The multimodal AI market size was valued at US$ 0.89 billion in 2022 and is expected to reach US$ 105.50 billion by 2030; it is estimated to record a CAGR of 36.2% from 2022 to 2030.
The buying pattern of consumers is progressing toward online shopping. In 2022, ~60% of the US population preferred online shopping. Further, customers anticipate short delivery times. Thus, e-commerce players seek process automation. The fluctuations in demand for stock-keeping units (SKUs) cause complexities in picking operations, which slows down the fulfillment process. The rising number of e-shoppers across the world propels the adoption of artificial intelligence (AI) enabled solutions in the e-commerce industry for storage, inventory retrieval, and workflow process automation. Inventory sold by e-commerce sellers is stored in warehouses, and to reduce the time for sorting and stocking these products, Automated Storage and Retrieval Systems (ASRS) seem to be one of the best tools.
Automation demand in the e-commerce sector varies highly, owing to which the forward pick areas are required to be continuously adjusted to aid the variability in demand. Along with managing SKU demand fluctuations, an ASRS also advances the fulfillment process, thus allowing e-commerce and omnichannel retailers to adhere better to service-level agreements by fulfilling order delivery commitments. Hence, to enhance operations, several providers of ASRS are integrating AI into their solutions. In November 2021, Honeywell International Inc launched a new ASRS system that was integrated with Honeywell Intelligrated's AI-enabld Momentum Warehouse Execution System and offered Decision Intelligence. ASRS device manufacturers are anticipated to increasingly integrate their hardware with multimodal AI to improve the efficiency of the device.
Europe has one of the most efficient and strongest data analytics industries across the world, and it is expanding. The increasing adoption of IoT-enabled technologies is driving the multimodal AI market. IoT analytics has enabled a whole new world of business intelligence tools to make life easier, faster, and smarter. Adoption of multimodal AI is predicted to grow due to an increasing demand for advanced analytic solutions for residents' health management and rising requirement for business intelligence to optimize health administration and strategy. Moreover, the rise in investments by companies to develop new products through machine vision technology for industrial automation is further propelling the adoption of solutions offered by multimodal AI market players. In December 2023, Google launched its most advanced and capable AI model, Gemini, with advanced multimodal capabilities. The company stated that the new model represents a significant leap forward in AI technology. It offers state-of-the-art performance as compared to existing large language models (LLMs).
The multimodal AI market is segmented on the basis of component, organization size, data type, and end user. Based on component, the multimodal AI market is bifurcated into solution and service. The multimodal AI market, by organization size, is bifurcated into SMEs and large enterprises. In terms of data type, the multimodal AI market is segmented into audio & video, image, and text. Based on end user, the multimodal AI market is segmented into automotive & transportation, BFSI, e-commerce & retail, healthcare, IT & telecom, media & entertainment, and others. By region, the multimodal AI market is segmented into North America, Europe, Asia Pacific (APAC), the Middle East & Africa (MEA), and South America (SAM). Aimesoft Inc, Alphabet Inc, Amazon Web Services Inc, IBM Corporation, Jina AI GmbH, Meta Platforms Inc, Microsoft Corporation, OpenAI LLC, Twelve Labs Inc, and Uniphore Technologies Inc are among the key players operating in the multimodal AI market. Several other major companies have been analyzed during this research study to get a holistic view of the multimodal AI market ecosystem.