Research Insights
According to Market.us, the global AI-powered supply chain planning software market was valued at $11.38 billion in 2025 and is expected to grow rapidly during the forecast period. The market is expected to reach approximately $240.96 billion by 2035, with a strong growth of 35.7% between 2025 and 2035. This growth is driven by increasing supply chain complexity and increasing demand for real-time forecasting, demand sensing, and inventory optimization. Businesses are adopting AI-driven planning platforms to improve resilience, reduce operational costs, and improve end-to-end visibility.
How Is AI Reshaping the Future of Supply Chain Planning Software Market?
- AI improves demand forecasting in supply chain planning software by analyzing large data sets for accurate forecasts, thereby minimizing stock-outs and overstocks.
- Real-time inventory optimization uses machine learning to dynamically adjust levels based on disruptions such as weather or delays.
- Predictive risk management quickly identifies potential bottlenecks through scenario simulations and integration of external data.
- Autonomous logistics planning automates route optimization and supplier selection for faster, cost-effective decisions.
- Generative AI allows planners to use natural language interfaces to query scenarios and instantly receive actionable insights.
Fast Market Facts
- Cloud deployment accounted for a 65.3% share, supported by scalability, faster implementation and seamless integration into distributed supply chain networks.
- Large enterprises led adoption with a 75.5% share, driven by complex global operations, high data volumes and sustained investments in advanced planning technologies.
- Demand planning and forecasting became the top 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 the extensive use of AI planning tools for seasonal demand management, omnichannel fulfillment and real-time inventory decisions.
- The US market reached $3.79 billion in 2025 and expanded at a strong growth rate of 31.4%, supported by the rapid adoption of AI and digitalization of the supply chain.
- North America maintained its regional leadership with a share of over 38.3% in 2025, supported by mature cloud infrastructure, adoption of advanced analytics, and strong corporate investment in AI-based supply chain planning solutions.
Emerging trends
Emerging trends in the AI-driven supply chain planning software landscape include the integration of continuous learning capabilities that allow models to adapt to evolving patterns without manual retraining.
There is also increasing 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 on shared digital platforms are gaining ground, improving alignment and visibility across extended networks.
Growth factors
The growth of the AI-based supply chain planning software market is supported by the increasing demand for end-to-end visibility, predictive responsiveness, and integrated planning processes. Organizations are prioritizing solutions that can optimize resource utilization, reduce costs, and support strategic decision-making amid global disruption and rapid market changes.
Advances in artificial intelligence, cloud computing, and data integration technologies are improving the accessibility and scalability of planning platforms for businesses of different sizes. As digital transformation initiatives intensify and supply chain resilience becomes a strategic priority, AI-driven planning solutions remain at the heart of organizational efforts to balance agility and operational stability.
Opportunity analysis
Emerging opportunities in the AI-based supply chain planning software market are linked to the growing focus on real-time decision support and adaptive planning. AI models that continually learn new data can identify changes in demand, supplier constraints, and network bottlenecks earlier, allowing planners to preemptively adjust their strategies.
Industry-specific solutions, tailored to the needs of the manufacturing, retail, healthcare and logistics sectors, further expand the addressable use cases. Enhanced scenario modeling and optimization capabilities that evaluate alternative plans and quantify risks also create value for organizations seeking resilient supply chain strategies amid continued market volatility.
Challenge Analysis
One of the key challenges facing this market is aligning AI recommendations with human expertise and operational decision-making. While AI planning systems can generate complex insights and optimization suggestions, planners must interpret the results within the business context and strategic priorities.
Resistance to algorithm-based advice, lack of internal skills to evaluate model results, and insufficient explainability of AI recommendations can hinder adoption. Ensuring that planning tools provide transparent, interpretable information that augments rather than replaces human judgment is critical to achieving organizational buy-in and effective implementation.
Recent development and news
- In January 2026, Blue Yonder launched AI-powered cognitive solutions for retail supply chains, introducing planning agents that optimize inventory and demand forecasts in milliseconds. During the 2025 Thanksgiving period, the platform processed delivery estimates for 1.2 billion SKUs, helping retailers reduce waste and improve order accuracy. The solution has been recognized for its agility and ability to support profitable growth in highly dynamic retail environments.
- In May 2025, Manhattan Associates introduced agentic AI capabilities to 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 setup 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
By deployment
By organization size
- Great organization
- SMEs
By application
- Demand planning and forecasting
- Procurement and Supply
- Inventory management
- Production planning and scheduling
- Warehouse and transport management
- Supply Chain Risk Management
- Others
By end-use sector
- Retail
- Health and pharmaceuticals
- Automotive
- Logistics and transportation
- Aerospace and defense
- Chemicals
- Electronics and Semiconductor
- Energy and Utilities
- Others