The global artificial intelligence in inventory management market was valued at US$ 1,670.3 Million in 2018 and is expected to reach US$ XX Million by the end of the forecast period, expanding at a CAGR of 26.30% during the forecast period. Several organizations across end-use industries have found it difficult to cope with rising operational costs, reducing sales, dissatisfied customers, and several such issues. In order to overcome such issues, the adoption of AI in inventory management has become imperative.

AI is equipped with computing techniques that help select and analyze large quantities of data collected from inventory management operations. Several organizations are focusing on digitizing their supply chain processes using AI. Augmenting the efficiency of supply chain operations is the key focus area for several organizations across end-use industries such as retail, automotive, and healthcare, among others. Owing to the penetration of artificial intelligence, many organizations are adopting this technology to ramp up their supply chain operations and thereby, increase profitability and reshape their businesses.

The success of artificial intelligence in accelerating business processes has attracted significant investments as well. For instance, in 2018, the government of Quebec has reportedly invested approximately US$ 60 Mn for supporting AI-enabled supply chain supercluster. In the same year, the Canadian government invested approximately US$ 230 Mn for supporting AI-enabled supply chain supercluster. Such investments have greatly improved the supply chain operations of several organizations across end-use industries. Machine learning integrated in inventory management helps in warehouse management through predictive abilities that can forecast the future demand and supply appropriately. Integrating machine learning technologies into supply chain operations will help project the best possible scenarios based on intelligent algorithms and machine-enabled analysis of huge data sets.

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Figure 1: AI in Inventory Management Market: Ecosystem Snapshot

Based on end-use industries, retail captured a fair chunk of the market in 2018 and is expected to display similar trends in the coming years as well. AI has made a stark difference in optimizing retail supply chain, as the need for fast delivery to shops and end-customers has intensified over the past few years. Artificial intelligence allows retailers to understand the proper operations of how their inventory is being managed, and It suggests improvements and reduces overhead costs and waste. Implementing artificial intelligence in inventory management functions could help retailers save approximately US$ 350 Bn yearly. Further, the implementation of artificial intelligence has also resulted in a reduction in operational costs by about 35%.

The rapid adoption of artificial intelligence in inventory management in the retail sector is being driven by some external pressures. Retailers are rapidly adopting AI in their inventory management processes in order to retain their business. Faster delivery with the help of AI and machine learning technologies has become a major differentiating factor for winning businesses. This rapid adoption of AI in inventory management processes has led to several retailers offering same-day delivery, and more retailers are expected to come up with similar offers in the coming years.

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Table 1: AI in Inventory Management Ecosystem: Segmentation

Global AI in Inventory Management Ecosystem

Based on regions, North America dominated the global market for AI in inventory management and is expected to display similar trends in the coming years as well. Asia Pacific is expected to display higher growth during the forecast period, with China, India, and Japan spearheading the growth of the market. China, for instance, is gearing itself to become the global superpower for artificial intelligence. AI is expected to upgrade and connect the entire country across all industries by 2025. The implementation of AI will control companies and help produce goods while keeping the demand and supply gap in check. The retail industry in China is gearing up for a dramatic change as well. The industry is shifting towards a new concept known as ‘New Retail’, which is an amalgamation of online and offline retail. The integration of AI in new retail in China will allow retailers to augment business efficiency and provide a much better shopping experience to customers. These factors are expected to support the growth of the AI in inventory management market in China in the coming years.

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Figure 2: AI in Inventory Management Ecosystem: Market Statistics Glimpse

There are many trends that are having an impact on the market forecast. These, when evaluated from a company’s perspective, can drive growth. Our numerous consulting projects have generated sizeable synergies across all regions and all sizes of companies.

The major players operating in the Global AI in Inventory Management Ecosystem are as follows:

Table 2 AI in Inventory Management Ecosystem: Key Players

Very few markets have interconnectivity with other markets like AI. Our Interconnectivity module focuses on the key nodes of heterogeneous markets in detail. AI Processors, Deep Learning, GPU, and Autonomous Robots, are some of our key researched markets

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AI in Inventory Management Ecosystem Major Interconnectivities

Global AI in Inventory Management Ecosystem: Key Trends

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