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市场调查报告书
商品编码
2021754

多模态生成式人工智慧市场预测至2034年：按模态、部署类型、应用和区域分類的全球分析

Multimodal Generative AI Market Forecasts to 2034 - Global Analysis By Modality (Text, Image, Audio, Video and Sensor Data), Deployment, Application and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球多模态生成式人工智慧市场预计将在 2026 年达到 51 亿美元，并在预测期内以 13.4% 的复合年增长率成长，到 2034 年达到 140 亿美元。

多模态生成式人工智慧是指能够解读、处理和产生各种资料格式内容（包括文字、影像、音讯和影片）的前沿人工智慧系统。透过整合多种模态，这些模型能够提供上下文丰富且智慧的输出，支援诸如图像转文字、生成影片以及根据音讯提示创建视觉效果等任务。这种整合能够改善人机交互，增强创造力，并简化各领域的自动化流程。透过连结不同的输入，多模态人工智慧能够实现沉浸式体验、辅助决策和创新应用，而这些对于单模态人工智慧模型而言是难以实现甚至无法实现的。

根据史丹佛 HAI AI 指数 2024，2023 年全球发布了 149 个基础模型，是 2022 年发布的约 70 个模型的两倍多。

对人工智慧驱动的内容创作的需求日益增长。

对人工智慧驱动的内容生成日益增长的需求，正推动多模态生成式人工智慧在媒体、行销和娱乐领域的广泛应用。企业正利用这些系统有效率地创建图像、影片、文字和音频，从而减少人工投入和营运成本。透过自动化创新工作流程并确保高品质的交付成果，企业可以提供个人化内容，增强用户互动并提升品牌影响力。这种对可扩展、创新且经济高效的内容解决方案的需求，正在推动数位行销和创新产业中多模态人工智慧解决方案的蓬勃发展，使其成为现代企业不可或缺的工具。

计算成本高

多模态生成式人工智慧需要大量的运算资源，这是一大障碍。训练和运行能够同时处理文字、图像和音讯的模型需要高性能GPU、大容量储存和强大的网络，从而导致高昂的能源和营运成本。对于中小企业而言，这些成本往往难以承受，阻碍了其采用。持续的维护、更新和扩展进一步加重了财务负担。因此，有效部署多模态人工智慧所需的基础设施和资源高成本，正在减缓市场成长，使得企业难以采用这些先进解决方案，儘管它们具有潜在的优势。

媒体和娱乐产业的扩张

媒体和娱乐产业可以利用多模态生成式人工智慧（AI）来创作涵盖文字、视觉、音讯和影片等多种形式的多元化内容。串流媒体平台、游戏工作室和製作公司可以透过AI实现内容创作自动化，从而节省时间并提升创造力。个人化故事、互动体验和虚拟角色可以有效率地製作，进而提高观众参与度。此外，AI还能大规模简化配音、字幕和内容在地化流程。随着消费者对创新和互动内容的需求日益增长，多模态AI为推动创新、提高製作效率以及在娱乐和创新领域开闢新的收入来源提供了机会。

虚假资讯和深度造假的风险

多模态生成式人工智慧可能被滥用，用于製作深度造假、假新闻和操纵媒体，这构成重大威胁。此类内容传播迅速，可能造成声誉、经济或社会损害。随着监管力道的加大，伦理和法律问题也随之出现，要求各组织机构实施严格的安全措施。不当管理或恶意使用这些人工智慧系统可能导致信誉受损、承担法律责任，并降低公众信任度。产生误导性或有害内容的风险是人工智慧普及应用的一大挑战，因此，对于部署多模态人工智慧解决方案的公司而言，安全性和负责任的使用至关重要。

新型冠状病毒（COVID-19）的影响：

新冠疫情加速了数位化解决方案和远距办公的转型，推动了多模态生成式人工智慧市场的发展。人们对线上教育、远程办公和虚拟协作的日益依赖，催生了对能够整合和分析文字、图像和音讯的人工智慧模型的需求。医疗和研究机构利用多模态人工智慧进行诊断、药物研发和远端医疗，以有效应对疫情带来的挑战。儘管面临供应链中断和运算资源受限的困境，这场危机仍然促进了人工智慧技术的创新和应用。新冠疫情凸显了多模态人工智慧在流程自动化、内容生成以及支援全球各产业关键决策的价值。

在预测期内，文本产业预计将占据最大的市场份额。

由于应用范围广泛，文本领域预计将在预测期内占据最大的市场份额。专门针对文字的AI解决方案支援内容创作、自然语言处理、自动报告和虚拟助手，从而提高效率并提供个人化体验。文字资料相对容易收集、处理和与其他模态资料集成，这有助于提升多模态AI的效能。对AI驱动的客户参与、行销和知识解决方案日益增长的需求进一步巩固了文本领域的地位。因此，文本将继续成为多模态生成式AI领域中最具主导地位和影响力的领域。

在预测期内，医疗保健和生命科学产业预计将呈现最高的复合年增长率。

在预测期内，医疗保健和生命科学领域预计将呈现最高的成长率，这主要得益于人工智慧在诊断、个人化医疗、远端医疗和药物研发等领域的日益普及。透过整合文字、医学影像、感测器测量数据和语音数据，多模态人工智慧能够提供精准的洞察，增强临床决策，并提高效率。对数位医疗投资的增加、对远端医疗服务需求的成长以及对更快、更经济高效的检测的追求，是推动该领域快速扩张的主要因素，也使医疗保健和生命科学成为全球多模态人工智慧生态系统中成长最快的领域。

市占率最大的地区：

在整个预测期内，北美预计将保持最大的市场份额，这主要得益于该地区集中了众多领先的人工智慧技术公司、大量的研发投入以及各行业的早期应用。该地区凭藉先进的IT基础设施、广泛的云端运算以及强大的产学研合作，促进了创新。医疗保健、金融、媒体和电子商务等关键产业正在采用多模态人工智慧进行分析、自动化和内容创作。政府的支持和成熟的人工智慧生态系统进一步巩固了其市场地位。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于快速的数位化进程和对人工智慧技术的投资。中国、印度和日本等国家在医疗保健、金融、零售和製造业等领域的需求领先。蓬勃发展的Start-Ups生态系统、政府的支持性政策以及不断完善的云端运算基础设施，都为加速成长做出了贡献。高人口密度、网路普及率的提高以及技术意识的增强，进一步推动了人工智慧的应用。这些趋势共同作用，使亚太地区成为全球成长最快的地区，为各行各业的多模态生成式人工智慧解决方案创造了巨大的机会。

免费客製化服务：

所有购买此报告的客户均可享受以下免费自订选项之一：

  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户要求，我们可以提供主要国家和地区的市场估算和预测，以及复合年增长率（註：需要进行可行性测试）。
  • 竞争性标竿分析
    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章执行摘要

  • 市场概览及主要亮点
  • 驱动因素、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球多模态生成式人工智慧市场：以模态划分

  • 文字
  • 影像
  • 声音的
  • 影片
  • 感测器数据

第六章：全球多模态生成式人工智慧市场：依部署方式划分

  • 云
  • 边缘
  • 杂交种

第七章：全球多模态生成式人工智慧市场：按应用划分

  • 医疗保健和生命科学
  • 银行、金融服务、保险业 (BFSI)
  • 汽车和运输业
  • 工业和製造业
  • 人机介面
  • 零售与电子商务
  • 媒体与娱乐
  • 教育和培训

第八章：全球多模态生成式人工智慧市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第九章 战略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十章：产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十一章：公司简介

  • Google
  • OpenAI
  • Twelve Labs
  • Aimesoft
  • Jina AI
  • Uniphore
  • Reka AI
  • Amazon Web Services
  • IBM
  • Microsoft
  • Runway
  • Aiberry
  • Aimsoft
  • Hoppr
  • Jiva.ai
  • Modality.AI
  • OpenStream.ai
  • Perceive AI
Product Code: SMRC34977

According to Stratistics MRC, the Global Multimodal Generative AI Market is accounted for $5.1 billion in 2026 and is expected to reach $14.0 billion by 2034 growing at a CAGR of 13.4% during the forecast period. Multimodal Generative AI represents cutting-edge AI systems that can interpret, process, and create content across various data formats, including text, visuals, sound, and video. By merging multiple modalities, these models deliver more context-rich and intelligent outputs, supporting tasks like converting images to text, generating videos, or producing visuals from audio cues. This integration improves human-computer interaction, boosts creativity, and streamlines automation in different sectors. By linking diverse inputs, multimodal AI enables immersive experiences, informed decision-making, and innovative applications that were challenging or impossible with single-modality AI models.

According to the Stanford HAI AI Index 2024, 149 foundation models were released globally in 2023, more than double the ~70 released in 2022.

Market Dynamics:

Driver:

Increasing demand for AI-powered content creation

The rising need for AI-assisted content generation is driving the adoption of multimodal generative AI across media, marketing, and entertainment sectors. Organizations are using these systems to create images, videos, text, and audio efficiently, reducing manual effort and operational costs. By automating creative workflows and ensuring high-quality outputs, businesses can deliver personalized content that boosts engagement and strengthens brand presence. This demand for scalable, innovative, and cost-effective content solutions is propelling the growth of multimodal AI solutions in digital marketing and creative industries, establishing them as essential tools for modern enterprises.

Restraint:

High computational costs

The substantial computational requirements of multimodal generative AI pose a significant barrier. Training and running models that handle text, images, and audio together demand powerful GPUs, large storage, and robust networks, resulting in high energy and operational costs. Small and mid-sized businesses often find these expenses prohibitive, limiting adoption. Continuous maintenance, updates, and scaling further increase financial strain. As a result, the high cost of infrastructure and resources required for effective multimodal AI deployment slows market growth, making it challenging for organizations to implement these advanced solutions despite their potential benefits.

Opportunity:

Expansion in media and entertainment

Media and entertainment industries can capitalize on multimodal generative AI to create diverse content across text, visuals, audio, and video. Streaming platforms, gaming studios, and production houses can use AI to automate content creation, saving time while boosting creativity. Personalized narratives, interactive experiences, and virtual characters can be produced efficiently, enhancing audience engagement. Additionally, AI simplifies dubbing, subtitling, and content localization at scale. As consumers increasingly demand innovative and interactive content, multimodal AI provides an opportunity to drive innovation, improve production efficiency, and unlock new revenue streams in the entertainment and creative sectors.

Threat:

Risk of misinformation and deepfakes

The potential misuse of multimodal generative AI for creating deepfakes, fake news, and manipulated media represents a major threat. Such content can spread quickly, causing reputational, financial, or social harm. Ethical and legal issues arise as regulators increase oversight, requiring organizations to implement strict safeguards. Mismanagement or malicious use of these AI systems can result in loss of credibility, legal consequences, and reduced public trust. This risk of generating misleading or harmful content poses a challenge to adoption and acceptance, making security and responsible use essential considerations for businesses deploying multimodal AI solutions.

Covid-19 Impact:

The COVID-19 pandemic boosted the multimodal generative AI market by accelerating the shift toward digital solutions and remote operations. Increased reliance on online education, telework, and virtual collaboration created demand for AI models capable of analyzing text, images, and audio together. Healthcare and research organizations used multimodal AI for diagnostics, drug discovery, and telehealth, addressing pandemic-related challenges efficiently. Despite disruptions in supply chains and limited computing resources, the crisis drove innovation and adoption of AI technologies. COVID-19 underscored the value of multimodal AI in automating processes, generating content, and supporting critical decision-making in various industries worldwide.

The text segment is expected to be the largest during the forecast period

The text segment is expected to account for the largest market share during the forecast period because of its extensive applications across sectors. AI solutions focused on text support content creation, natural language processing, automated reporting, and virtual assistants, delivering efficiency and tailored experiences. Text data is relatively easier to gather, process, and combine with other modalities, improving multimodal AI performance. The rising demand for AI-driven customer engagement, marketing, and knowledge solutions further strengthens its position. As a result, text continues to be the dominant and most impactful segment within the multimodal generative AI landscape.

The healthcare & life sciences segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare & life sciences segment is predicted to witness the highest growth rate, driven by rising adoption of AI for diagnostics, personalized treatment, telehealth, and drug development. By integrating text, medical imaging, sensor readings, and audio data, multimodal AI delivers precise insights, enhances clinical decisions, and improves efficiency. Increased investments in digital health, growing demand for remote medical services, and the push for faster, cost-effective research are major contributors to this segment's rapid expansion, positioning healthcare and life sciences as the fastest-growing area in the global multimodal AI ecosystem.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, fueled by a concentration of leading AI technology companies, significant research and development investments, and early adoption across sectors. The region benefits from advanced IT infrastructure, widespread cloud computing, and strong industry-academia collaboration, promoting innovation. Critical industries including healthcare, finance, media, and e-commerce are implementing multimodal AI for analytics, automation, and content creation. Government support and a mature AI ecosystem further reinforce its position.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid digital adoption and investments in AI technologies. Countries like China, India, and Japan are fueling demand in healthcare, finance, retail, and manufacturing industries. A growing startup ecosystem, supportive government policies, and enhanced cloud computing infrastructure contribute to accelerating growth. High population density, rising internet usage, and increased technological awareness further encourage AI deployment. Together, these trends establish Asia-Pacific as the fastest-growing region globally, offering significant opportunities for multimodal generative AI solutions across multiple sectors.

Key players in the market

Some of the key players in Multimodal Generative AI Market include Google, OpenAI, Twelve Labs, Aimesoft, Jina AI, Uniphore, Reka AI, Amazon Web Services, IBM, Microsoft, Runway, Aiberry, Aimsoft, Hoppr, Jiva.ai, Modality.AI, OpenStream.ai and Perceive AI.

Key Developments:

In January 2026, Microsoft Corp has been awarded a $170,444,462 firm-fixed-price task order for the Cloud One Program by the U.S. Department of War. The contract will provide Microsoft Azure cloud service offerings to support the Air Force's Cloud One Program and its customers. Work on the project will be performed at Microsoft's designated facilities across the contiguous United States.

In December 2025, IBM and Confluent, Inc. announced they have entered into a definitive agreement under which IBM will acquire all of the issued and outstanding common shares of Confluent for $31 per share, representing an enterprise value of $11 billion. Confluent provides a leading open-source enterprise data streaming platform that connects processes and governs reusable and reliable data and events in real time, foundational for the deployment of AI.

In November 2025, Amazon Web Services (AWS) and OpenAI announced a multi-year, strategic partnership that provides AWS's world-class infrastructure to run and scale OpenAI's core artificial intelligence (AI) workloads starting immediately. Under this new $38 billion agreement, which will have continued growth over the next seven years, OpenAI is accessing AWS compute comprising hundreds of thousands of state-of-the-art NVIDIA GPUs, with the ability to expand to tens of millions of CPUs to rapidly scale agentic workloads.

Modalities Covered:

  • Text
  • Image
  • Audio
  • Video
  • Sensor Data

Deployments Covered:

  • Cloud
  • Edge
  • Hybrid

Applications Covered:

  • Healthcare & Life Sciences
  • BFSI (Banking, Financial Services, Insurance)
  • Automotive & Transportation
  • Industrial & Manufacturing
  • Human-Machine Interfaces
  • Retail & E-commerce
  • Media & Entertainment
  • Education & Training

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Multimodal Generative AI Market, By Modality

  • 5.1 Text
  • 5.2 Image
  • 5.3 Audio
  • 5.4 Video
  • 5.5 Sensor Data

6 Global Multimodal Generative AI Market, By Deployment

  • 6.1 Cloud
  • 6.2 Edge
  • 6.3 Hybrid

7 Global Multimodal Generative AI Market, By Application

  • 7.1 Healthcare & Life Sciences
  • 7.2 BFSI (Banking, Financial Services, Insurance)
  • 7.3 Automotive & Transportation
  • 7.4 Industrial & Manufacturing
  • 7.5 Human-Machine Interfaces
  • 7.6 Retail & E-commerce
  • 7.7 Media & Entertainment
  • 7.8 Education & Training

8 Global Multimodal Generative AI Market, By Geography

  • 8.1 North America
    • 8.1.1 United States
    • 8.1.2 Canada
    • 8.1.3 Mexico
  • 8.2 Europe
    • 8.2.1 United Kingdom
    • 8.2.2 Germany
    • 8.2.3 France
    • 8.2.4 Italy
    • 8.2.5 Spain
    • 8.2.6 Netherlands
    • 8.2.7 Belgium
    • 8.2.8 Sweden
    • 8.2.9 Switzerland
    • 8.2.10 Poland
    • 8.2.11 Rest of Europe
  • 8.3 Asia Pacific
    • 8.3.1 China
    • 8.3.2 Japan
    • 8.3.3 India
    • 8.3.4 South Korea
    • 8.3.5 Australia
    • 8.3.6 Indonesia
    • 8.3.7 Thailand
    • 8.3.8 Malaysia
    • 8.3.9 Singapore
    • 8.3.10 Vietnam
    • 8.3.11 Rest of Asia Pacific
  • 8.4 South America
    • 8.4.1 Brazil
    • 8.4.2 Argentina
    • 8.4.3 Colombia
    • 8.4.4 Chile
    • 8.4.5 Peru
    • 8.4.6 Rest of South America
  • 8.5 Rest of the World (RoW)
    • 8.5.1 Middle East
      • 8.5.1.1 Saudi Arabia
      • 8.5.1.2 United Arab Emirates
      • 8.5.1.3 Qatar
      • 8.5.1.4 Israel
      • 8.5.1.5 Rest of Middle East
    • 8.5.2 Africa
      • 8.5.2.1 South Africa
      • 8.5.2.2 Egypt
      • 8.5.2.3 Morocco
      • 8.5.2.4 Rest of Africa

9 Strategic Market Intelligence

  • 9.1 Industry Value Network and Supply Chain Assessment
  • 9.2 White-Space and Opportunity Mapping
  • 9.3 Product Evolution and Market Life Cycle Analysis
  • 9.4 Channel, Distributor, and Go-to-Market Assessment

10 Industry Developments and Strategic Initiatives

  • 10.1 Mergers and Acquisitions
  • 10.2 Partnerships, Alliances, and Joint Ventures
  • 10.3 New Product Launches and Certifications
  • 10.4 Capacity Expansion and Investments
  • 10.5 Other Strategic Initiatives

11 Company Profiles

  • 11.1 Google
  • 11.2 OpenAI
  • 11.3 Twelve Labs
  • 11.4 Aimesoft
  • 11.5 Jina AI
  • 11.6 Uniphore
  • 11.7 Reka AI
  • 11.8 Amazon Web Services
  • 11.9 IBM
  • 11.10 Microsoft
  • 11.11 Runway
  • 11.12 Aiberry
  • 11.13 Aimsoft
  • 11.14 Hoppr
  • 11.15 Jiva.ai
  • 11.16 Modality.AI
  • 11.17 OpenStream.ai
  • 11.18 Perceive AI

List of Tables

  • Table 1 Global Multimodal Generative AI Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Multimodal Generative AI Market Outlook, By Modality (2023-2034) ($MN)
  • Table 3 Global Multimodal Generative AI Market Outlook, By Text (2023-2034) ($MN)
  • Table 4 Global Multimodal Generative AI Market Outlook, By Image (2023-2034) ($MN)
  • Table 5 Global Multimodal Generative AI Market Outlook, By Audio (2023-2034) ($MN)
  • Table 6 Global Multimodal Generative AI Market Outlook, By Video (2023-2034) ($MN)
  • Table 7 Global Multimodal Generative AI Market Outlook, By Sensor Data (2023-2034) ($MN)
  • Table 8 Global Multimodal Generative AI Market Outlook, By Deployment (2023-2034) ($MN)
  • Table 9 Global Multimodal Generative AI Market Outlook, By Cloud (2023-2034) ($MN)
  • Table 10 Global Multimodal Generative AI Market Outlook, By Edge (2023-2034) ($MN)
  • Table 11 Global Multimodal Generative AI Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 12 Global Multimodal Generative AI Market Outlook, By Application (2023-2034) ($MN)
  • Table 13 Global Multimodal Generative AI Market Outlook, By Healthcare & Life Sciences (2023-2034) ($MN)
  • Table 14 Global Multimodal Generative AI Market Outlook, By BFSI (Banking, Financial Services, Insurance) (2023-2034) ($MN)
  • Table 15 Global Multimodal Generative AI Market Outlook, By Automotive & Transportation (2023-2034) ($MN)
  • Table 16 Global Multimodal Generative AI Market Outlook, By Industrial & Manufacturing (2023-2034) ($MN)
  • Table 17 Global Multimodal Generative AI Market Outlook, By Human-Machine Interfaces (2023-2034) ($MN)
  • Table 18 Global Multimodal Generative AI Market Outlook, By Retail & E-commerce (2023-2034) ($MN)
  • Table 19 Global Multimodal Generative AI Market Outlook, By Media & Entertainment (2023-2034) ($MN)
  • Table 20 Global Multimodal Generative AI Market Outlook, By Education & Training (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.