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1856974

全球多模態人工智慧市場：未來預測（至2032年）—按組件、模態、多模態人工智慧類型、技術、最終使用者和地區進行分析

Multimodal AI Market Forecasts to 2032 - Global Analysis By Component (Software and Services), Modality (Text Data, Speech & Voice Data, Image Data and Other Modalities), Multimodal AI Type, Technology, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球多模態人工智慧市場預計到 2025 年將達到 24 億美元，到 2032 年將達到 238 億美元，預測期內複合年成長率為 38.8%。

多模態人工智慧是指能夠同時處理、理解和產生多種類型資料（包括文字、圖像、音訊和影片）資訊的人工智慧系統。與專注於單一模態的傳統人工智慧模型不同，多模態人工智慧整合了這些不同的資料來源，從而產生更豐富、更具上下文感知能力的洞察。這種能力支持影像描述、視訊分析、語音助理和跨模態搜尋等應用。結合不同的模態可以提高準確性、推理能力和類人理解能力。多模態人工智慧是邁向更通用、更智慧的系統的重要一步，這些系統能夠無縫地解讀複雜的現實世界資訊。

提高了準確性和穩健性

跨模態模型融合了文字、圖像、音訊和感測器數據，以提升上下文理解能力和預測可靠性。在情緒偵測、目標追蹤和對話反應生成等任務中，多模態系統優於單模態模型。與邊緣設備和雲端平台的整合支援分散式環境下的即時推理和自適應學習。企業利用多模態人工智慧來增強決策能力、自動化工作流程並實現個人化使用者體驗。這些功能推動了平台創新，並提升了關鍵任務型應用的營運效率。

高運算需求

訓練和推理需要藉助先進的GPU和針對跨模態融合與對齊最佳化的流程，才能完成大型資料集的訓練和推理。對於即時應用而言，模型複雜性和延遲要求會增加基礎設施成本。小型公司和學術實驗室在獲取運算資源以及管理跨邊緣和雲端環境的部署方面面臨挑戰。能源消耗和碳排放仍然是大型多模態系統需要關注的問題。

自然互動的進展

語音、手勢和臉部辨識能夠實現數位和實體環境的直覺式介面和身臨其境型使用者體驗。人工智慧代理人利用多模態線索，能夠更準確、更快速地解讀使用者的情感和脈絡。與擴增實境/虛擬實境機器人和智慧型裝置的整合，拓展了其在消費品產業和醫療保健領域的應用場景。多語言人群、神經病變和老年人群體對類人互動和包容性設計的需求日益成長。這些趨勢正在推動多模態使用者體驗對話式人工智慧以及整個輔助技術生態系統的發展。

監管和隱私挑戰

多種數據收集方式引發了公共和私營部門對知情同意、監控和生物識別安全性的擔憂。臉部辨識、語音資料和行為追蹤的法律規範因司法管轄區和應用場景而異。模型決策缺乏透明度，使得審核、課責和倫理監督變得更加複雜。公眾對偏見操縱和虛假資訊的關注，加大了供應商和開發商的壓力。這些風險持續限制敏感產業和受監管環境中平台的普及應用。

新冠疫情的影響：

疫情加速了人們對多模態人工智慧的興趣，推動了醫療零售、教育和公共服務等領域遠距互動和數位參與的激增。醫院利用多模態平台進行遠端醫療診斷和病患監測，以提升對情境的感知能力。零售商在行動和網路通路上應用人工智慧技術，實現虛擬試穿、語音購物和情緒分析。教育機構部署多模態工具，用於遠距學習評估和無障礙支援。在疫情封鎖和恢復階段，大眾對人工智慧驅動的互動和自動化技術的認知度顯著提高。後疫情時代的策略已將多模態人工智慧作為數位轉型中提升營運韌性和用戶參與的核心支柱。

預計在預測期內，影像資料區段將是最大的資料部分。

由於影像資料在電腦視覺人臉臉部辨識和多模態平台中的目標偵測方面發揮基礎性作用，預計在預測期內，影像資料區段將佔據最大的市場佔有率。與文字轉語音和感測器輸入的整合可以提高即時應用中的場景理解、上下文分析和決策準確性。基於影像的模型支援醫療保健、成像、自主導航、零售分析和監控系統等應用場景。工業、消費和政府部門對可擴展的高解析度影像處理的需求正在不斷成長。供應商提供模組化流程和預訓練模型，以實現快速部署和客製化。

預計在預測期內，自然語言處理（NLP）將以最高的複合年成長率成長。

預計在預測期內，自然語言處理 (NLP) 領域將迎來最高的成長率，這主要得益於多模態平台在對話式人工智慧內容產生和情緒分析領域的擴展。 NLP 模型整合了影像、語音和手勢數據，以提升情境反應的準確性和情緒智慧。其應用領域包括行動、桌面和嵌入式環境中的虛擬助理、客戶支援、教育工具和輔助功能平台。全球市場和不同用戶群體對多語言、情感感知和特定領域的 NLP 的需求正在不斷成長。供應商提供基於變壓器 的架構以及針對特定任務和產業的精細化模型。

佔比最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其先進的人工智慧基礎設施研究生態系統以及在醫療保健、國防、零售和媒體等行業的企業級應用。美國和加拿大的公司正在診斷、自動駕駛系統、客戶體驗和公共應用領域部署多模態平台。對生成式人工智慧邊緣運算和雲端原生架構的投資，有助於在法規環境中實現可擴展性、高效能和合規性。領先的人工智慧研究實驗室、大學和科技公司的存在，推動了模型開發的標準化和商業化。監管機構透過沙盒計畫、倫理框架和創新津貼方式支持人工智慧的發展。

複合年成長率最高的地區：

預計亞太地區在預測期內將呈現最高的複合年成長率，這主要得益於行動技術的普及、數位創新以及政府支持的人工智慧計畫在智慧城市、教育、醫療和公共服務領域的融合發展。中國、印度、日本和韓國等國家正在城市基礎設施、農村服務和工業自動化領域擴展多模態平台。當地企業推出針對區域用例和合規規範量身定做的多語言模型。對邊緣人工智慧機器人和即時互動的投資將支援平台在消費者業務和政府領域的擴展。城市中心的製造業園區和低度開發地區對擴充性、低成本的多模態解決方案的需求正在成長。這些趨勢正在推動多模態人工智慧生態系統和創新叢集在區域內的整體成長。

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目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 分析方法
  • 分析材料
    • 原始研究資料
    • 二手研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 市場機遇
  • 威脅
  • 技術分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新參與企業的威脅
  • 公司間的競爭

5. 全球多模態人工智慧市場（按組件分類）

  • 軟體
  • 服務

6. 全球多模態人工智慧市場（以模態分類）

  • 文字數據
  • 音訊數據
  • 影像資料
  • 影片數據
  • 感測器和數值資料
  • 其他方式

7. 全球多模態人工智慧市場（以多模態人工智慧類型分類）

  • 生成式多模態人工智慧
  • 互動式多模態人工智慧
  • 基於概覽的多模態人工智慧
  • 轉化型多模態人工智慧
  • 其他類型的多模態人工智慧

8. 全球多模態人工智慧市場（依技術分類）

  • 自然語言處理（NLP）
  • 電腦視覺
  • 機器學習
  • 情境感知
  • 物聯網 (IoT)
  • 其他技術

9. 全球多模態人工智慧市場（以最終用戶分類）

  • 媒體與娛樂
  • 銀行、金融服務和保險（BFSI）
  • 衛生保健
  • 零售與電子商務
  • 汽車與運輸
  • 製造業
  • 政府/國防
  • 通訊
  • 教育
  • 其他最終用戶

第10章：全球多模態人工智慧市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章：主要趨勢

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第12章：公司簡介

  • Google
  • OpenAI
  • Twelve Labs
  • Microsoft
  • IBM
  • Amazon Web Services（AWS）
  • Meta Platforms
  • Apple
  • Anthropic
  • Hugging Face
  • Runway
  • Adept AI
  • DeepMind
  • Stability AI
  • Rephrase.ai
Product Code: SMRC31838

According to Stratistics MRC, the Global Multimodal AI Market is accounted for $2.40 billion in 2025 and is expected to reach $23.8 billion by 2032 growing at a CAGR of 38.8% during the forecast period. Multimodal AI refers to artificial intelligence systems designed to process, understand, and generate information from multiple types of data simultaneously, such as text, images, audio, and video. Unlike traditional AI models that specialize in a single modality, multimodal AI integrates these diverse data sources to create richer and more context-aware insights. This capability enables applications like image captioning, video analysis, voice-activated assistants, and cross-modal search. By combining different modalities, it can improve accuracy, reasoning, and human-like understanding. Multimodal AI represents a step toward more versatile and intelligent systems capable of interpreting complex, real-world information seamlessly.

Market Dynamics:

Driver:

Improved accuracy and robustness

Cross-modal models combine text image audio and sensor data to improve contextual understanding and prediction reliability. Multimodal systems outperform single-modality models in tasks such as emotion detection object tracking and conversational response generation. Integration with edge devices and cloud platforms supports real-time inference and adaptive learning across distributed environments. Enterprises use multimodal AI to enhance decision-making automates workflows and personalize user experiences. These capabilities are driving platform innovation and operational efficiency across mission-critical applications.

Restraint:

High computational demands

Training and inference require advanced GPUs large datasets and optimized pipelines for cross-modal fusion and alignment. Infrastructure costs increase with model complexity and latency requirements across real-time applications. Smaller firms and academic labs face challenges in accessing compute resources and managing deployment across edge and cloud environments. Energy consumption and carbon footprint remain concerns for large-scale multimodal systems.

Opportunity:

Advancements in natural interaction

Voice gesture and facial recognition enable intuitive interfaces and immersive user experiences across digital and physical environments. AI agents use multimodal cues to interpret intent emotion and context with higher precision and responsiveness. Integration with AR VR robotics and smart devices expands use cases across consumer industrial and healthcare domains. Demand for human-like interaction and inclusive design is rising across multilingual neurodiverse and aging populations. These trends are fostering growth across multimodal UX conversational AI and assistive technology ecosystems.

Threat:

Regulatory and privacy challenges

Data collection from multiple modalities raises concerns around consent surveillance and biometric security across public and private sectors. Regulatory frameworks for facial recognition voice data and behavioral tracking vary across jurisdictions and use cases. Lack of transparency in model decision-making complicates auditability accountability and ethical oversight. Public scrutiny around bias manipulation and misinformation increases pressure on vendors and developers. These risks continue to constrain platform adoption across sensitive industries and regulated environments.

Covid-19 Impact:

The pandemic accelerated interest in multimodal AI as remote interaction and digital engagement surged across healthcare retail education and public services. Hospitals used multimodal platforms for telemedicine diagnostics and patient monitoring with improved contextual awareness. Retailers adopted AI for virtual try-ons voice commerce and sentiment analysis across mobile and web channels. Educational institutions deployed multimodal tools for remote learning assessment and accessibility support. Public awareness of AI-driven interaction and automation increased during lockdowns and recovery phases. Post-pandemic strategies now include multimodal AI as a core pillar of digital transformation operational resilience and user engagement.

The image data segment is expected to be the largest during the forecast period

The image data segment is expected to account for the largest market share during the forecast period due to its foundational role in computer vision facial recognition and object detection across multimodal platforms. Integration with text audio and sensor inputs improves scene understanding contextual analysis and decision accuracy across real-time applications. Image-based models support use cases in healthcare imaging autonomous navigation retail analytics and surveillance systems. Demand for scalable high-resolution image processing is rising across industrial consumer and government domains. Vendors offer modular pipelines and pretrained models for rapid deployment and customization.

The natural language processing (NLP) segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the natural language processing (NLP) segment is predicted to witness the highest growth rate as multimodal platforms scale across conversational AI content generation and sentiment analysis. NLP models integrate with image audio and gesture data to enhance contextual understanding response accuracy and emotional intelligence. Applications include virtual assistants customer support educational tools and accessibility platforms across mobile desktop and embedded environments. Demand for multilingual emotion-aware and domain-specific NLP is rising across global markets and diverse user segments. Vendors offer transformer-based architectures and fine-tuned models for specialized tasks and industries.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its advanced AI infrastructure research ecosystem and enterprise adoption across healthcare defense retail and media sectors. U.S. and Canadian firms deploy multimodal platforms across diagnostics autonomous systems customer experience and public safety applications. Investment in generative AI edge computing and cloud-native architecture supports scalability performance and compliance across regulated environments. Presence of leading AI labs universities and technology firms drives model development standardization and commercialization. Regulatory bodies support AI through sandbox programs ethical frameworks and innovation grants.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as mobile penetration digital innovation and government-backed AI programs converge across smart cities education healthcare and public services. Countries like China India Japan and South Korea scale multimodal platforms across urban infrastructure rural outreach and industrial automation. Local firms launch multilingual culturally adapted models tailored to regional use cases and compliance norms. Investment in edge AI robotics and real-time interaction supports platform expansion across consumer enterprise and government domains. Demand for scalable low-cost multimodal solutions rises across urban centers manufacturing zones and underserved populations. These trends are accelerating regional growth across multimodal AI ecosystems and innovation clusters.

Key players in the market

Some of the key players in Multimodal AI Market include Google, OpenAI, Twelve Labs, Microsoft, IBM, Amazon Web Services (AWS), Meta Platforms, Apple, Anthropic, Hugging Face, Runway, Adept AI, DeepMind, Stability AI and Rephrase.ai.

Key Developments:

In May 2025, OpenAI launched GPT-4o, a fully multimodal model capable of processing text, image, voice, and code in real time. Integrated into ChatGPT Enterprise and API endpoints, GPT-4o supports sensory fusion and agentic reasoning, enabling dynamic applications across customer support, education, and creative industries.

In March 2025, Google DeepMind launched Gemini 2.5, its most advanced multimodal AI model capable of processing text, image, video, and audio simultaneously. Gemini 2.5 introduced improved reasoning and cross-format understanding, enabling businesses to deploy richer customer insights, creative generation, and operational analytics across diverse media inputs.

Components Covered:

  • Software
  • Services

Modalities Covered:

  • Text Data
  • Speech & Voice Data
  • Image Data
  • Video Data
  • Sensor & Numerical Data
  • Other Modalities

Multimodal AI Types Covered:

  • Generative Multimodal AI
  • Interactive Multimodal AI
  • Explanatory Multimodal AI
  • Translative Multimodal AI
  • Other Multimodal AI Types

Technologies Covered:

  • Natural Language Processing (NLP)
  • Computer Vision
  • Machine Learning
  • Context Awareness
  • Internet of Things (IoT)
  • Other Technologies

End Users Covered:

  • Media & Entertainment
  • Banking, Financial Services & Insurance (BFSI)
  • Healthcare
  • Retail & E-Commerce
  • Automotive & Transportation
  • Manufacturing
  • Government & Defense
  • Telecommunications
  • Education
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Multimodal AI Market, By Component

  • 5.1 Introduction
  • 5.2 Software
  • 5.3 Services

6 Global Multimodal AI Market, By Modality

  • 6.1 Introduction
  • 6.2 Text Data
  • 6.3 Speech & Voice Data
  • 6.4 Image Data
  • 6.5 Video Data
  • 6.6 Sensor & Numerical Data
  • 6.7 Other Modalities

7 Global Multimodal AI Market, By Multimodal AI Type

  • 7.1 Introduction
  • 7.2 Generative Multimodal AI
  • 7.3 Interactive Multimodal AI
  • 7.4 Explanatory Multimodal AI
  • 7.5 Translative Multimodal AI
  • 7.6 Other Multimodal AI Types

8 Global Multimodal AI Market, By Technology

  • 8.1 Introduction
  • 8.2 Natural Language Processing (NLP)
  • 8.3 Computer Vision
  • 8.4 Machine Learning
  • 8.5 Context Awareness
  • 8.6 Internet of Things (IoT)
  • 8.7 Other Technologies

9 Global Multimodal AI Market, By End User

  • 9.1 Introduction
  • 9.2 Media & Entertainment
  • 9.3 Banking, Financial Services & Insurance (BFSI)
  • 9.4 Healthcare
  • 9.5 Retail & E-Commerce
  • 9.6 Automotive & Transportation
  • 9.7 Manufacturing
  • 9.8 Government & Defense
  • 9.9 Telecommunications
  • 9.10 Education
  • 9.11 Other End Users

10 Global Multimodal AI Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Google
  • 12.2 OpenAI
  • 12.3 Twelve Labs
  • 12.4 Microsoft
  • 12.5 IBM
  • 12.6 Amazon Web Services (AWS)
  • 12.7 Meta Platforms
  • 12.8 Apple
  • 12.9 Anthropic
  • 12.10 Hugging Face
  • 12.11 Runway
  • 12.12 Adept AI
  • 12.13 DeepMind
  • 12.14 Stability AI
  • 12.15 Rephrase.ai

List of Tables

  • Table 1 Global Multimodal AI Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Multimodal AI Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Multimodal AI Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global Multimodal AI Market Outlook, By Services (2024-2032) ($MN)
  • Table 5 Global Multimodal AI Market Outlook, By Modality (2024-2032) ($MN)
  • Table 6 Global Multimodal AI Market Outlook, By Text Data (2024-2032) ($MN)
  • Table 7 Global Multimodal AI Market Outlook, By Speech & Voice Data (2024-2032) ($MN)
  • Table 8 Global Multimodal AI Market Outlook, By Image Data (2024-2032) ($MN)
  • Table 9 Global Multimodal AI Market Outlook, By Video Data (2024-2032) ($MN)
  • Table 10 Global Multimodal AI Market Outlook, By Sensor & Numerical Data (2024-2032) ($MN)
  • Table 11 Global Multimodal AI Market Outlook, By Other Modalities (2024-2032) ($MN)
  • Table 12 Global Multimodal AI Market Outlook, By Multimodal AI Type (2024-2032) ($MN)
  • Table 13 Global Multimodal AI Market Outlook, By Generative Multimodal AI (2024-2032) ($MN)
  • Table 14 Global Multimodal AI Market Outlook, By Interactive Multimodal AI (2024-2032) ($MN)
  • Table 15 Global Multimodal AI Market Outlook, By Explanatory Multimodal AI (2024-2032) ($MN)
  • Table 16 Global Multimodal AI Market Outlook, By Translative Multimodal AI (2024-2032) ($MN)
  • Table 17 Global Multimodal AI Market Outlook, By Other Multimodal AI Types (2024-2032) ($MN)
  • Table 18 Global Multimodal AI Market Outlook, By Technology (2024-2032) ($MN)
  • Table 19 Global Multimodal AI Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 20 Global Multimodal AI Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 21 Global Multimodal AI Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 22 Global Multimodal AI Market Outlook, By Context Awareness (2024-2032) ($MN)
  • Table 23 Global Multimodal AI Market Outlook, By Internet of Things (IoT) (2024-2032) ($MN)
  • Table 24 Global Multimodal AI Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 25 Global Multimodal AI Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global Multimodal AI Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 27 Global Multimodal AI Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2024-2032) ($MN)
  • Table 28 Global Multimodal AI Market Outlook, By Healthcare (2024-2032) ($MN)
  • Table 29 Global Multimodal AI Market Outlook, By Retail & E-Commerce (2024-2032) ($MN)
  • Table 30 Global Multimodal AI Market Outlook, By Automotive & Transportation (2024-2032) ($MN)
  • Table 31 Global Multimodal AI Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 32 Global Multimodal AI Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 33 Global Multimodal AI Market Outlook, By Telecommunications (2024-2032) ($MN)
  • Table 34 Global Multimodal AI Market Outlook, By Education (2024-2032) ($MN)
  • Table 35 Global Multimodal AI Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.