US Multimodal Al Market Size, Share & Industry Trends Analysis Report By Offering, By Type (Generative, Translative, Interactive, and Explanatory), By Technology, By Data Modality, By Vertical, Growth Forecast, 2023 - 2030

The USA Multimodal Al Market size is expected to reach $2.2 billion by 2030, rising at a market growth of 30.5% CAGR during the forecast period.

The multimodal AI market in the United States is experiencing significant growth and advancements. In the US, this technology is increasingly being integrated across healthcare, automotive, retail, education, and customer service sectors. Companies are leveraging multimodal AI for applications like virtual assistants, personalized recommendations, diagnostics, and enhanced user experiences.

Technology giants, startups, and research institutions are making significant investments in developing and advancing multimodal AI technologies. This investment fosters innovation and pushes the boundaries of what these systems can achieve. The US is home to a thriving startup ecosystem, and multimodal AI has been a focal point for many emerging companies. Venture capital funding has poured into startups specializing in multimodal AI, enabling them to innovate and develop new applications and use cases. These startups often bring fresh perspectives and niche solutions, contributing to the overall innovation in the field.

Major technology companies in the United States, including Apple, Google, Microsoft, and Amazon, have invested significant resources in the study, development, and implementation of multimodal AI technologies. These companies invest in both in-house R&D and acquisitions of startups specializing in AI, thereby fostering innovation and pushing the envelope in terms of what multimodal AI systems can achieve.

Regulatory frameworks and standards around AI and data usage are evolving. The US government and various agencies are exploring policies and guidelines to govern AI technologies' ethical and responsible use. The Biden-Harris Administration is committed to advancing responsible AI systems that are ethical, trustworthy, and safe and serve the public good. The fiscal year (FY) 2023 President's Budget Request included substantial and specific funding requests for AI R&D as part of a broad expansion of federally funded R&D to advance key technologies and address societal challenges. The CHIPS and Science Act of 2022 and Consolidated Appropriations Act of 2023 reflect Administration and Congressional support for an expansion of federally funded R&D, including AI R&D.

Market Trends

Increasing demand for multimodal AI owing to rising data availability

The US has witnessed an explosion of digital data from various sources such as social media, e-commerce transactions, IoT devices, sensors, and more. This diverse data landscape includes text, images, videos, audio, and sensor-generated information, providing a wealth of multimodal data for AI systems. With the proliferation of smartphones, wearables, and connected devices, individuals generate vast amounts of data daily. This data, ranging from location information to user behavior, contributes to the multimodal AI dataset, enabling more comprehensive analyses and predictions.

Social media platforms generate massive multimodal content—photos, videos, comments, and reactions—providing insights into consumer sentiments, trends, and preferences. AI algorithms analyze this data for sentiment analysis, trend identification, and targeted marketing. Industries across the US are increasingly relying on data-driven strategies. Companies recognize the value of data in making informed decisions, driving innovation, and gaining competitive advantages, leading to a surge in demand for AI systems capable of handling multimodal data. The confluence of these factors—ample availability of diverse data sources, technological advancements in data collection, and the growing reliance on data-driven insights—has propelled the demand for multimodal AI solutions in the US.

Growing usage of multimodal AI in retail and e-commerce

Multimodal AI has been making significant inroads into the retail and e-commerce sectors in the US, transforming various aspects of the industry. Platforms like Pinterest and Google Lens use this technology to allow users to search for items by uploading images. Moreover, integrating voice assistants with e-commerce platforms enables users to shop using voice commands. Amazon's Alexa, for example, facilitates voice-based shopping on Amazon's platform, allowing users to add items to their cart or make purchases through voice commands.

Combining data from various sources like browsing history, purchase behavior, and demographic information with AI enables personalized product recommendations. Retailers like Amazon and Netflix use this approach to suggest products or content tailored to individual preferences. Multimodal AI-powered chatbots assist customers in finding products, providing information, and offering support. For instance, The North Face assists customers in locating the appropriate products based on their needs and preferences via an AI-powered chatbot.

Furthermore, multimodal AI analyzes data from various sources to predict customer demand, allowing retailers to optimize inventory and supply chain management. Companies like Walmart use AI-driven demand forecasting to streamline inventory levels and enhance efficiency. These applications demonstrate how multimodal AI is revolutionizing the retail and e-commerce landscape in the US, providing enhanced experiences for customers, optimizing operations, and driving business growth.

Competition Analysis

The multimodal AI market is becoming increasingly competitive, with numerous players entering the space. This competition stimulates innovation and broadens the market, providing businesses and consumers with a greater selection of products and services. Most well-known companies present in the US multimodal AI market are Open AI, Microsoft, Facebook (Meta), IBM, Google (Alphabet Inc.), NVIDIA, Salesforce, Adobe, etc.

OpenAI is known for its work in artificial general intelligence. They have been involved in projects like GPT-3 (Generative Pre-trained Transformer 3), a powerful language model capable of multimodal tasks, and they continue to explore applications of advanced AI technologies.

Likewise, Google has been actively involved in multimodal AI with projects like BERT (Bidirectional Encoder Representations from Transformers) for natural language processing. Google's research division, Google Research, consistently advances multimodal AI technologies.

Microsoft has been investing in multimodal AI applications across its products. They continue to work on AI technologies for various domains, including computer vision, speech recognition, and natural language processing, integrating them into services like Azure Cognitive Services.

Salesforce has invested in AI for customer relationship management (CRM). Their platform, Einstein, incorporates AI capabilities, including natural language processing, to provide personalized insights and predictions for sales and customer service. These organizations are pioneers in researching, developing, and implementing multimodal artificial intelligence across diverse sectors, fostering advancements in computer vision, natural language processing, and other related fields.

List of Key Companies Profiled

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

US Multimodal Al Market Report Segmentation

By Offering

• Solution
• Solution Deployment Type
  • Cloud
  • On-premise
• Solution Type
  • Platform
  • Software
  • Framework
• Services

By Type

• Generative
• Translative
• Interactive
• Explanatory

By Technology

• Natural Language Processing
• Machine Learning
• Computer Vision
• Context Awareness
• Internet of Things

By Data Modality

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

By Vertical

• BFSI
• Government & Public Sector
• Automotive, Transportation & Logistics
• Healthcare & Lifesciences
• Media & Entertainment
• Manufacturing
• Retail & eCommerce
• Telecommunications
• Others

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 USA Multimodal AI Market, by Offering
1.4.2 USA Multimodal AI Market, by Type
1.4.3 USA Multimodal AI Market, by Technology
1.4.4 USA Multimodal AI Market, by Data Modality
1.4.5 USA Multimodal AI Market, by Vertical
1.5 Methodology for the research

Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints

Chapter 3. Competition Analysis - Global
3.1 KBV Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.2.4 Geographical Expansion
3.3 Market Share Analysis, 2022
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
3.4.2 Key Strategic Move: (Product Launches and Product Expansions: 2021, Jun – 2023, Dec) Leading Players
3.5 Porter’s Five Forces Analysis

Chapter 4. US Multimodal AI Market
4.1 US Multimodal AI Market by Offering
4.1.1 US Multimodal AI Market by Solution Deployment Type
4.1.2 US Multimodal AI Market by Solution Type
4.2 US Multimodal AI Market by Type
4.3 US Multimodal AI Market by Technology
4.4 US Multimodal AI Market by Data Modality
4.5 US Multimodal AI Market by Vertical

Chapter 5. Company Profiles – Global Leaders
5.1 Twelve Labs Inc.
5.1.1 Company Overview
5.2 Aimesoft
5.2.1 Company Overview
5.2.2 Recent strategies and developments:
5.2.2.1 Product Launches and Product Expansions:
5.2.2.2 Geographical Expansions:
5.3 Jina AI GmbH
5.3.1 Company Overview
5.4 Uniphore Technologies Inc.
5.4.1 Company Overview
5.4.2 Recent strategies and developments:
5.4.2.1 Partnerships, Collaborations, and Agreements:
5.4.2.2 Acquisition and Mergers:
5.5 Google LLC (Alphabet Inc.)
5.5.1 Company Overview
5.5.2 Financial Analysis
5.5.3 Segmental and Regional Analysis
5.5.4 Research & Development Expense
5.5.5 Recent strategies and developments:
5.5.5.1 Partnerships, Collaborations, and Agreements:
5.5.5.2 Product Launches and Product Expansions:
5.5.6 SWOT Analysis
5.6 Microsoft Corporation
5.6.1 Company Overview
5.6.2 Financial Analysis
5.6.3 Segmental and Regional Analysis
5.6.4 Research & Development Expenses
5.6.5 Recent strategies and developments:
5.6.5.1 Partnerships, Collaborations, and Agreements:
5.6.5.2 Product Launches and Product Expansions:
5.6.6 SWOT Analysis
5.7 OpenAI, L.L.C.
5.7.1 Company Overview
5.7.2 Recent strategies and developments:
5.7.2.1 Partnerships, Collaborations, and Agreements:
5.7.3 SWOT Analysis
5.8 Meta Platforms, Inc. (Meta)
5.8.1 Company Overview
5.8.2 Financial Analysis
5.8.3 Segment and Regional Analysis
5.8.4 Research & Development Expense
5.8.5 Recent strategies and developments:
5.8.5.1 Partnerships, Collaborations, and Agreements:
5.8.5.2 Product Launches and Product Expansions:
5.8.6 SWOT Analysis
5.9 Amazon Web Services, Inc. (Amazon.com, Inc.)
5.9.1 Company Overview
5.9.2 Financial Analysis
5.9.3 Segmental Analysis
5.9.4 Recent strategies and developments:
5.9.4.1 Partnerships, Collaborations, and Agreements:
5.9.4.2 Product Launches and Product Expansions:
5.9.5 SWOT Analysis
5.10. IBM Corporation
5.10.1 Company Overview
5.10.2 Financial Analysis
5.10.3 Regional & Segmental Analysis
5.10.4 Research & Development Expenses
5.10.5 Recent strategies and developments:
5.10.5.1 Partnerships, Collaborations, and Agreements:
5.10.5.2 Product Launches and Product Expansions:
5.10.6 SWOT Analysis

TABLE 1 US Multimodal AI Market, 2019 - 2022, USD Million
TABLE 2 US Multimodal AI Market, 2023 - 2030, USD Million
TABLE 3 Partnerships, Collaborations and Agreements– Multimodal AI MARKET
TABLE 4 Product Launches And Product Expansions– Multimodal AI Market
TABLE 5 Acquisition and Mergers– Multimodal AI Market
TABLE 6 Geographical Exxpansion – Multimodal AI Market
TABLE 7 US Multimodal AI Market by Offering, 2019 - 2022, USD Million
TABLE 8 US Multimodal AI Market by Offering, 2023 - 2030, USD Million
TABLE 9 US Multimodal AI Market by Solution Deployment Type, 2019 - 2022, USD Million
TABLE 10 US Multimodal AI Market by Solution Deployment Type, 2023 - 2030, USD Million
TABLE 11 US Multimodal AI Market by Solution Type, 2019 - 2022, USD Million
TABLE 12 US Multimodal AI Market by Solution Type, 2023 - 2030, USD Million
TABLE 13 US Multimodal AI Market by Type, 2019 - 2022, USD Million
TABLE 14 US Multimodal AI Market by Type, 2023 - 2030, USD Million
TABLE 15 US Multimodal AI Market by Technology, 2019 - 2022, USD Million
TABLE 16 US Multimodal AI Market by Technology, 2023 - 2030, USD Million
TABLE 17 US Multimodal AI Market by Data Modality, 2019 - 2022, USD Million
TABLE 18 US Multimodal AI Market by Data Modality, 2023 - 2030, USD Million
TABLE 19 US Multimodal AI Market by Vertical, 2019 - 2022, USD Million
TABLE 20 US Multimodal AI Market by Vertical, 2023 - 2030, USD Million
TABLE 21 Key Information – Twelve Labs Inc.
TABLE 22 Key Information – Aimesoft
TABLE 23 Key Information – Jina AI GmbH
TABLE 24 Key Information – Uniphore Technologies Inc.
TABLE 25 Key Information – Google LLC
TABLE 26 Key Information – Microsoft Corporation
TABLE 27 Key Information – OpenAI, L.L.C.
TABLE 28 Key Information – Meta Platforms, Inc.
TABLE 29 Key Information – Amazon Web Services, Inc.
TABLE 30 Key Information – IBM Corporation

List of Figures
FIG 1 Methodology for the research
FIG 2 US Multimodal AI Market, 2019 - 2030, USD Million
FIG 3 Key Factors Impacting Multimodal AI Market
FIG 4 KBV Cardinal Matrix
FIG 5 Market Share Analysis, 2022
FIG 6 Key Leading Strategies: Percentage Distribution (2019-2023)
FIG 7 Key Strategic Move: (Product Launches and Product Expansions : 2021, Jun – 2023, dec Leading Players
FIG 8 Porter’s Five Forces Analysis – Multimodal ai market
FIG 9 US Multimodal AI Market share by Offering, 2022
FIG 10 US Multimodal AI Market share by Offering, 2030
FIG 11 US Multimodal AI Market by Offering, 2019 - 2030, USD million
FIG 12 US Multimodal AI Market share by Type, 2022
FIG 13 US Multimodal AI Market share by Type, 2030
FIG 14 US Multimodal AI Market by Type, 2019 - 2030, USD million
FIG 15 US Multimodal AI Market share by Technology, 2022
FIG 16 US Multimodal AI Market share by Technology, 2030
FIG 17 US Multimodal AI Market by Technology, 2019- 2030, USD million
FIG 18 US Multimodal AI Market share by Data Modality, 2022
FIG 19 US Multimodal AI Market share by Data Modality, 2030
FIG 20 US Multimodal AI Market by Data Modality, 2019 - 2030, USD million
FIG 21 US Multimodal AI Market share by Vertical, 2022
FIG 22 US Multimodal AI Market share by Vertical, 2030
FIG 23 US Multimodal AI Market by Vertical, 2019 - 2030, USD million
FIG 24 Recent strategies and developments: Aimesoft
FIG 25 Recent strategies and developments: Uniphore Technologies Inc.
FIG 26 Recent strategies and developments: Google LLC
FIG 27 SWOT Analysis: Google LLC
FIG 28 Recent strategies and developments: Microsoft Corporation
FIG 29 SWOT Analysis: Microsoft Corporation
FIG 30 SWOT Analysis: OpenAI, L.L.C.
FIG 31 Recent strategies and developments: Meta Platform Inc.
FIG 32 SWOT Analysis: Meta Platforms, Inc.
FIG 33 Recent strategies and developments: Amazon Web Services, Inc.
FIG 34 SWOT analysis: Amazon Web Services, Inc.
FIG 35 Recent strategies and developments: ibm Corporation
FIG 36 Swot Analysis: IBM Corporation