Multimodal AI Market by Offering (Solutions & Services), Data Modality (Image, Audio), Technology (ML, NLP, Computer Vision, Context Awareness, IoT), Type (Generative, Translative, Explanatory, Interactive), Vertical and Region - Global Forecast to 2028
By Offering, Data Modality, Technology, Type, Verticals, and Region
Regions covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
The global multimodal AI market is valued at USD 1.0 billion in 2023 and is estimated to reach USD 4.5 billion by 2028, registering a CAGR of 35.0% during the forecast period. In today's data-driven world, an abundance of information is generated in unstructured formats such as text, images, and videos. This wealth of data is often rich in insights and valuable content, but its unstructured nature makes it challenging to process, analyze, and extract meaningful information using traditional analytics methods. Multimodal AI steps in as a transformative solution, allowing organizations to harness the riches concealed within unstructured data sources. With the capability to process and interpret information from videos, images, and text, multimodal AI surpasses the limitations of single-modal AI approaches, which are often confined to analyzing structured data or a single data type. This driver underscores the essential role of multimodal AI in addressing the increasing complexity of data analysis requirements in the digital age.
By solutions, the platform segment is projected to hold the largest market size during the forecast period
Multimodal AI solutions in the form of platforms represent comprehensive systems designed to handle and process diverse types of data simultaneously, including text, images, audio, and video. These platforms typically incorporate a range of advanced technologies such as machine learning, deep learning, and natural language processing to enable a holistic understanding of multimodal information. In practical terms, a multimodal AI platform allows users to develop, deploy, and manage AI models capable of handling multiple data modalities in a unified manner. These platforms empower organizations to build intelligent systems that can interpret and respond to complex, real-world scenarios by integrating insights from different data sources.
By data modality, Video Data segment is registered to grow at the highest CAGR during the forecast period
Video data consists of a sequence of frames, each containing visual content, and is a critical modality in multimodal AI applications. Video data allows AI systems to interpret dynamic scenes, track objects, recognize patterns, and understand temporal relationships, making it valuable in various domains such as surveillance, healthcare, and entertainment. The growing prevalence of video content on the internet, the increasing adoption of surveillance and monitoring systems, and the demand for more sophisticated video analytics in industries like retail and manufacturing drives the utilization of video data in multimodal AI.
Asia Pacific is projected to witness the highest CAGR during the forecast period.
The Asia Pacific region emerges as a vibrant hub of economic prowess and technological progress, forecasted to contribute a substantial 70% of global growth in 2023, surpassing other regions. With over half of the world's population residing in this region, any technological shifts, particularly those driven by AI, are anticipated to significantly influence its future trajectory. Several Asian countries, including China, India, Japan, and others, are actively embracing information-intensive AI technologies, with conversational AI leading the technological forefront. Nations like China, Japan, South Korea, India, and Singapore are making substantial investments in artificial intelligence, positioning the APAC region as the fastest-growing AI market globally.
Breakdown of primaries
In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the multimodal AI market.
By Company: Tier I: 35%, Tier II: 45%, and Tier III: 20%
By Designation: C-Level Executives: 35%, Directors: 25%, and Others: 40%
By Region: North America: 45%, Europe: 20%, Asia Pacific: 30%, RoW: 5%
Major vendors offering multimodal AI and services across the globe are Google (US), Microsoft (US), OpenAI (US), Meta (US), AWS (US), IBM (US), Twelve Labs (US), Aimesoft (US), Jina AI (Germany), Uniphore (US), Reka AI (US), Runway (US), Jiva.ai (UK), Vidrovr (US), Mobius Labs (US), Newsbridge (France), OpenStream.ai (US), Habana Labs (US), Modality.AI (US), Perceiv AI (Canada), Multimodal (US), Neuraptic AI (Spain), Inworld AI (US), Aiberry (US), One AI (US), Beewant (France), Owlbot.AI (US), Hoppr (US), Archetype AI (US), Stability AI (England).
Research Coverage
The market study covers multimodal AI across segments. It aims at estimating the market size and the growth potential across different segments, such as offering, data modality, technology, type, vertical, and region. It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.
Key Benefits of Buying the Report
The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall market for multimodal AI and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (The need to analyze unstructured data in multiple formats drives the multimodal AI market, The ability of multimodal AI to handle complex tasks and provide a holistic approach to problem-solving, Generative AI techniques to accelerate multimodal ecosystem development and The availability of large-scale machine learning models that support multimodality.), restraints (Susceptibility to bias in multimodal models and Processing and training multi-modal AI models demand extensive computational resources), opportunities (Rising demand for customized and industry-specific solutions, Enhanced adaptability to unseen data types propels multimodal AI forward, Data Management Services to empowering multimodal AI advancements), and challenges (Teaching AI to grasp nuance and context-dependent meanings poses complex linguistic challenges, Optimal data fusion presents complex challenges in multimodal AI integration, Limitations in transferability pose challenges for multimodal AI adaptation to diverse data types) influencing the growth of the multimodal AI market
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the multimodal AI market.
Market Development: Comprehensive information about lucrative markets - the report analyses the multimodal AI market across varied regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in multimodal AI market strategies; the report also helps stakeholders understand the pulse of the multimodal AI market and provides them with information on key market drivers, restraints, challenges, and opportunities.
Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players such as Google (US), Microsoft (US), OpenAI (US), AWS (US), Meta (US) among others in the multimodal AI market.
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 MARKET SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 REGIONS COVERED
1.4 YEARS CONSIDERED
1.5 CURRENCY CONSIDERED
1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
FIGURE 1 MULTIMODAL AI MARKET: RESEARCH DESIGN
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
TABLE 1 PRIMARY INTERVIEWS
2.1.2.1 Breakup of primary profiles
2.1.2.2 Key industry insights
2.2 DATA TRIANGULATION
FIGURE 2 DATA TRIANGULATION
2.3 MARKET SIZE ESTIMATION
FIGURE 3 MULTIMODAL AI MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): FLOWCHART USING REVENUE FROM MULTIMODAL AI SOLUTIONS/SERVICES
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL MULTIMODAL AI SOLUTION/SERVICE PROVIDERS
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): REVENUES OF TOP PLAYERS AND SOURCES OF DATA
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE THROUGH OVERALL MULTIMODAL AI SPENDING
2.4 MARKET FORECAST
TABLE 2 FACTOR ANALYSIS
2.5 RESEARCH ASSUMPTIONS
2.6 LIMITATIONS
2.7 IMPLICATIONS OF RECESSION ON MULTIMODAL AI MARKET
TABLE 3 IMPACT OF RECESSION ON GLOBAL MULTIMODAL AI MARKET
3 EXECUTIVE SUMMARY
TABLE 4 MULTIMODAL AI MARKET SIZE AND GROWTH RATE, 2017-2022 (USD MILLION, Y-O-Y)
TABLE 5 MULTIMODAL AI MARKET SIZE AND GROWTH RATE, 2023-2028 (USD MILLION, Y-O-Y)
FIGURE 8 SOLUTIONS TO HOLD LARGER MARKET IN 2023
FIGURE 9 PLATFORM SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023
FIGURE 10 CLOUD DEPLOYMENT TO BE LARGER MARKET IN 2023
FIGURE 11 PROFESSIONAL SERVICES TO ACCOUNT FOR LARGER MARKET IN 2023
FIGURE 12 CONSULTING TO ACCOUNT FOR LARGEST SHARE IN 2023
FIGURE 13 IMAGE DATA TO ACCOUNT FOR LARGEST MARKET IN 2023
FIGURE 14 GENERATIVE MULTIMODAL AI TO ACCOUNT FOR LARGEST SHARE IN 2023
FIGURE 15 NATURAL LANGUAGE PROCESSING TO ACCOUNT FOR LARGEST MARKET IN 2023
FIGURE 16 HEALTHCARE & LIFE SCIENCES TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023
FIGURE 17 ASIA PACIFIC TO GROW AT HIGHEST CAGR IN MULTIMODAL AI MARKET
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES IN MULTIMODAL AI MARKET
FIGURE 18 INCREASING NEED TO COMPREHEND AND PROCESS MULTIPLE DATA MODALITIES DRIVES MARKET GROWTH
4.2 MULTIMODAL AI MARKET: SOLUTIONS
FIGURE 19 SOFTWARE SEGMENT TO GROW AT HIGHEST CAGR IN MULTIMODAL AI MARKET
4.3 MULTIMODAL AI MARKET, BY OFFERING & KEY VERTICAL
FIGURE 20 SOLUTIONS AND HEALTHCARE & LIFE SCIENCES VERTICAL TO ACCOUNT FOR LARGEST SHARES IN 2023
4.4 MULTIMODAL AI MARKET, BY REGION
FIGURE 21 NORTH AMERICA TO ACCOUNT FOR LARGEST SHARE IN 2023
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 22 MARKET DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
5.2.1 DRIVERS
5.2.1.1 Need to analyze unstructured data in multiple formats to drive multimodal AI market
5.2.1.2 Ability of multimodal AI to handle complex tasks and provide holistic approach to problem-solving to boost market
5.2.1.3 Generative AI techniques to accelerate multimodal ecosystem development
5.2.1.4 Availability of large-scale machine learning models that support multimodality to propel market growth
5.2.2 RESTRAINTS
5.2.2.1 Susceptibility to bias in multimodal models
5.2.2.2 Processing and training multimodal AI models to demand extensive computational resources
5.2.3 OPPORTUNITIES
5.2.3.1 Rising demand for customized and industry-specific solutions
5.2.3.2 Enhanced adaptability to unseen data types to propel multimodal AI forward
5.2.3.3 Data management services to empower multimodal AI advancements
5.2.4 CHALLENGES
5.2.4.1 Teaching AI to grasp nuance and context-dependent meanings to pose complex linguistic challenges
5.2.4.2 Optimal data fusion to present challenges in multimodal AI integration
5.2.4.3 Limitations in transferability to pose challenges for multimodal AI adaptation to diverse data types
5.3 INDUSTRY TRENDS
5.3.1 MULTIMODAL AI: ARCHITECTURE
FIGURE 23 MULTIMODAL AI ARCHITECTURE
5.3.2 MULTIMODAL AI: EVOLUTION
FIGURE 24 MULTIMODAL AI MARKET EVOLUTION
5.3.3 VALUE CHAIN ANALYSIS
FIGURE 25 MULTIMODAL AI MARKET: VALUE CHAIN ANALYSIS
5.3.4 ECOSYSTEM/MARKET MAP
FIGURE 26 KEY PLAYERS IN MULTIMODAL AI MARKET ECOSYSTEM
TABLE 6 MULTIMODAL AI MARKET: ECOSYSTEM
5.3.4.1 Solution Providers
5.3.4.2 Service Providers
5.3.4.3 End Users
5.3.4.4 Regulatory Bodies
5.3.5 PRICING ANALYSIS
5.3.5.1 Average Selling Price Trend of Key Players: Top 3 Data Modalities
FIGURE 27 AVERAGE SELLING PRICE TREND OF KEY PLAYERS: TOP THREE DATA MODALITIES
TABLE 7 AVERAGE SELLING PRICE TREND OF KEY PLAYERS FOR TOP THREE DATA MODALITIES (USD)
5.3.5.2 Indicative Pricing Analysis of Multimodal AI, By Solution
TABLE 8 MULTIMODAL AI: INDICATIVE PRICING LEVELS OF MULTIMODAL AI, BY SOLUTION
5.3.6 PORTER'S FIVE FORCES ANALYSIS
FIGURE 28 PORTER'S FIVE FORCES ANALYSIS
TABLE 9 MULTIMODAL AI MARKET: PORTER'S FIVE FORCES ANALYSIS
5.3.6.1 Threat of new entrants
5.3.6.2 Threat of substitutes
5.3.6.3 Bargaining power of suppliers
5.3.6.4 Bargaining power of buyers
5.3.6.5 Intensity of competitive rivalry
5.3.7 TRENDS/DISRUPTIONS IMPACTING CUSTOMER'S BUSINESS
5.3.7.1 Trends/Disruptions impacting customer's business
FIGURE 29 MULTIMODAL AI MARKET: TRENDS/DISRUPTIONS IMPACTING CUSTOMER'S BUSINESS
5.3.8 TECHNOLOGY ANALYSIS
FIGURE 30 MULTIMODAL AI MARKET: TECHNOLOGY ANALYSIS
5.3.8.1 Key Technologies
5.3.8.1.1 Machine Learning
5.3.8.1.2 Natural Language Processing
5.3.8.1.3 AR & VR
5.3.8.1.4 Computer Vision
5.3.8.1.5 IoT
5.3.8.2 Complementary Technologies
5.3.8.2.1 Cloud Computing
5.3.8.2.2 Data Mining
5.3.8.2.3 Biometric Authentication
5.3.8.3 Adjacent Technologies
5.3.8.3.1 Big Data
5.3.8.3.2 Predictive Analytics
5.3.8.3.3 Edge Computing
5.3.8.3.4 Knowledge Graph
5.3.9 CASE STUDY ANALYSIS
5.3.9.1 CASE STUDY 1: Associated Press revolutionized multimedia processing with Vidrovr
5.3.9.2 CASE STUDY 2: SceneXplain's innovative automation and tagging solution revolutionized European e-commerce platform
5.3.9.3 CASE STUDY 3: Global banking group transformed its operations with Uniphore's AI-driven compliance and monitoring solution
5.3.9.4 CASE STUDY 4: Uniphore's U-Assist solution transformed healthcare services company's agent guidance
5.3.9.5 CASE STUDY 5: Telecom leader enhanced efficiency and customer experience with Uniphore's AI-powered automation
5.3.10 PATENT ANALYSIS
5.3.10.1 Methodology
5.3.10.2 Patents Filed, By Document Type
TABLE 10 PATENTS FILED, BY DOCUMENT TYPE
5.3.10.3 Innovation and patent applications
FIGURE 31 NUMBER OF PATENTS GRANTED IN LAST 10 YEARS, 2013-2023
5.3.10.3.1 Top 10 applicants in multimodal AI market
FIGURE 32 TOP 10 APPLICANTS IN MULTIMODAL AI MARKET, 2013-2023
FIGURE 33 REGIONAL ANALYSIS OF PATENTS GRANTED, 2013-2023
TABLE 11 TOP 20 PATENT OWNERS IN MULTIMODAL AI MARKET, 2013-2023
TABLE 12 LIST OF PATENTS GRANTED IN MULTIMODAL AI MARKET, 2023