spend.
What Leading Companies Are Actually Doing
Maersk, one of the world’s largest shipping companies, runs predictive maintenance that has cut ship downtime by 30%, saved over $300 million a year, and reduced carbon emissions by about a million and a half tons. At the same time, it built a digital twin of its global supply chain to run “what if” scenarios in advance.
Unilever uses generative AI to simulate demand scenarios across markets worldwide, and runs supplier risk scoring based on financial data, sustainability metrics, and customs data, enabling rapid supplier switching in a crisis. Siemens, using Scoutbee’s AI platform, identified 6,893 potential suppliers for 94 projects across 18 business units, cutting supplier sourcing time by 90%. Coca-Cola runs machine learning for scenario planning and sales forecasting, Levi Strauss cut inventory by 10% without hurting service levels, and Tesla uses computer vision for quality control on its assembly lines.
The Next Wave: Generative AI
International consulting firms estimate that generative AI could add $2.6 to $4.4 trillion in annual value across a range of use cases. In the supply chain, this means moving from slow, manual planning cycles to continuous, AI-assisted forecasting — a capability worth its weight in gold precisely in volatile environments, where historical data is no longer a reliable predictor.
AI Investment and ROI
A 2025 survey found that 85% of large organizations increased their AI investment, yet only 6% saw a return within less than a year, with most reaching a satisfactory return within two to four years. Gartner found that only 23% of supply chain organizations have built a formal AI strategy, even among those already running it. What separates successful organizations from failing ones isn’t the technology but the operating model, data quality, and change management: the survey found that organizations investing 15% or more of the project budget in training and change management achieve adoption rates 2.8 times higher and ROI 3.5 times higher.
What This Means for Israeli Organizations
The lesson for Israeli organizations is simple: start with a high-value, clearly defined use case, not with a platform. In Mashik’s supply chain division, we work with clients to identify where adopting an AI platform will pay back the investment already in the first year, and we build the data, process, and change management around it, so the investment translates into a measurable result.
