Supply Chain AI Statistics: 18+ Statistics You Should Know for 2026

TL;DR — The numbers that matter most:

• 94% of supply chain companies plan to use AI or Gen AI for decision support within two years. (ABI Research, 2025)
• Only 23% of supply chain organizations have a formal AI strategy in place. (Gartner, 2025)
• Companies with AI-mature supply chains are 23% more profitable than their peers. (Accenture, 2024)
• 72% of logistics employees adopted AI tools in 2024, the highest rate across all industries. (ActivTrak, 2025)
• The AI in supply chain market is valued at $9.94 billion in 2025 and projected to reach $236 billion by 2035. (Precedence Research, 2026)

AI adoption in supply chain operations is accelerating rapidly, but adoption alone is not what separates the “leaders” from the “laggards”. The real differentiator is how effectively organizations operationalize AI within their existing workflows, systems, and decision- making processes. 

According to ABI Research’s 2025 survey of 490 supply chain professionals, 94% of companies plan to deploy AI or Gen AI for decision support within the next two years.

Transitioning from intent to execution is where most organizations stall. Gartner found that only 23% of supply chain organizations have a formal AI strategy, even among those already deploying AI. 

The statistics below break down where the industry stands heading into 2026, where AI is delivering measurable results, and where readiness gaps are creating the biggest risks for operations leaders.

Featured Supply Chain AI Statistics

Each statistic below comes from primary survey data or analyst projections published by Gartner, McKinsey, Accenture, PwC, and ABI Research. We’ve included commentary on what the data means for operations leaders evaluating WMS, TMS, and labor management investments.

94% of supply chain companies plan to use AI for decision support within two years (ABI Research, 2025)

When ABI Research surveyed 490 supply chain professionals across the US, Mexico, Germany, and Malaysia, the response was near-unanimous: AI and Gen AI are coming to decision support functions within 24 months.

That level of intent signals a clear shift in priorities, but intent alone doesn’t drive outcomes

Gartner found that only 23% of organizations have a formal AI strategy.

Gartner surveyed 120 supply chain leaders who had already deployed AI in the past 12 months. Even among that group, just 23% reported having a formal supply chain AI strategy in place.

That means three out of four organizations deploying AI are doing so without a documented strategy guiding their investments, use cases, or scaling plans. For companies evaluating Warehouse Management System (WMS) or Transportation Management System (TMS) upgrades, this creates a concrete risk: you can embed AI capabilities into your technology stack without a clear plan for how to operationalize them across facilities, measure ROI, or train your teams to use them effectively.

This gap between ambition and execution is where many organizations struggle, introducing new capabilities without a clear path to scale, standardize, or measure impact.

Companies with AI-mature supply chains are 23% more profitable (Accenture, 2024)

Accenture analyzed 1,148 companies across 10 industries in 15 countries and found that organizations with the most mature supply chains are 23% more profitable than their peers. Those same leaders are six times as likely to use AI and generative AI widely across their supply chain operations.

Accenture’s definition of “next-gen” maturity extends beyond AI alone and includes digital twins, advanced automation, and integrated planning capabilities. Still, AI adoption is the clearest differentiator between the top-performing group and everyone else. A 23% profitability gap should raise a red flag for any CFO weighing supply chain technology investments this year.

57% of operations and supply chain leaders have already integrated AI (PwC, 2025)

PwC’s 2025 Digital Trends in Operations Survey, conducted among 610 US-based operations executives and supply chain officers, found that 57% have integrated AI into selected functions or throughout their organization.

This pushes the industry past the halfway mark for initial AI integration. And the data comes from C-suite executives through managers with direct responsibility for operations, supply chain, or procurement decisions. For organizations that haven’t started, the competitive window is narrowing. Your peers across pharmaceuticals, consumer markets, industrial products, and technology are already deploying AI in the functions you manage.

64% say AI capabilities are important when evaluating new technology (ABI Research, 2025)

AI is becoming a selection criterion for supply chain technology purchases. In ABI Research’s survey, 64% of supply chain leaders rated AI/Gen AI capabilities as important or very important when evaluating a new technology solution.

For companies evaluating WMS platforms, TMS solutions, or labor management systems (LMS), the shift in buyer expectations is worth tracking. Technology partners that don’t have a clear AI roadmap are increasingly at a disadvantage during procurement evaluations, and the organizations making these decisions are looking for partners who can articulate how AI integrates into their implementation approach.

AI-enabled distribution delivers 5–20% logistics cost reduction and 20–30% inventory reduction (McKinsey, 2024)

McKinsey’s research on AI in distribution operations quantified the cost impact across three operational areas: reductions of 20 to 30 percent in inventory, 5 to 20 percent in logistics costs, and 5 to 15 percent in procurement spend.

Those ranges are broad, and where your organization lands depends heavily on data quality, and implementation maturity, as well as how well AI models are integrated into existing WMS and planning systems. But the directional impact is consistent across the operations McKinsey studied: AI embedded in distribution workflows reduces carrying costs, improves demand signal accuracy, and shrinks procurement inefficiencies. For warehouse operators managing multiple facilities, even hitting the low end of those ranges represents significant annual savings.

70% of large organizations will adopt AI-based supply chain forecasting by 2030 (Gartner, 2025)

Gartner projects that 70% of large-scale organizations will adopt AI-based forecasting to predict future demand by 2030. Demand forecasting is consistently cited as the highest-priority AI use case in supply chain, and this projection reflects the convergence of better data infrastructure, more accessible machine learning tools, and the competitive pressure to reduce stockouts and overstock.

If you’re running forecasting processes that still rely primarily on historical averages and manual adjustments, the next four years will likely force a technology decision. The organizations already deploying AI-driven forecasting are building a compounding data advantage that becomes harder to catch as their models improve with each demand cycle.

72% of logistics employees adopted AI tools in 2024 (ActivTrak, 2025)

ActivTrak’s Productivity Lab tracked actual tool usage across 774 companies and found that 72% of logistics employees used AI tools in 2024. That adoption rate is 14 percentage points above the cross-industry average, making logistics the leading industry for AI tool adoption.

This is behavioral data from workplace analytics, not self-reported survey responses, which makes it a particularly reliable signal. Your warehouse and logistics teams are already using AI-powered tools whether your organization has a formal AI strategy or not. The question is whether you’re directing that adoption toward tools that integrate with your WMS and operations stack, or whether employees are finding their own solutions independently.

85% of executives plan to increase AI spending in 2026 (Supply Chain Brain, 2025)

According to a survey covered by Supply Chain Brain, 85% of executives are planning to increase their spending on AI in 2026. One in five expects AI spend to rise by 20% or more.

Pair these results with Deloitte’s finding that 85% of organizations increased AI investment over the past 12 months, yet only 6% saw ROI in under a year. Most achieve satisfactory returns within two to four years. The takeaway for supply chain leaders: budget for a multi-year ROI timeline, not a quick payback. Organizations that pull funding after 12 months of underwhelming returns are often abandoning their investment right before the compounding benefits start to materialize.

94% of procurement executives use generative AI tools at least weekly (AI at Wharton / Hackett Group, 2025)

Research from AI at Wharton and the Hackett Group found that 94% of procurement executives now use generative AI tools at least weekly, a 44 percentage point increase year-over-year.

Procurement sits at the intersection of supply chain planning, vendor management, and cost control. When nearly all procurement leaders are using Gen AI weekly, the downstream effects on sourcing decisions, contract analysis, and supplier evaluation will reshape how the entire supply chain operates. For organizations managing complex vendor ecosystems across multiple distribution centers, this trend signals that your procurement partners and competitors are making faster, more data-informed decisions than they were 12 months ago.

Complete List of Supply Chain AI Statistics

AI Adoption in Supply Chain

1. 57% of operations and supply chain leaders have integrated AI into selected functions or throughout their organization. (PwC, Feb–Mar 2025)
2. 72% of logistics employees adopted AI tools in 2024, the highest rate across all industries. (ActivTrak, 2025)
3. 94% of procurement executives use generative AI tools at least weekly, up 44 percentage points year-over-year. (AI at Wharton / Hackett Group, 2025)

Supply Chain AI Market Size

1. The AI in supply chain market is valued at $9.94 billion in 2025, projected to reach $236.42 billion by 2035 at a 37.3% CAGR. (Precedence Research, 2026)
2. The supply chain management AI market is valued at $40.4 billion in 2025, projected to reach $101.8 billion by 2033 at a 10% CAGR. (Grand View Research, 2025)
3. The warehouse automation market is valued at $21.84 billion in 2025, projected to reach $71.25 billion by 2033 at a 15.93% CAGR. (SNS Insider, Dec 2025)

Supply Chain AI Investment Intent

1. 94% of supply chain companies plan to use AI or Gen AI for decision support within two years. (ABI Research, 2025)
2. 64% of supply chain leaders say AI/Gen AI capabilities are important or very important when evaluating new technology solutions. (ABI Research, 2025)
3. 85% of executives plan to increase AI spending in 2026, with one in five expecting a 20%+ increase. (Supply Chain Brain, 2025)

Supply Chain AI ROI and Business Impact

1. Companies with AI-mature supply chains are 23% more profitable than peers and six times as likely to use AI/Gen AI widely. (Accenture, July 2024)
2. AI-enabled distribution operations see 5–20% logistics cost reduction, 20–30% inventory reduction, and 5–15% procurement spend reduction. (McKinsey, 2024)
3. 85% of organizations increased AI investment in the past year, yet only 6% saw ROI in under a year; most achieve satisfactory ROI within 2–4 years. (Deloitte, 2025)

AI in Demand Forecasting and Warehouse Operations

1. 70% of large-scale organizations will adopt AI-based forecasting to predict future demand by 2030. (Gartner, Sept 2025)
2. 20% of supply chain professionals had adopted AI-enabled vision systems as of December 2023; Gartner predicts 50% will by 2027. (Gartner, June 2024)

Supply Chain AI Strategy and Readiness Gaps

1. Only 23% of supply chain organizations have a formal AI strategy. (Gartner, 2025)
2. Only 29% of supply chain organizations have built the capabilities needed for future readiness. (Gartner, Feb 2025)

Supply Chain AI Future Predictions

1. 15% of daily logistics decisions will be made autonomously by AI agents by 2028. (Gartner via Inbound Logistics, 2026)
2. By 2031, 60% of supply chain disruptions will be resolved without human intervention. (Gartner via SDC Exec, March 2026)

What These Statistics Mean for Your Operations

AI adoption is becoming table stakes- but effective execution remains the differentiator.. Nearly all supply chain companies plan to use AI within two years. Fewer than one in four have a formal strategy for doing so. And the organizations that have figured out how to deploy AI at scale across their warehouses, transportation networks, and procurement functions are pulling away from competitors in profitability, cost efficiency, and operational resilience.

The ROI timeline matters. Deloitte’s data shows that most organizations don’t see satisfactory returns from AI investments for two to four years. That means the decision to invest in AI-capable WMS, TMS, and labor management systems today is a bet on compound returns, not a quick payback. The organizations starting now will have two to four years of data, model training, and workflow optimization built up by the time their competitors begin their first deployments.

Gartner projects that 60% of supply chain disruptions will be resolved without human intervention by 2031. For operations leaders, the question is no longer whether AI will reshape your supply chain. The real question is whether your organization will approach that transformation with discipline- connecting data, systems, and execution in a way that drives consistent, scalable results.