Artificial Intelligence-Driven Inventory Optimization Market Global Report 2026

The artificial intelligence-driven inventory optimization market size has grown exponentially in recent years. It will grow from $4.96 billion in 2025 to $5.98 billion in 2026 at a compound annual growth rate (CAGR) of 20.6%. The growth in the historic period can be attributed to growth of global supply chain digitization, increasing adoption of enterprise resource planning systems, rising e commerce demand volatility, expansion of warehouse automation systems, increasing use of barcode and rfid based tracking technologies.

The artificial intelligence-driven inventory optimization market size is expected to see exponential growth in the next few years. It will grow to $12.46 billion in 2030 at a compound annual growth rate (CAGR) of 20.2%. The growth in the forecast period can be attributed to expansion of AI powered supply chain optimization platforms, rising demand for real time inventory visibility, growth of omnichannel retail and fulfillment networks, increasing focus on cost efficient logistics operations, adoption of predictive analytics for demand and supply balancing. Major trends in the forecast period include real time inventory visibility and automated stock replenishment systems, predictive demand forecasting for multi channel retail inventory optimization, AI driven warehouse automation and smart storage allocation, dynamic safety stock optimization based on demand variability analysis, integrated supply chain planning with end to end inventory intelligence.

The increasing number of retail stores is expected to propel the growth of the artificial intelligence-driven inventory optimization market going forward. Retail stores refer to establishments where goods are sold directly to consumers in relatively small quantities for personal consumption or use. The increasing number of retail stores is primarily driven by growing consumer demand, supported by higher purchasing power, evolving lifestyles, urbanization, and greater access to both offline and online shopping options. Artificial intelligence-driven inventory optimization supports retail stores by enabling accurate demand forecasting and real-time stock management, reducing stockouts, minimizing excess inventory, and improving overall operational efficiency. For instance, in January 2024, according to the National Association of Convenience Stores, a US-based trade association, the number of convenience stores operating in the United States reached 152,396 in 2024, representing a 1.5% increase compared to the previous year's count. Therefore, the increasing number of retail stores is driving the growth of the artificial intelligence-driven inventory optimization market.

Key companies operating in the artificial intelligence-driven inventory optimization market are focusing on developing innovative solutions, such as predictive, real-time demand forecasting systems, to minimize stockouts, reduce excess inventory, and improve supply chain efficiency. A predictive, real-time demand forecasting system is a technology that uses AI and live data to predict future customer demand instantly as conditions change, so businesses can adjust inventory and supply decisions immediately. For example, in December 2025, Nauta Technologies Inc., a US-based AI-native supply chain operating system provider, launched the AI-powered Nauta Inventory Optimization Engine, a predictive, real-time demand forecasting system designed to enhance end-to-end inventory planning. The platform integrates and structures enterprise supply chain data across multiple systems down to the SKU level, enabling unified visibility across inventory networks. It uses predictive AI models to assess stockout risks in advance, especially during high-demand periods such as peak holiday seasons. The solution helps shippers optimize procurement, replenishment, and distribution decisions in real time while improving service levels and reducing excess inventory holding costs.

In September 2023, Logility Inc., a US-based software company, acquired Garvis for an undisclosed amount. Through this acquisition, Logility aims to enhance its AI-native demand forecasting and inventory optimization capabilities by integrating Garvis’ generative AI and machine learning technologies into its Digital Supply Chain Platform to improve forecast accuracy, supply chain visibility, and inventory decision-making. Garvis is a Belgium-based company that provides generative AI-powered demand forecasting, inventory planning, and cloud-based supply chain analytics solutions.

Major companies operating in the artificial intelligence-driven inventory optimization market are Microsoft Corporation; Oracle Corporation; SAP SE; Manhattan Associates Inc.; Kinaxis Inc.; o9 Solutions Inc.; RELEX Solutions Oy; C3 AI Inc.; Slimstock Holding B.V.; ToolsGroup B.V.; E2open Parent Holdings Inc.; NETSTOCK Operations Limited; Retalon Inc.; Optilon AB; Infor Inc.; Invent Inc.; Leafio Inc.; Lokad SAS; Nextail Labs S.L.

North America was the largest region in the artificial intelligence-driven inventory optimization market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence-driven inventory optimization market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence-driven inventory optimization market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The artificial intelligence-driven inventory optimization market includes revenues earned by entities by providing services such as inventory planning, stock monitoring, automated replenishment, supply chain analytics, predictive inventory management, and inventory optimization consulting services. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

The artificial intelligence-driven inventory optimization market research report is one of a series of new reports that provides artificial intelligence-driven inventory optimization market statistics, including artificial intelligence-driven inventory optimization industry global market size, regional shares, competitors with a artificial intelligence-driven inventory optimization market share, detailed artificial intelligence-driven inventory optimization market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence-driven inventory optimization industry. This artificial intelligence-driven inventory optimization market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

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