AI as a Service Market by Offering (SaaS, PaaS, IaaS), Technology (Machine Learning, Natural Language Processing, Context Awareness, Computer Vision), Cloud Type (Public, Private, Hybrid), Organization Size, Vertical and Region - Global Forecast to 2028
Updated on : May 04, 2023
AI as a Service Market Forecast & Report Summary, Global Size
[301 Pages Report] The global AI as a Service Market size was worth approximately $9.3 billion in 2023 and poised to generate revenue around $55.0 billion by the end of 2028, projecting a CAGR of 42.6% from 2023 to 2028.
AI as a service refers to the delivery of artificial intelligence (AI) capabilities and tools via the cloud as a subscription-based service. Instead of building and maintaining their own AI infrastructure, organizations can leverage cloud-based AI services. AI as a service offerings typically include pre-built machine learning models, natural language processing tools, computer vision services, and other AI capabilities that can be easily integrated into applications or used to build new AI-powered applications.
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AI as a Service Market Growth Dynamics
Driver: Growth in importance of data-driven decision-making in business
The significance of data-driven decision-making in businesses is increasing rapidly, and AIaaS plays a crucial role in this area. By leveraging machine learning algorithms, AIaaS solutions can identify patterns and trends in data that may not be identified manually, enabling end users to make faster and more informed decisions. The major industries such as finance, healthcare, and manufacturing are increasingly using these solutions, where timely decisions based on accurate data can have a significant impact on business outcomes. In addition, AIaaS solutions automate routine tasks and processes, freeing up end users to focus on higher-value activities such as strategic planning and analysis. This can lead to increased productivity, improved operational efficiency, and reduced costs. In this way, AIaaS provides end users with powerful new capabilities to help them make more informed decisions and stay ahead of the competition in a data-driven business environment.
Restraint: Lack of skilled employees
The primary issue that most organizations face while incorporating ML into their business processes is the lack of analytic talent. The dearth of deep analytic talent continues to be a concern for organizations. As a result, there is a rising demand for professionals who can monitor analytical content. Recruiting and retaining technical resources has become a significant focus for many enterprises. There are not enough skilled people to develop and execute analytics projects that involve complex techniques, such as ML. Data scientists are considered the most skilled analytic professionals with in-depth knowledge of computer science, mathematics, and domain expertise. However, experienced data scientists command high price tags and demand engaging projects, which in most cases is not feasible for SMEs and even large organizations. To stay competitive in the market, there is a rising need to adopt ML-enabled solutions. Thus, the scarcity of skilled employees is expected to be a significant restraint for the growth of the global AI as a Service market.
Opportunity: Increase in need for intelligent business applications
Owing to digitalization, IoT, and advancement in traditional technologies, there has been an increase in the amount of data generated in the past few years. Moreover, connected devices and smartphones linked to the internet are considered significant factors in generating a considerable amount of data. The data generated through these devices is growing at a faster pace. Similarly, applications that can analyze large volumes of data are also increasing significantly. These applications are expected to grow in the coming years. As data is becoming crucial in formulating various business strategies, end-users are concentrating more on the data analysis process. AI-powered solutions play a vital role in this process. For instance, Chatbots analyze large volumes of customer data and respond to customer queries. Thus, by deploying chatbots, various organizations can achieve benefits, such as business process automation and Return on Investment (ROI), to stay competitive in the market. Service providers such as Vital AI offer a framework for chatbots as well as intelligent assistants. Among the other service providers, Chatfuel provides a framework to build intelligent bots.
Challenge: Sensitivity involved with security of data
Owing to the introduction and expansion of new technologies, such as IoT, big data, and ML, there is intense market competition. These technologies have significantly contributed to the rise of end-points collecting data, thereby resulting in an increase in dynamic data that keeps changing/updating every second. For every organization that predicts customers’ behavior by analyzing the collected sets of data, maintaining data privacy is a huge security mandate. s related to data ownership and privacy of collected data retain potential risks to an individual’s identity. Government authorities impose various data security laws and regulations across various regions. Therefore, enterprises must stay up-to-date with the changing rules and data-related regulations. The enterprises are expected to implement the latest security measures to ensure the privacy of their collected data. Furthermore, in the case of outsourcing data analysis to a third-party Business Intelligence (BI) vendor, the organizations have to ensure that BI vendors secure firms’ data appropriately.
By technology, computer vision to register at the highest CAGR among technologies during the forecast period
In AI as a Service, computer vision is becoming increasingly accessible to businesses of all sizes. Computer vision is being used in a wide range of applications, from self-driving cars to medical imaging to surveillance systems. The computer vision technology is projected to grow at the highest CAGR during the forecast period. By leveraging cloud-based platforms, companies can easily upload and analyze large amounts of visual data and train machine learning models to perform complex tasks, such as object detection, image recognition, and video analysis. By using computer vision in AIaaS, businesses can gain valuable insights from visual data, improve operations, and enhance the customer experience. It enables companies to analyze large volumes of visual data in real-time, allowing them to make faster and more informed decisions.
By cloud type, public cloud to account for the largest market size during the forecast period
In AIaaS, public cloud providers offer a range of services, including machine learning, natural language processing, and computer vision, which can be used by organizations to build, train, and deploy AI models. Public cloud AIaaS solutions offer several benefits, including cost-effectiveness, scalability, and availability. Public cloud providers typically operate on a pay-as-you-go model, enabling organizations to pay only for the services they use. Public cloud platforms offer unlimited scalability, enabling organizations to quickly ramp up or down their AI workloads based on demand. Public cloud providers also have a global presence providing high availability to organizations worldwide.
North America to account for the largest market size during the forecast period
North America is expected to have the largest market share in AI as a Service. North America has been a major contributor to the development and growth of the AI as a Service market. The region is home to several leading AI companies, including Google, Microsoft, IBM, and Amazon, which have been investing heavily in AI research and development. These companies have been providing AI services and tools to businesses and organizations of all sizes, enabling them to leverage the power of AI without having to invest in expensive hardware or software. North America has also been at the forefront of AI innovation, with many universities and research institutions in the region conducting groundbreaking research in the field. This has led to the development of new AI technologies and applications, further driving the growth of the AI as a Service market.
Key Market Players
The AI as a Service vendors have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major vendors in the global market for AI as a Service IBM (US), Microsoft (US), Google (US), AWS (US), FICO (US), SAS Institute (US), Baidu (China), SAP (Germany), Salesforce (US), Oracle (US), Iris.AI (US), Craft.AI (France), BigML (US), H2O.ai (US), Vital.ai (US), Fuzzy.ai (Canada), RainBird Technologies (UK), SiftScience (US) DataBricks (US), CenturySoft (India), DataRobot (US), Alibaba (China), Tencent (China), Dataiku (US), Yottamine Analytics (US), Tecnotree (Finland), Cloudera (US), and Meya.ai (KSA).
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Report Metrics |
Details |
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Market size available for years |
2017–2028 |
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Base year considered |
2023 |
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Forecast period |
2023–2028 |
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Forecast units |
USD Million/Billion |
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Segments covered |
Offering, Cloud Type, Technology, Organization Size, Vertical, and Region |
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Geographies covered |
North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America |
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Companies covered |
IBM (US), Microsoft (US), Google (US), AWS (US), FICO (US), SAS Institute (US), Baidu (China), SAP (Germany), Salesforce (US), Oracle (US), Iris.AI (US), Craft.AI (France), BigML (US), H2O.ai (US), Vital.ai (US), Fuzzy.ai (Canada), RainBird Technologies (UK), SiftScience (US) DataBricks (US), CenturySoft (India), DataRobot (US), Alibaba (China), Tencent (China), Dataiku (US), Yottamine Analytics (US), Tecnotree (Finland), Cloudera (US), and Meya.ai (KSA) |
This research report categorizes the AI as a Service market based on Offering, Cloud Type, Technology, Organization Size, Vertical, and Region.
By Technology:
- Machine Learning
- Natural Language Processing
- Context Awareness
- Computer Visison
By Cloud Type:
- Public Cloud
- Hybrid Cloud
- Private Cloud
By Organization Size:
- Small & Medium-Sized Enterprises
- Large Enterprises
By Offering:
- Infrastructure as a Service
- Platform as a Service
- Software as a Service
By Vertical:
- Banking, financial services, and insurance
- Retail & eCommerce
- Healthcare & life sciences
- IT & ITeS
- Telecommunications
- Government & defense
- Manufacturing
- Energy & utilities
- Other Verticals
By Region:
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North America
- US
- Canada
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Europe
- UK
- Germany
- France
- Rest of Europe
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Asia Pacific
- China
- Japan
- India
- South Korea
- Australia & New Zealand
- ASEAN
- Rest of Asia Pacific
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Middle East & Africa
- UAE
- Kingdom of Saudi Arabia
- Israel
- Turkey
- South Africa
- Rest of the Middle East & Africa
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Latin America
- Brazil
- Mexico
- Rest of Latin America
Recent Developments:
- In March 2023, Google Cloud introduced Generative AI support in Vertex AI that allows data science teams access to foundation models from Google and others, enables them build and customize atop these models on the same platform they use for homegrown ML models and MLops.
- In March 2023, Salesforce launched Einstein GPT, a generative AI CRM technology, which delivered AI-created content across every sale, service, marketing, commerce, and IT interaction at a hyper-scale.
- In January 2023, Microsoft extended its partnership with OpenAI to accelerate AI breakthroughs to ensure these benefits were broadly shared with the world.
- In December 2022, IBM announced the acquisition of Databand.ai, a leading provider of data observability software that helped organizations fix issues with their data, including errors, pipeline failures, and poor quality, before it impacted their bottom line.
- In May 2022, FICO introduced new and enhanced capabilities to the FICO Platform. The new capabilities would empower businesses to organize their data, apply the latest in machine learning and analytics to generate new insights, take proactive action, and drive meaningful business outcomes.
Frequently Asked Questions (FAQ):
What is AI as a Service?
AI as a Service (also known as AI as a Service, AI-as-a-Service, and AI Cloud) refers to a cloud-based service that provides access to various AI technologies and tools, allowing businesses to leverage the benefits of AI without having to invest in developing and maintaining their own AI infrastructure. AI as a Service includes natural language processing, computer vision, predictive analytics, and speech recognition.
Which countries are considered in the European region?
The report includes an analysis of the UK, Germany, France, Spain, and Italy in the European region.
Which are key verticals adopting AI as a Service software and services?
Key verticals adopting AI as a Service and services include BFSI, retail & consumer goods, automotive, government & defense, healthcare & life sciences, telecommunication & IT, energy & utilities, and others (education, media & entertainment, travel & hospitality, and manufacturing).
Which are the key drivers supporting the market growth for AI as a Service?
The key drivers supporting the market growth for AI as a Service include the growth in importance of data-driven decision-making in business, increase in need to provide enhanced customer experience and gain competitive advantage, rise in demand for AI-powered services in API and SDK forms.
Who are the key vendors in the market for AI as a Service?
The key vendors in the global AI as a Service market include IBM (US), Microsoft (US), Google (US), AWS (US), FICO (US), SAS Institute (US), Baidu (China), Intel (US), SAP (Germany), Salesforce (US), Oracle (US), Iris.AI (US), Craft.AI (France), BigML (US), H2O.ai (US), Vital.ai (US), Fuzzy.ai (Canada), RainBird Technologies (UK), SiftScience (US) DataBricks (US), CenturySoft (India), DataRobot (US), Alibaba (China), Tencent (China), Dataiku (US), Yottamine Analytics (US), Tecnotree (Finland), Cloudera (US), and Meya.ai (KSA).
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The research methodology for the global AIaaS market report involved the use of extensive secondary sources and directories, as well as various reputed open-source databases, to identify and collect information useful for this technical and market-oriented study. In-depth interviews were conducted with various primary respondents, including key opinion leaders, subject matter experts, high-level executives of multiple companies offering AIaaS offerings, and industry consultants to obtain and verify critical qualitative and quantitative information, as well as assess the market prospects and industry trends.
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; and white papers, certified publications, and articles from recognized associations and government publishing sources.
The secondary research was mainly used to obtain the key information about the industry’s value chain, 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 market and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both the supply and demand sides of the AIasS 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, and related key executives from various vendors providing AIasS offerings; associated service providers; and system integrators operating in the targeted regions. All possible 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 (including calculations for market statistics, market breakup, 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 undertaken 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 the top-down and bottom-up approaches were extensively used, along with several data triangulation methods, to perform the market estimation and market 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 record the critical information/insights throughout the report.
The following is the breakup of primary profiles:
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Market Size Estimation
For making market estimates and forecasting the AIaaS market and the other dependent submarkets, top-down and bottom-up approaches were used. The bottom-up procedure was used to arrive at the overall market size of the global AIasS market, using the revenue from the key companies and their offerings in the market. With data triangulation and validation through primary interviews, the exact value of the overall parent market size was determined and confirmed using this study. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segments.
In the top-down approach, an exhaustive list of all the vendors offering AIaaS was prepared. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor’s offerings were evaluated based on the breadth of solution and service offerings, cloud type, organization size, and verticals. The aggregate of all the revenues of the companies was extrapolated to reach the overall market size. Each subsegment was studied and analyzed for its global market size and regional penetration. The markets were triangulated through both primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets repository for validation.
In the bottom-up approach, the adoption rate of AIaaS solutions and services among different end-users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of AI as a Service solutions and services among industries, along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in different regions for the market size calculation.
All the possible parameters that affect the market covered in the research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. The data is consolidated and added with detailed inputs and analysis from MarketsandMarkets.
- The pricing trend is assumed to vary over time.
- All the forecasts are made with the standard assumption that the accepted currency is USD.
- For the conversion of various currencies to USD, average historical exchange rates are used according to the year specified. For all the historical and current exchange rates required for calculations and currency conversions, the US Internal Revenue Service’s website is used.
- All the forecasts are made under the standard assumption that the globally accepted currency, USD, remains constant during the next five years.
- Vendor-side analysis: The market size estimates of associated solutions and services are factored in from the vendor side by assuming an average of licensing and subscription-based models of leading and innovative vendors.
- Demand/end-user analysis: End users operating in verticals across regions are analyzed in terms of market spending on AI as a Service solutions based on some of the key use cases. These factors for the AI in the project management tool industry per region are separately analyzed, and the average spending was extrapolated with an approximation based on assumed weightage. This factor is derived by averaging various market influencers, including recent developments, regulations, mergers and acquisitions, enterprise/SME adoption, startup ecosystem, IT spending, technology propensity and maturity, use cases, and the estimated number of organizations per region.
Data Triangulation
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
AI as a Service (also known as AI as a Service, AI-as-a-Service, and AI Cloud) refers to a cloud-based service that provides access to various AI technologies and tools, allowing businesses to leverage the benefits of AI without having to invest in developing and maintaining their own AI infrastructure. AI as a Service includes natural language processing, computer vision, predictive analytics, and speech recognition.
Key Stakeholders
- Research organizations
- Third-party service providers
- Technology providers
- Cloud services providers
- AI consulting companies
- Independent software vendors (ISVs)
- Service providers and distributors
- Application development vendors
- System integrators
- Consultants/consultancy/advisory firms
- Training and education service providers
- Support and maintenance service providers
- Managed service providers
Report Objectives
- To define, describe, and forecast the AI as a Service market based on offering, service type, technology, cloud type, organization size, vertical, and region
- To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the market growth
- To analyze subsegments with respect to individual growth trends, prospects, and contributions to the total market
- To analyze opportunities in the market for stakeholders and provide the competitive landscape of the market
- To forecast the revenue of the market segments with respect to all the five major regions, namely, North America, Europe, Asia Pacific (APAC), the Middle East & Africa (MEA), and Latin America
- To profile the key players and comprehensively analyze the recent developments and their positioning related to the AI as a Service market
- To analyze competitive developments, such as mergers & acquisitions, product developments, and research & development (R&D) activities, in the market
- To analyze the impact of recession across all the regions across the AI as a Service market
Available Customizations
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
- Product matrix provides a detailed comparison of the product portfolio of each company
Geographic Analysis
- Further breakup of the North American market for AI as a Service
- Further breakup of the European market for AI as a Service
- Further breakup of the Asia Pacific market for AI as a Service
- Further breakup of the Latin American market for AI as a Service
- Further breakup of the Middle East & Africa market for AI as a Service
Company Information
- Detailed analysis and profiling of additional market players (up to five)
Growth opportunities and latent adjacency in AI as a Service Market
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