세계의 멀티모달 AI 시장 규모 조사 및 예측 : 컴포넌트별, 모달리티별, 기업 규모별, 최종 용도별, 지역별 분석(2023-2030년)

Global Multimodal AI Market is valued at approximately USD 0.99 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 35.8% during the forecast period 2023-2030. Multimodal AI refers to artificial intelligence systems capable of processing and understanding information from diverse sources such as text, images, audio, and video. By integrating data from multiple modalities, these systems achieve a deeper understanding of complex information, akin to human perception. Utilizing advanced machine learning algorithms, such as deep learning models, multimodal AI enables tasks such as image recognition, speech recognition, and natural language understanding. Its applications range from healthcare and autonomous driving to virtual assistants and multimedia content analysis. Multimodal AI enhances the intelligence and context-awareness of systems, enabling them to make more accurate decisions across various domains. The growth of the Multimodal AI Market is driven by several factors, including the increasing demand for analyzing unstructured data across various formats, the ability of multimodal AI to address intricate tasks and provide holistic problem-solving solutions, the rapid development of the multimodal ecosystem fueled by Generative AI techniques, and the availability of large-scale machine learning models that facilitate multimodal support.

Additionally, the rise in the adoption of smartphones, smart devices, and the increasing availability of high-quality data is acting as a catalyzing factor for the market demand across the globe. According to Statista, in 2022, it was assessed that approximately 104,7.22 million mobiles have subscribed to 5G around the world. Also, it is anticipated that the figure is likely to rise and reach nearly 2021.2 million by 2025. Thus, these aforementioned factors are primarily attributed to the global market growth. Moreover, the rising demand for customized and industry-specific solutions, as well as the enhanced adaptability to unseen data types to propel multimodal AI forward presents various lucrative opportunities over the forecast years. However, the susceptibility to bias in multimodal models and the limitations in transferability are hindering the market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Multimodal AI Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the emergence of technologies and a growing preference for advanced, human-like interactions between machines and users. The widespread adoption of smartphones and smart devices, along with the increasing abundance of high-quality data have also contributed to the regional market expansion. The region's focus on innovation fosters an environment conducive to the advancement of multimodal AI. Whereas, Asia Pacific is expected to grow at the highest CAGR over the forecast years. The rapid adoption and integration of advanced technologies across diverse industries. Countries such as China, Japan, South Korea, and India have experienced robust economic growth, prompting substantial investments in AI, which are significantly propelling the market demand across the region. Furthermore, businesses and governments in the region are increasingly prioritizing digital transformation initiatives, thereby accelerating the deployment of multimodal AI solutions across various industries in Asia Pacific.

Major market players included in this report are:

• Aimesoft
• Amazon Web Services, Inc.
• Google LLC
• International Business Machines (IBM) Corporation
• Jina AI GmbH
• Meta.
• Microsoft Corporation
• OpenAI, L.L.C.
• Twelve Labs Inc.
• Uniphore Technologies Inc.

Recent Developments in the Market:

• In December 2023, Meta announced its intention to integrate multimodal AI capabilities into its offerings, including smart glasses. These functionalities leverage data captured by the device's cameras and microphones to provide users with information about their surroundings. Through a simple command-"Hey Meta"-users wearing Ray-Ban smart glasses can activate a virtual assistant that seamlessly combines visual and auditory inputs to perceive events in their immediate environment.
• In December 2023, Alphabet Inc., a prominent American multinational technology conglomerate, introduced the initial phase of its cutting-edge AI model, Gemini. This pioneering model marks the first instance of outperforming human experts in MMLU (Massive Multitask Language Understanding), a renowned benchmark for assessing language model capabilities.
• In October 2023, Reka AI, Inc. introduced Yasa-1, an innovative multimodal AI assistant designed to expand its comprehension beyond text to encompass images, short videos, and audio snippets. Yasa-1 provides enterprises with the flexibility to customize their abilities to private datasets of different modalities, facilitating the development of unique experiences for various use cases. With proficiency in 20 languages, the assistant is equipped to provide contextually relevant responses sourced from the internet, manage extensive contextual documents, and execute code as needed.

Global Multimodal AI Market Report Scope:

• Historical Data - 2020 - 2021
• Base Year for Estimation - 2022
• Forecast period - 2023-2030
• Report Coverage - Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
• Segments Covered - Component, Modality, Enterprise Size, End-use, Region
• Regional Scope - North America; Europe; Asia Pacific; Latin America; Middle East & Africa
• Customization Scope - Free report customization (equivalent up to 8 analyst's working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:

• Software
• Service

By Modality:

• Image Data
• Text Data
• Speech & Voice Data
• Video & Audio Data

By Enterprise Size:

• Large Enterprise
• SMEs

By End-use:

• Media & Entertainment
• BFSI
• IT & Telecommunication
• Healthcare
• Automotive & Transportation
• Gaming
• Others

By Region:

• North America
• U.S.
• Canada
• Europe
• UK
• Germany
• France
• Spain
• Italy
• ROE
• Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• RoAPAC
• Latin America
• Brazil
• Mexico
• Middle East & Africa
• Saudi Arabia
• South Africa
• Rest of Middle East & Africa

Table of Contents

Chapter 1.Executive Summary

• 1.1.Market Snapshot
• 1.2.Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
  • 1.2.1.Multimodal AI Market, by Region, 2020-2030 (USD Billion)
  • 1.2.2.Multimodal AI Market, by Component, 2020-2030 (USD Billion)
  • 1.2.3.Multimodal AI Market, by Modality, 2020-2030 (USD Billion)
  • 1.2.4.Multimodal AI Market, by Enterprise Size, 2020-2030 (USD Billion)
  • 1.2.5.Multimodal AI Market, by End-use, 2020-2030 (USD Billion)
• 1.3.Key Trends
• 1.4.Estimation Methodology
• 1.5.Research Assumption

Chapter 2.Global Multimodal AI Market Definition and Scope

• 2.1.Objective of the Study
• 2.2.Market Definition & Scope
  • 2.2.1.Industry Evolution
  • 2.2.2.Scope of the Study
• 2.3.Years Considered for the Study
• 2.4.Currency Conversion Rates

Chapter 3.Global Multimodal AI Market Dynamics

• 3.1.Multimodal AI Market Impact Analysis (2020-2030)
  • 3.1.1.Market Drivers
    • 3.1.1.1.Rapid development of the multimodal ecosystem fuelled by Generative AI techniques
    • 3.1.1.2.Rising in adoption of smartphones
  • 3.1.2.Market Challenges
    • 3.1.2.1.Susceptibility to bias in multimodal models
    • 3.1.2.2.Limitations in transferability
  • 3.1.3.Market Opportunities
    • 3.1.3.1.Rising demand for customized and industry-specific solutions
    • 3.1.3.2.Enhanced adaptability to unseen data types to propel multimodal AI forward

Chapter 4.Global Multimodal AI Market Industry Analysis

• 4.1.Porter's 5 Force Model
  • 4.1.1.Bargaining Power of Suppliers
  • 4.1.2.Bargaining Power of Buyers
  • 4.1.3.Threat of New Entrants
  • 4.1.4.Threat of Substitutes
  • 4.1.5.Competitive Rivalry
• 4.2.Porter's 5 Force Impact Analysis
• 4.3.PEST Analysis
  • 4.3.1.Political
  • 4.3.2.Economical
  • 4.3.3.Social
  • 4.3.4.Technological
  • 4.3.5.Environmental
  • 4.3.6.Legal
• 4.4.Top investment opportunity
• 4.5.Top winning strategies
• 4.6.COVID-19 Impact Analysis
• 4.7.Disruptive Trends
• 4.8.Industry Expert Perspective
• 4.9.Analyst Recommendation & Conclusion

Chapter 5.Global Multimodal AI Market, by Component

• 5.1.Market Snapshot
• 5.2.Global Multimodal AI Market by Component, Performance - Potential Analysis
• 5.3.Global Multimodal AI Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
• 5.4.Multimodal AI Market, Sub Segment Analysis
  • 5.4.1.Software
  • 5.4.2.Service

Chapter 6.Global Multimodal AI Market, by Modality

• 6.1.Market Snapshot
• 6.2.Global Multimodal AI Market by Modality, Performance - Potential Analysis
• 6.3.Global Multimodal AI Market Estimates & Forecasts by Modality 2020-2030 (USD Billion)
• 6.4.Multimodal AI Market, Sub Segment Analysis
  • 6.4.1.Image Data
  • 6.4.2.Text Data
  • 6.4.3.Speech & Voice Data
  • 6.4.4.Video & Audio Data

Chapter 7.Global Multimodal AI Market, by Enterprise Size

• 7.1.Market Snapshot
• 7.2.Global Multimodal AI Market by Enterprise Size, Performance - Potential Analysis
• 7.3.Global Multimodal AI Market Estimates & Forecasts by Enterprise Size 2020-2030 (USD Billion)
• 7.4.Multimodal AI Market, Sub Segment Analysis
  • 7.4.1.Large Enterprise
  • 7.4.2.SMEs

Chapter 8.Multimodal AI Market, by End-use

• 8.1.Market Snapshot
• 8.2.Global Multimodal AI Market by End-use, Performance - Potential Analysis
• 8.3.Global Multimodal AI Market Estimates & Forecasts by End-use 2020-2030 (USD Billion)
• 8.4.Multimodal AI Market, Sub Segment Analysis
  • 8.4.1.Media & Entertainment
  • 8.4.2.BFSI
  • 8.4.3.IT & Telecommunication
  • 8.4.4.Healthcare
  • 8.4.5.Automotive & Transportation
  • 8.4.6.Gaming
  • 8.4.7.Others

Chapter 9.Global Multimodal AI Market, Regional Analysis

• 9.1.Top Leading Countries
• 9.2.Top Emerging Countries
• 9.3.Multimodal AI Market, Regional Market Snapshot
• 9.4.North America Multimodal AI Market
  • 9.4.1.U.S. Multimodal AI Market
    • 9.4.1.1.Component breakdown estimates & forecasts, 2020-2030
    • 9.4.1.2.Modality breakdown estimates & forecasts, 2020-2030
    • 9.4.1.3.Enterprise Size breakdown estimates & forecasts, 2020-2030
    • 9.4.1.4.End-use breakdown estimates & forecasts, 2020-2030
  • 9.4.2.Canada Multimodal AI Market
• 9.5.Europe Multimodal AI Market Snapshot
  • 9.5.1.U.K. Multimodal AI Market
  • 9.5.2.Germany Multimodal AI Market
  • 9.5.3.France Multimodal AI Market
  • 9.5.4.Spain Multimodal AI Market
  • 9.5.5.Italy Multimodal AI Market
  • 9.5.6.Rest of Europe Multimodal AI Market
• 9.6.Asia-Pacific Multimodal AI Market Snapshot
  • 9.6.1.China Multimodal AI Market
  • 9.6.2.India Multimodal AI Market
  • 9.6.3.Japan Multimodal AI Market
  • 9.6.4.Australia Multimodal AI Market
  • 9.6.5.South Korea Multimodal AI Market
  • 9.6.6.Rest of Asia Pacific Multimodal AI Market
• 9.7.Latin America Multimodal AI Market Snapshot
  • 9.7.1.Brazil Multimodal AI Market
  • 9.7.2.Mexico Multimodal AI Market
• 9.8.Middle East & Africa Multimodal AI Market
  • 9.8.1.Saudi Arabia Multimodal AI Market
  • 9.8.2.South Africa Multimodal AI Market
  • 9.8.3.Rest of Middle East & Africa Multimodal AI Market

Chapter 10.Competitive Intelligence

• 10.1.Key Company SWOT Analysis
  • 10.1.1.Company 1
  • 10.1.2.Company 2
  • 10.1.3.Company 3
• 10.2.Top Market Strategies
• 10.3.Company Profiles
  • 10.3.1.Aimesoft
    • 10.3.1.1.Key Information
    • 10.3.1.2.Overview
    • 10.3.1.3.Financial (Subject to Data Availability)
    • 10.3.1.4.Product Summary
    • 10.3.1.5.Recent Developments
  • 10.3.2.Amazon Web Services, Inc.
  • 10.3.3.Google LLC
  • 10.3.4.International Business Machines (IBM) Corporation
  • 10.3.5.Jina AI GmbH
  • 10.3.6.Meta.
  • 10.3.7.Microsoft Corporation
  • 10.3.8.OpenAI, L.L.C.
  • 10.3.9.Twelve Labs Inc.
  • 10.3.10.Uniphore Technologies Inc.

Chapter 11.Research Process

• 11.1.Research Process
  • 11.1.1.Data Mining
  • 11.1.2.Analysis
  • 11.1.3.Market Estimation
  • 11.1.4.Validation
  • 11.1.5.Publishing
• 11.2.Research Attributes
• 11.3.Research Assumption