Text-to-Video AI Market by Component (Software, Services), Deployment Mode, Organization Size, End User (Corporate Professionals, Content Creators), Vertical (Education, Media & Entertainment, Retail & eCommerce) and Region - Global Forecast to 2027
[251 Pages Report] The global text-to-video AI market size is projected to grow from USD 0.1 billion in 2022 to USD 0.9 billion by 2027 at a Compound Annual Growth Rate (CAGR) of 37.1% during the forecast period. Increasing developments in technologies such as AI, and deep learning, NLP is driving market growth.
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Market Dynamics
Driver: Realistic AI avatars to add social components to videos and make them dynamic
Video has become an important tool for increasing customer engagement and retention. Text-to-video AI solution providers such as Synthesia and Movio provide options to choose among multiple AI avatars. These avatars can speak the provided text in more than 120 languages and accents. These avatars are broad and diverse and cover different ages, ethnicities, races, and styles. The latest features, such as micro gestures, allow users to add various gestures to the avatars and make them wink, nod, frown, or raise an eyebrow. These videos are used for various purposes, such as learning and training videos, product walkthrough videos, corporate communications, and marketing. An AI-powered talking avatar draws customer attention and engages them.
Restraint: Ethical implications
ML approaches such as deepfakes are used to generate synthetic media such as images, videos, and audio. It becomes difficult or almost impossible to differentiate such AI-generated content from real media. Hence, posing serious ethical implications. Such media may be used to spread misinformation, manipulate public opinion, or even harass or defame individuals. A deepfake video pretending to show a political candidate saying or doing something that did not happen could manipulate public opinion and interfere with the democratic process.
Opportunity: Availability of applications in multiple languages to save on voiceover budgets
AI video generators help users create videos by applying minimum effort and cost, making it the best choice for businesses with tight budgets. The generation of text-to-video is a synthetic video generation form that utilizes NLP to convert written input into digital animation. Text-to-video AI software helps to convert plain text into videos in a fraction of a minute. This software helps create videos with high-quality content in multiple languages and saves up to 80% of time and budget without compromising on quality. The software provides AI voices that are digital clones of the voices of real people. So, it helps users convert text into professional voiceovers with consistent audio quality and language.
Challenge: High computing costs and lack of good datasets
Text-to-video AI software requires a vast amount of computing power and has high computation costs making training from scratch nearly unaffordable. They need an even bigger computational lift compared to large AI models. These models use a large amount of data to train, as they need to put the data together for just one short video. Only large enterprises can afford to build these types of systems for the predictable future. It becomes trickier to train those models due to the lack of large-scale data sets of high-quality videos paired with text.
Food & Beverages segment is projected to grow at the fastest rate during the forecast period.
Food & beverages form one of the fastest-growing industries in video content, so this industry can benefit from text-to-video AI. Using text-to-video AI, many companies can use advertise their products as videos are attractive. The videos bring out actual colors, consistency and visuals of the food and dishes. The text-to-video AI helps showcase the list of products available on the menu, which helps customers decide on the order, thus reducing order time per customer. Videos help food and beverage brands connect directly with their customers, thus making a positive image in the market to increase sales and compete.
Software segment is set to account for the largest market share during the forecast period
The text-to-video AI software tools are AI-powered solutions designed to convert raw input texts or even audio into animated character-centric video content. These solutions provide many features with options to select from various AI avatars, multiple languages, different voices, intended music, built-in video templates, transition effects and up-to-date editing options to generate high-quality videos.
North America to account for the largest market share during the forecast period
North America includes developed countries such as US and Canada with well-established infrastructures. It is expected to hold the largest global text-to-video AI market share. There are Copyright Acts in the US and Canada to protect the original work of the creators. No amendments are proposed for the upcoming creative work using technologies such as generative AI, ML and big data. These technology tools carry risks, and there can be action from the government in the form of regulations for the protection of the content generated with these technologies. North America consists of major players such as Meta and Google, which have released products related to AI video generation.
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Key Market Players
The text-to-video AI market vendors have implemented various organic and inorganic growth strategies, such as new product launches, product upgrades, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major vendors in the global text-to-video AI market are GliaCloud (Taiwan), Designs.ai (Singapore), Pictory (US), Raw Shorts (US), Wochit (US), Vimeo (US), Vedia (US), Lumen5 (Canada), Synthesia (UK), Steve AI (US), InVideo (US), Meta (US), Hour One (Israel), Google (US), Elai.io (US), Peech (Israel), Wave.video (US), DeepBrain AI (South Korea), D-ID (Israel), Yepic AI (UK), Movio (US), KLleon (South Korea), Synthesys (UK), VEED (UK), and Ezoic (US). The study includes an in-depth competitive analysis of these key players in the text-to-video AI market with their company profiles, recent developments, and key market strategies.
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Report Metrics |
Details |
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Market size available for years |
2018–2027 |
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Base year considered |
2021 |
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Forecast period |
2022–2027 |
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Forecast units |
Value (USD Million/Billion) |
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Segments covered |
By component, deployment mode, organization size, end user, vertical and region |
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Regions covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
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Companies covered |
GliaCloud (Taiwan), Designs.ai (Singapore), Pictory (US), Raw Shorts (US), Wochit (US), Vimeo (US), Vedia (US), Lumen5 (Canada), Synthesia (UK), Steve AI (US), InVideo (US), Meta (US), Hour One (Israel), Google (US), Elai.io (US), Peech (Israel), Wave.video (US), DeepBrain AI (South Korea), D-ID (Israel), Yepic AI (UK), Movio (US), KLleon (South Korea), Synthesys (UK), VEED (UK), and Ezoic (US) |
This research report categorizes the text to video AI market to forecast revenues and analyze trends in each of the following subsegments:
By Component
- Software
-
Services
- Consulting Services
- Integration Services
- Support and Maintenance Services
By Deployment Mode
- On-premises
- Cloud
By Organization Size
- Large Enterprises
- Small- & Medium-Sized Enterprises
By End User
- Marketers
- Social Media Managers
- Educators & Course Creators
- Content Creators
- Corporate Professionals
- Other End Users
By Vertical
- Education
- Food & Beverages
- Media & Entertainment
- Fashion & Beauty
- Retail & Ecommerce
- Health & Wellness
- Travel & Hospitality
- Real Estate
- Other Verticals
By Region
-
North America
- US
- Canada
-
Europe
- UK
- Germany
- France
- Italy
- Spain
- Nordic Region
- Rest of Europe
-
Asia Pacific
- China
- India
- Japan
- Australia and New Zealand
- Southeast Asia
- Rest of Asia Pacific
- Middle East and Africa
-
Middle East
- UAE
- KSA
- Rest of Middle East
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Africa
- South Africa
- Egypt
- Nigeria
- Rest of Africa
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Latin America
- Brazil
- Mexico
- Rest of Latin America
Recent Developments:
- In March 2022, Vimeo acquired the interactive video platform Wirewax. With this acquisition, Wirewax would offer more interactive video functionality to Vimeo, particularly with a drag-and-drop interface and the addition of “shoppable” videos, which Wirewax frequently promoted.
- In March 2022, InVideo acquired the website KIZOA. InVideo bought the website KIZOA, a 13-year-old video editing software platform with 18 million registered accounts to the web service worldwide. InVideo’s purchase of Kizoa increased its market share in the online video editor sector.
- In January 2020, Wochit partnered with Kaltura to offer Wochit video creation capabilities to Kaltura customers.
Frequently Asked Questions (FAQ):
What is text-to-video AI?
Text-to-video AI is an AI technology that takes text as input and produces video as output. The technique is inspired by text-to-image models.
According to Raw Shorts, text-to-video is an automated platform that uses AI to scan the main idea of the provided text. Then, it searches for related media assets to create a video timeline and generate voice narration.
Which countries are considered in Europe?
The report includes an analysis of the UK, France, Germany, Italy, Spain, and the Nordic region in Europe.
Which are the key drivers supporting the growth of the text-to-video AI market?
The key driver supporting the growth of the text-to-video AI market includes the inclusion of data-driven videos on websites to boost conversion rates, realistic AI avatars to add social components to videos and make them dynamic, and rise in demand for engaging videos in businesses.
Who are the key vendors in the text-to-video AI market?
The key vendors operating in the text-to-video AI market include GliaCloud (Taiwan), Designs.ai (Singapore), Pictory (US), Raw Shorts (US), Wochit (US), Vimeo (US), Vedia (US), Lumen5 (Canada), Synthesia (UK), Steve AI (US), InVideo (US), Meta (US), Hour One (Israel), Google (US), Elai.io (US), Peech (Israel), Wave.video (US), DeepBrain AI (South Korea), D-ID (Israel), Yepic AI (UK), Movio (US), KLleon (South Korea), Synthesys (UK), VEED (UK), and Ezoic (US).
What are some of the technological advancements in the market?
Generative AI research is pushing opportunities for people with the tools to quickly and easily create new content. With just a few words or lines of text, it is possible to make a video with vivid colors, characters, and landscapes. In text-to-video conversion technologies, with the use of AI, one can convert text into speech. The text is selected to use in the video. This results in time-saving, can boost conversions and make your content more appealing to customers to increase customer engagement. It has greater flexibility and optimization and a promising future. Also, now Deep Learning is integrated into video editing software. Combining AI with Deep Learning can bring exceptional results. The use cases of AI-generated videos are extending, varying from e-learning and e-commerce to dubbing and official communications. It simplifies mundane tasks and adjusts the workflow; AI has an intact potential to offer an exceptional experience for content creators.
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This research study involved the extensive use of secondary sources, directories, and databases, such as D&B Hoovers, Bloomberg Businessweek, and Factiva, to identify and collect information useful for this technical, market-oriented, and commercial study of the text-to-video AI market. Primary sources were industry experts from core and related industries, preferred system developers, service providers, resellers, partners, and organizations related to the various segments of the industry’s value chain. In-depth interviews were conducted with various primary respondents, including key industry participants and subject-matter experts, to obtain and verify critical qualitative and quantitative information, as well as to assess the market’s prospects. These included key industry participants, subject-matter experts, C-level executives of key companies, and industry consultants.
Secondary Research
In the secondary research process, various secondary sources were referred to for identifying and collecting information for the study. The secondary sources included annual reports; press releases and investor presentations of companies; white papers, certified publications, and articles from recognized associations and government publishing sources. Several journals and various associations were also referred to, such as the Analytics India Magazine and Diggit Magazine. Secondary research was used to obtain key information about industry insights, the market’s monetary chain, the overall pool of key players, market classification and segmentation according to industry trends to the bottom-most level, regional markets, and key developments from both the market- and technology-oriented perspectives.
Secondary research was used to obtain key information about the industry’s supply chain, the total pool of key players, market classification, and segmentation according to the industry trends to the bottom-most level, regional markets, and key developments from both market and technology-oriented perspectives, all of which were further validated by primary sources.
Primary Research
In the primary research process, various primary sources from both supply and demand sides of the text-to-video AI market ecosystem were interviewed to obtain qualitative and quantitative information for this study. The primary sources from the supply side included industry experts, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), marketing directors, technology and innovation directors, related key executives from various vendors providing text-to-video AI solutions, associated service providers, and system integrators operating in the targeted regions. All parameters that affect the market covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
After the complete market engineering process (including calculations for market statistics, market breakdown, market size estimations, market forecast, and data triangulation), extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. Primary research was also conducted to identify and validate the segmentation types; industry trends; key players; the competitive landscape of the market; and key market dynamics, such as drivers, restraints, opportunities, challenges, industry trends, and key strategies.
In the complete market engineering process, both top-down and bottom-up approaches and several data triangulation methods were used to perform the market estimation and forecast for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was performed on the complete market engineering process to list the key information/insights throughout the report.
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Multiple approaches were adopted to estimate and forecast the market size of the text-to-video AI market. The first approach involves the estimation of the market size by summing up the revenues of the companies generated through the sale of software and services.
Text to video AI Market: Bottom-Up Approach
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Data Triangulation
The bottom-up approach was employed to arrive at the overall size of the text-to-video AI market from the revenue of the key players and their share in this market. The revenue of the key players was analyzed to determine the overall size of the text-to-video AI market.
Report Objectives
- To determine, segment, and forecast the global text to video AI market by component, deployment mode, organization size, end user, vertical and region in terms of value.
- To forecast the size of the market segments with respect to five main regions: North America, Europe, Asia Pacific, Latin America, and Middle East & Africa.
- To provide detailed information about the major factors (drivers, opportunities, threats, and challenges) influencing the growth of the text to video AI market.
- To study the complete value chain and related industry segments and perform a value chain analysis of the text to video AI market landscape.
- To strategically analyze macro and micromarkets with respect to individual growth trends, prospects, and contributions to the total text to video AI market.
- To analyze industry trends, pricing data, and patents and innovations related to the text to video AI market.
- To analyze opportunities in the market for stakeholders by identifying the high-growth segments of the text to video AI market.
- To profile key players in the market and comprehensively analyze their market share/ranking and core competencies.
- To track and analyze competitive developments, such as mergers and acquisitions, new product launches and developments, partnerships, agreements, collaborations, business expansions, and Research and Development (R&D) activities.
Available Customizations
Along with the market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
- Further breakdown of South Korean text to video AI market
Product Analysis
- Product Matrix, which gives a detailed comparison of the product portfolio of each company.
Company Information
- Detailed analysis and profiling of additional market players (up to five)
Growth opportunities and latent adjacency in Text-to-Video AI Market