AI-Powered Supply Chain Planning Software Market Gains Momentum as Enterprises Embrace Automation

Research Insights

According to Market.us, The global AI Powered Supply Chain Planning Software market was valued at USD 11.38 billion in 2025 and is expected to expand rapidly over the forecast period. The market is projected to reach approximately USD 240.96 billion by 2035, growing at a strong CAGR of 35.7% from 2025 to 2035. This growth is driven by increasing supply chain complexity and rising demand for real time forecasting, demand sensing, and inventory optimization. Enterprises are adopting AI driven planning platforms to improve resilience, reduce operational costs, and enhance end to end visibility.

How AI is Reshaping the Future of Supply Chain Planning Software Market?

• AI enhances demand forecasting in supply chain planning software by analyzing vast datasets for accurate predictions, minimizing stockouts and overstock.
• ​Real-time inventory optimization uses machine learning to adjust levels dynamically based on disruptions like weather or delays.
• ​Predictive risk management identifies potential bottlenecks early through scenario simulations and external data integration.
• ​Autonomous logistics planning automates route optimization and supplier selection for faster, cost-effective decisions.
• ​Generative AI enables natural language interfaces for planners to query scenarios and receive actionable insights instantly.

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Quick Market Facts

• Cloud deployment accounted for a 65.3% share, supported by scalability, faster implementation, and seamless integration across distributed supply chain networks.
• Large enterprises dominated adoption with a 75.5% share, driven by complex global operations, high data volumes, and sustained investment in advanced planning technologies.
• Demand planning and forecasting emerged as the leading application with a 38.9% share, highlighting the importance of AI in improving forecast accuracy, inventory balance, and market responsiveness.
• The retail sector captured a 34.6% share, reflecting extensive use of AI planning tools for seasonal demand management, omnichannel fulfillment, and real time inventory decisions.
• The U.S. market reached USD 3.79 billion in 2025 and expanded at a strong 31.4% growth rate, supported by rapid AI adoption and supply chain digitalization.
• North America maintained regional leadership with more than a 38.3% share in 2025, backed by mature cloud infrastructure, advanced analytics adoption, and strong enterprise investment in AI based supply chain planning solutions.

Emerging Trends

Emerging trends in the AI-powered supply chain planning software landscape include the integration of continual learning capabilities that enable models to adapt to evolving patterns without manual retraining.

There is also growing use of digital twin representations of supply chain networks that allow planners to simulate alternative scenarios and test the impact of disruptions before execution.

Collaborative planning environments that connect suppliers, manufacturers, and distributors in shared digital platforms are gaining traction, improving alignment and visibility across extended networks.

Growth Factors

Growth in the AI-powered supply chain planning software market is supported by the increasing demand for end-to-end visibility, predictive responsiveness, and integrated planning processes. Organisations prioritise solutions that can optimise resource utilisation, reduce costs, and support strategic decision making amid global disruptions and rapid market shifts.

Advances in artificial intelligence, cloud computing, and data integration technologies improve the accessibility and scalability of planning platforms for enterprises of varied sizes. As digital transformation initiatives intensify and supply chain resilience becomes a strategic priority, AI-driven planning solutions remain central to organisational efforts to balance agility with operational stability.

Opportunity Analysis

Emerging opportunities in the AI-powered supply chain planning software market are linked to the growing emphasis on real-time decision support and adaptive planning. AI models that continuously learn from new data can identify demand shifts, supplier constraints, and network bottlenecks earlier, enabling planners to adjust strategies pre-emptively.

Industry-specific solutions tailored to the needs of manufacturing, retail, healthcare, and logistics sectors further broaden addressable use cases. Enhancing scenario modelling and optimisation features that evaluate alternative plans and quantify risks also creates value for organisations seeking resilient supply chain strategies amidst ongoing market volatility.

Challenge Analysis

A central challenge confronting this market involves aligning AI recommendations with human expertise and operational decision making. While AI planning systems can generate complex insights and optimisation suggestions, planners must interpret results within business context and strategic priorities.

Resistance to algorithm-driven guidance, lack of internal skills to evaluate model outputs, and insufficient explainability of AI recommendations can hinder adoption. Ensuring that planning tools provide transparent, interpretable insights that augment rather than replace human judgement is critical to achieving organisational buy-in and effective implementation.

Recent Developement & News

• In January 2026, Blue Yonder launched AI driven Cognitive Solutions for retail supply chains, introducing planning agents that optimize inventory and demand forecasts within milliseconds. During the 2025 Thanksgiving period, the platform processed delivery estimates for 1.2 billion SKUs, helping retailers reduce waste and improve fulfillment accuracy. The solution was recognized for its agility and ability to support profitable growth in highly dynamic retail environments.
• In May 2025, Manhattan Associates introduced Agentic AI capabilities within its Manhattan Active solutions, including Intelligent Store Manager and Labor Optimizer agents. Powered by large language models, these agents enable autonomous workflows and natural language interactions, significantly reducing system configuration time. The launch of Manhattan Agent Foundry allows users to quickly build and deploy custom AI agents, improving operational flexibility and speed.

Key Market Segments

By Offering

• Software
• Services

By Deployment

• Cloud

• On-Premises
• Hybrid

By Organization Size

• Large Organization
• SME’s

By Application

• Demand Planning & Forecasting
• Procurement & Sourcing
• Inventory Management
• Production Planning & Scheduling
• Warehouse & Transportation Management
• Supply Chain Risk Management
• Others

By End-Use Industry

• Retail
• Healthcare & Pharmaceuticals
• Automotive
• Logistics & Transportation
• Aerospace & Defense
• Chemicals
• Electronics & Semiconductor
• Energy & Utilities
• Others