The global multimodal AI market size was estimated at USD 1.34 billion in 2023 and is projected to grow at a compound annual growth rate (CAGR) of 35.8% from 2024 to 2030. Multimodal artificial intelligence (AI) involves the use of diverse data types, including video, audio, speech, images, text, and traditional numerical datasets, to improve its capability to make precise predictions, derive insightful conclusions, and offer accurate solutions to real-world issues. This strategy entails training AI systems to concurrently synthesize and process various data sources, allowing them to gain a deeper understanding of both content and context. With the increasing adoption of multimodal AI across diverse sectors, stakeholders are presented with a significant opportunity to capitalize on the expanding market. By providing innovative multimodal AI solutions tailored to meet the specific needs of various industries, stakeholders can play an important role in driving market growth.
With the continuous advancement of AI technologies, there is an increasing awareness that the implementation of multimodal AI can be tailored to meet the specific needs and challenges of various industries. Whether in healthcare, education, finance, or entertainment, each sector contains unique data characteristics and specific demands. Multimodal AI is strategically positioned to deliver personalized solutions by leveraging the capabilities of multiple data modalities. For instance, in the healthcare sector, multimodal AI can be applied to analyze medical images, audio recordings of doctor-patient interactions, and textual patient records, providing comprehensive diagnostic insights and transforming patient care and medical research.
Moreover, within the automotive industry, multimodal AI is utilized in developing advanced driver-assistance systems. This involves integrating visual data from cameras, textual data from sensors, and audio data from in-car voice assistants to improve road safety and enhance the overall driving experience. This sector-specific approach is paving the way for a new generation of innovation, where the distinctive challenges and opportunities of each industry are met with customized multimodal AI solutions.
The market growth stage is high, and the pace of the market growth is accelerating. Multimodal AI, which integrates diverse data types such as text, images, audio, and video, is witnessing rapid advancements in both research and practical applications. Innovations in algorithms, machine learning (ML) models, and neural network architectures are enhancing the capability of multimodal AI systems to understand and interpret complex, real-world data. Enterprises can now tailor these systems to their specific needs, leveraging private datasets and industry-specific requirements. This degree of customization fosters innovation across sectors, from healthcare and finance to entertainment and manufacturing.
The multimodal artificial intelligence market is characterized by a high level of merger and acquisition (M&A) activity, reflecting the industry's rapid evolution. Established players are strategically acquiring startups to enhance their technological portfolios and gain a competitive edge. These transactions often target companies specializing in innovative algorithms, advanced ML models, or unique applications of multimodal AI.
Concerns surrounding data privacy and the possible misuse of sensitive information have prompted the introduction of regulatory frameworks. Countries are implementing laws to govern the responsible development and deployment of multimodal AI systems. These regulations aim to ensure transparency, accountability, and fairness in AI applications. In addition, ethical guidelines and principles are being proposed to address the social and ethical considerations of AI technologies. As the market expands, regulatory efforts are expected to intensify, focusing on creating a balance between fostering innovation and safeguarding societal interests.
While multimodal AI stands as a cutting-edge technology with diverse applications, there are emerging substitutes that cater to specific use cases. One notable substitute is single-modal AI, which focuses on analyzing and processing data from a singular source like text, images, or audio. Despite lacking the comprehensive capabilities of multimodal systems, single-modal AI proves efficient in tasks where a particular data type takes precedence. Furthermore, traditional analytics tools and statistical models offer alternatives for extracting insights from structured data. In addition, human expertise and manual data processing continue to be substituted, particularly in minute tasks requiring subjective interpretation.
The software segment led the market and accounted for a 65.2% share of the global revenue in 2023. Multimodal AI software constitutes integrated systems specifically created to concurrently handle and process various types of data, encompassing images, text, audio, and video. These software solutions commonly integrate advanced technologies like ML, deep learning (DL), and natural language processing (NLP) to facilitate a comprehensive understanding of multimodal information. In practical terms, multimodal AI software empowers users to create, implement, and oversee AI models with the ability to manage diverse data modalities cohesively.
The service segment is expected to register the fastest CAGR during the forecast period. Multimodal AI services encompass a broad spectrum of offerings tailored to diverse requirements in the domains of professional and managed services. Professional services involve consulting and providing strategic guidance for the implementation of multimodal AI solutions, along with specialized training and workshops to equip teams with essential skills. Multimodal data integration services facilitate the seamless blend of various data types. In the domain of managed services, comprehensive solutions are delivered, managing the entire lifecycle of multimodal AI systems. This includes continuous improvement, infrastructure management, and ensuring optimal performance, enabling organizations to harness the advantages of multimodal.
The text data segment accounted for the largest market revenue share in 2023. Text data, being a fundamental component of communication and information exchange, is prevalent in various sectors, such as customer service, NLP, and content analysis. The ability of multimodal AI to effectively analyze and comprehend text data has made it a key solution for tasks like chatbots, sentiment analysis, and document processing, driving its prominence and contributing significantly to the overall market revenue.
The speech & voice data segment is projected to grow significantly over the forecast period. The widespread adoption of voice-enabled devices, virtual assistants, and voice-activated applications across various industries has fueled the importance of speech and voice data. In addition, advancements in speech recognition technology, improved language processing algorithms, and the rising popularity of voice-driven commands in smart devices have contributed to the segment's dominance. The seamless integration of speech and voice data in multimodal AI applications has further solidified its position as a key driver of the market.
The media & entertainment segment accounted for the largest market revenue share in 2023, owing to the industry's increasing focus on enhancing user experiences, content personalization, and creative innovation. Multimodal AI technologies are particularly well-suited for applications within media and entertainment, where the combination of text, image, audio, and video data is crucial for delivering immersive and engaging content.
The BFSI segment is expected to register the fastest CAGR during the forecast period. Multimodal AI, especially in facial recognition, is employed for secure and user-friendly customer authentication. This technology strengthens security protocols in mobile apps, online banking, and ATM transactions. In the BFSI sector, chatbots and virtual assistants leverage multimodal AI to comprehend and address customer queries effectively. This involves handling text-based queries, interpreting images of documents, and incorporating voice commands to ensure a smooth customer service experience. Multimodal AI examines customer behavior across diverse online and mobile banking channels, enabling the detection of irregular patterns like unexpected transactions or login anomalies and prompting alerts for potential fraud.
The large enterprise segment accounted for the largest market revenue share in 2023.Large enterprises generally deal with a diverse range of data types, including text, images, videos, and audio. Multimodal AI assists in addressing the complexity of these organizations' operations by providing comprehensive solutions that can analyze and interpret various modalities. In addition, multimodal AI platforms often offer customization options, allowing large enterprises to tailor the technology to their specific requirements. This level of customization is essential for addressing the varied and intricate processes within large organizations.
The SME segment is expected to register the fastest CAGR during the forecast period. Multimodal AI solutions tailored for SMEs offer cost-effective options, making these advanced technologies more accessible to smaller businesses with limited budgets. Multimodal AI platforms customized for SMEs are more adaptable to smaller-scale workflows, offering solutions that are suited to specific operations and requirements of SMEs.
North America dominated the market and accounted for a 48.9% share in 2023. The North America market is undergoing substantial growth, fueled by the convergence of technologies and a rising demand for more sophisticated and human-like interactions between machines and users. A key driving force is the widespread adoption of smartphones and smart devices, coupled with the increasing availability of high-quality data. The region's emphasis on innovation creates an environment conducive to the progress of multimodal AI. North American companies are pioneering the development and implementation of multimodal AI solutions, reflecting the region's dedication to advancing technology and pushing the boundaries of AI to enhance user engagement and problem-solving.
Asia Pacific is anticipated to witness significant growth in the market. One significant factor is the rapid adoption and integration of advanced technologies across various industries in the region. Countries in the Asia Pacific, such as China, Japan, South Korea, and India, have witnessed substantial growth in their economies, leading to increased investments in AI. The region's large and diverse consumer base, along with the proliferation of smartphones and other smart devices, has driven the demand for multimodal AI applications in areas like e-commerce, healthcare, and finance. In addition, the growing focus on digital transformation initiatives by businesses and governments has further accelerated the deployment of multimodal AI solutions in the Asia Pacific region.
Some of the key players operating in the market include Google LLC; Microsoft; and Amazon Web Services, Inc.
Google LLC has been a major player in advancing multimodal AI technologies, leveraging ML, deep learning, and NLP. The company's contributions to the field include the development of state-of-the-art models for image and speech recognition, language translation, and understanding complex data modalities.
Microsoft is a multinational technology company renowned for its software products, operating systems, and cloud computing services. Microsoft's Azure cloud platform provides a suite of AI services, including computer vision, speech recognition, and NLP. These services empower developers to build multimodal AI applications.
Clarifai, Inc. and SenseTime are some of the emerging market participants in the multimodal artificial intelligence market.
Clarifai, Inc. is a prominent player in the multimodal AI market with a specialized focus on visual recognition and analysis. The company offers a comprehensive platform that harnesses the power of multimodal AI to interpret and analyze visual data, including images and videos.
SenseTime is renowned for its advancements in AI and computer vision technologies. The company specializes in a diverse range of AI applications, with a notable emphasis on facial recognition, image and video analysis, and solutions for autonomous driving.
In December 2023, Alphabet Inc., an American multinational technology conglomerate holding company, unveiled the initial phase of its advanced AI model, Gemini. This groundbreaking model represents the first instance of surpassing human experts in performance on MMLU (Massive Multitask Language Understanding), a widely recognized benchmark for evaluating the capabilities of language models.
In December 2023, Meta revealed its plan to introduce multimodal AI functionalities that provide information about the surroundings collected through the cameras and microphones of the company's smart glasses. By saying "Hey Meta" while wearing the Ray-Ban smart glasses, users can activate a virtual assistant capable of both seeing and hearing the events in their immediate environment.
In October 2023, Reka AI, Inc. unveiled Yasa-1, a groundbreaking multimodal AI assistant designed to extend its understanding beyond text to include images, short videos, and audio snippets. Yasa-1 offers enterprises the flexibility to tailor their capabilities to private datasets of various modalities, enabling the creation of innovative experiences for diverse use cases. With support for 20 languages, the assistant boasts the capacity to deliver contextually informed answers sourced from the internet, handle extensive contextual documents, and even execute code.
The following are the leading companies in the multimodal AI market. These companies collectively hold the largest market share and dictate industry trends. Financials, strategy maps & products of these multimodal AI companies are analyzed to map the supply network.
Market size value in 2024
USD 1.74 billion
Revenue forecast in 2030
USD 10.89 billion
CAGR of 35.8% from 2024 to 2030
Base year for estimation
2017 - 2022
2024 - 2030
Revenue in USD million/billion and CAGR from 2024 to 2030
Revenue forecast, company ranking, competitive landscape, growth factors, and trends
Component, data modality, end-use, enterprise size, and region
North America; Europe; Asia Pacific; Latin America; MEA
U.S.; Canada; Germany; UK; France; China; Japan; India; South Korea; Australia; Brazil; Mexico; KSA; UAE; South Africa
Key companies profiled
Aimesoft; Amazon Web Services, Inc.; Google LLC; IBM Corporation; Jina AI GmbH; Meta.; Microsoft; OpenAI, L.L.C.; Twelve Labs Inc.; Uniphore Technologies Inc.
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This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For this study, Grand View Research has segmented the global multimodal AI market report based on component, data modality, end-use, enterprise size, and region.
Component Outlook (Revenue, USD Million, 2017 - 2030)
Data Modality Outlook (Revenue, USD Million, 2017 - 2030)
Speech & Voice Data
Video & Audio Data
End-use Outlook (Revenue, USD Million, 2017 - 2030)
Media & Entertainment
IT & Telecommunication
Automotive & Transportation
Enterprise Size Outlook (Revenue, USD Million, 2017 - 2030)
Regional Outlook (Revenue, USD Million, 2017 - 2030)
Middle East and Africa (MEA)
b. The global multimodal AI market size was estimated at USD 1.34 billion in 2023 and is expected to reach USD 1.74 billion in 2024.
b. The global multimodal AI market is expected to grow at a compound annual growth rate of 35.8% from 2024 to 2030 to reach USD 10.89 billion by 2030.
b. North America dominated the multimodal AI market with a share of 48.9% in 2023 fueled by the convergence of technologies and a rising demand for more sophisticated and human-like interactions between machines and users.
b. Some key players operating in the multimodal AI market include Aimesoft; Amazon Web Services, Inc.; Google LLC; IBM Corporation; Jina AI GmbH; Meta.; Microsoft; OpenAI, L.L.C.; Twelve Labs Inc.; and Uniphore Technologies Inc.
b. Key factors that are driving the multimodal AI market growth include the increasing need for more immersive and context-aware user experiences in applications such as virtual assistants, customer service, and content recommendation, and growing integration of multimodal AI in industry-specific applications, such as healthcare diagnostics, autonomous vehicles, and security surveillance.
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