Multimodal AI Market to exceed US$ 10,550.20 million by 2031

    Published on 13-Jun-2024
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    Report : Multimodal AI Market Size and Forecast (2021 - 2031), Global and Regional Share, Trend, and Growth Opportunity Analysis Report Coverage: By Component (Solution and Service), Organization Size (SMEs and Large Enterprises), Data Type (Audio and Video, Image, and Text), End Use (Automotive and Transportation, BFSI, E-commerce and Retail, Healthcare, IT and Telecom, Media and Entertainment, and Others), and Geography

    According to our latest study on "Multimodal AI Market Forecast to 2031 - Global and Regional Share, Trend, and Growth Opportunity Analysis - by Type, Rating, and End User," the market was valued at US$ 893.5 million in 2023, and the Multimodal AI market size is projected to reach US$ 10,550.20 million by 2031. The Multimodal AI market is expected to record a CAGR of 36.2% from 2023 to 2031.

    Surging Applications in Healthcare Sector Propel the Growth During the Forecast Period

    The integration of many data sources increases the understanding of complex medical conditions as well as provides the framework for more refined and tailored medical treatments. Thus, multimodal AI has a huge potential to alter several aspects of the healthcare sector. In clinical trials, digitalization provides transformative solutions to long-standing issues. Moreover, various AI technologies, including wearable devices and smartphone-enabled self-reported questionnaires, help researchers overcome hurdles associated with time, cost, and participant diversity. Integrating data from several modalities improves information granularity while also allowing for automatic phenotyping and subgrouping. Adaptive trial designs enabled by multimodal AI improve efficiency and responsiveness in overall trials. In May 2022, Bristol Meyers Squibb entered into a strategic collaboration with Owkin. The acquired business employed AI to improve the design and execution of Bristol Meyers Squibb's trials, helping it optimize endpoint definitions, patient subgroups, and treatment impact estimation, including covariate adjustment and external control arms. Owkin uses multimodal patient data in collaboration with major academic centers across the US and Europe. This high-quality patient data, which reflects a greater standard of care, powers their AI. They also work together through initiatives such as MOSAIC to include spatial omics and other new modalities into their data offering. Further, Owkin expands its worldwide data network while maintaining data security and academic partner trust in research collaborations by utilizing privacy-enhancing technologies such as federated learning.

    Multimodal AI also improves remote monitoring and care. The integration of data from wearables, electronic health records (EHRs), and ambient wireless sensors improves remote monitoring customizations. For example, when integrated with wearables, environmental sensors improve fall detection and gait analysis performance, ensuring reliability while reducing false alarms. Thus, the expansion of AI applications in healthcare is driving the multimodal AI market.

    Key Findings of Multimodal AI Market Study:

    The multimodal AI market analysis has been carried out by considering the following segments: component, organization size, data type, and end-use. Based on component, the market is segmented into solutions and services. In terms of organization size, the market is divided into SMEs and large enterprises. Based on data type, the market is segmented into audio and video, image, and text. Based on end use, the market is segmented into automotive and transportation, BFSI, e-commerce and retail, healthcare, IT and telecom, media and entertainment, and others. The BFSI segment held the largest multimodal AI market share in 2023.

    Based on data type, the market is segmented into video, image, and text. In January 2024, Google revealed Lumiere AI, a revolutionary system that can generate realistic and diversified videos using natural language or image inputs. Lumiere AI is a space-time diffusion model that synthesizes videos in a single pass, unlike most other models that use a cascaded method. This leads to improved temporal consistency and motion quality, as well as greater flexibility in video editing and creation. Over the last decade, there have been major advancements in AI-powered audio production techniques, such as music and speech synthesis. With many core principles from big language models and text-to-image generation modified and implemented into the audio modality, the latest AI-powered audio-generative systems have surpassed the previously set quality standards.

    Moreover, factors such as surging applications in the healthcare sector propel the Multimodal AI market growth. Also, the ability to improve self-driving car performance is expected to bring new Multimodal AI market trends in the coming years.

    The scope of the Multimodal AI market report is primarily divided into North America (the US, Canada, and Mexico), Europe (Spain, the UK, Germany, France, Italy, and the Rest of Europe), Asia Pacific (South Korea, China, India, Japan, Australia, and the Rest of Asia Pacific), Middle East & Africa (South Africa, Saudi Arabia, the UAE, and the Rest of Middle East & Africa), and South & Central America (Brazil, Argentina, and the Rest of South & Central America). North America accounted for the largest Multimodal AI market share in 2023.

    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 profiled in the Multimodal AI market report.

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