Ai Created Saas Market
AI Created Saas Market Forecasts to 2030 - Global Analysis by Type of AI Technology (Machine Learning (ML) as a Service, Natural Language Processing (NLP) as a Service, Computer Vision as a Service and Other Types of AI Technologies), Functionality, Delivery Method, Deployment Model, Size of Business, Application and By Geography
|
Years Covered |
2022-2030 |
|
Estimated Year Value (2024) |
US $72.4 BN |
|
Projected Year Value (2030) |
US $598.5 BN |
|
CAGR (2024 - 2030) |
42.2% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
Asia Pacific |
|
Highest Growing Market |
North America |
According to Stratistics MRC, the Global AI Created Saas Market is accounted for $72.4 billion in 2024 and is expected to reach $598.5 billion by 2030 growing at a CAGR of 42.2% during the forecast period. AI-Created SaaS (Software as a Service) refers to cloud-based software solutions powered by artificial intelligence that are delivered via subscription models. These platforms leverage AI technologies, such as machine learning and natural language processing, to automate processes, enhance decision-making, and provide personalized experiences. AI-Created SaaS solutions enable businesses to analyze large datasets, improve operational efficiency, and optimize customer interactions. By offering scalable and adaptable services, these platforms are designed to meet the specific needs of various industries, reducing manual workloads, improving accuracy, and fostering innovation through intelligent automation and predictive capabilities.
Market Dynamics:
Driver:
Increased Demand for Automation
The AI-Created SaaS market is driven by the growing need for automation, which forces companies to implement scalable, cost-effective, and efficient solutions. AI-powered SaaS solutions have the capacity to automate jobs across a variety of roles, from data processing to customer support, as businesses look to improve productivity, decrease manual involvement, and streamline operations. Because AI solutions offer quicker, more accurate, and more individualized services, this trend toward automation encourages wider market adoption and eventually increases operational efficiency and competitiveness.
Restraint:
High Initial Investment
High initial investment in AI-created SaaS solutions can hinder market growth by limiting accessibility for small and medium-sized businesses. The substantial upfront costs required for research, development, and infrastructure makes it challenging for startups and organizations with limited budgets to adopt AI-powered platforms. This financial barrier restricts the widespread adoption of AI SaaS, slowing down its integration across various industries and delaying its potential benefits.
Opportunity:
Enhanced Data Analysis and Insights
Improved data analysis and insights propel the AI-Created SaaS industry by allowing firms to make data-driven decisions. Large volumes of data can be analyzed by AI-powered platforms, which find patterns and trends that people can would find challenging to identify. Better forecasts, streamlined procedures, and focused tactics result from this, raising overall performance and competitiveness. Because of this, companies are using AI SaaS solutions more and more to leverage data, obtain a competitive advantage, and boost operational effectiveness, thus it drives the growth of the market.
Threat:
Complexity and Integration Challenges
Complexity and integration challenges in the AI-Created SaaS market hinder adoption by making it difficult for businesses to seamlessly incorporate AI solutions into their existing systems. The need for specialized skills and resources to manage these integrations can delay implementation, increase costs, and cause disruptions. Companies with legacy infrastructure may face additional obstacles, limiting the scalability and effectiveness of AI-driven SaaS platforms in their operations.
Covid-19 Impact
COVID-19 accelerated the adoption of AI-Created SaaS solutions as businesses sought efficient, remote, and scalable technologies to adapt to disruptions. The shift to digital operations, remote work, and e-commerce spurred demand for AI-powered tools for automation, data analysis, and customer engagement. However, the pandemic also posed challenges, including budget constraints and delays in technology adoption for some businesses, slowing down the market’s full potential growth.
The healthcare segment is expected to account for the largest market share during the forecast period
The healthcare segment is expected to account for the largest market share during the forecast period, as AI-powered SaaS solutions automate administrative duties, improve patient care management, and expedite medical processes, they save operating expenses. With real-time analysis of patient data, they also improve data-driven decision-making, increasing effectiveness and results. The use of AI SaaS in healthcare is being further accelerated by the rising demand for telemedicine, health analytics, and electronic health record (EHR) systems.
The content creation segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the content creation segment is predicted to witness the highest growth rate, because it enhance the generation of high-quality content. AI-powered tools assist in creating personalized marketing materials, social media posts, product descriptions, and even multimedia content, improving efficiency and reducing costs. The demand for scalable and innovative content solutions is increasing, as AI SaaS platforms streamline content production, optimize engagement, and enable real-time customization, ultimately boosting the growth of AI-driven SaaS offerings.
Region with largest share:
During the forecast period, Asia Pacific region is expected to hold the largest market share, owing to rapid digital transformation and increasing demand for automation across industries. The rise of cloud adoption, coupled with advancements in AI technologies, enables businesses to leverage cost-effective, scalable solutions. Governments promoting digitalization, along with a growing number of startups, are further accelerating market growth. Additionally, industries like healthcare, finance, and retail are adopting AI-powered SaaS solutions for improved efficiency, data analytics, and personalized services, driving the region's AI SaaS market expansion.
Region with highest CAGR:
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, due to industry-wide demands for efficiency, automation, and data-driven insights. AI-powered solutions are being embraced by businesses more and more in an effort to improve customer experiences, increase operational efficiency, and obtain a competitive advantage. Market expansion is fueled by the region's robust technology infrastructure, availability of highly qualified personnel, and significant investments in AI research. Furthermore, North America's adoption of AI-driven SaaS platforms is accelerated by the growing demand for scalable and affordable software solutions.
Key players in the market
Some of the key players profiled in the AI Created Saas Market include Adobe, Alteryx, Amazon Web Services (AWS) , C3.ai, Cortexica, DataRobot, Freshworks, Google Cloud, Hootsuite, HubSpot, IBM, Kaltura, LogMeIn, Microsoft, MonkeyLearn, Pega Systems, Salesforce, Sentient Technologies, UiPath and Zendesk.
Key Developments:
In January 2024, Amazon Web Services (AWS) is teaming up with renowned global investment and transformation company General Catalyst in a first-of-its-kind collaboration that is driving toward a stronger health care ecosystem, with the help of generative AI.
In January 2024, Amazon and Intuit expanded their partnership to bring their existing Amazon data into Intuit products and experiences—ultimately making it easier for sellers to understand and optimize profitability, manage cash flow, access capital, and simplify taxes with confidence.
In January 2024, Amazon and Anthropic announced a strategic collaboration, which included Anthropic naming Amazon Web Services (AWS) its primary cloud provider and Amazon making a $4 billion investment in Anthropic. Both companies will continue to work closely to keep advancing Trainium's hardware and software capabilities.
Types of AI Technology Covered:
• Machine Learning (ML) as a Service
• Natural Language Processing (NLP) as a Service
• Computer Vision as a Service
• Speech Recognition and AI-driven Voice Assistants
• Robotic Process Automation (RPA) as a Service
• Other Types of AI Technologies
Functionalities Covered:
• Analytics and Insights
• Customer Engagement
• Predictive Analytics
• Content Creation
• Security and Fraud Prevention
Delivery Methods Covered:
• Platform-as-a-Service (PaaS)
• Software-as-a-Service (SaaS)
• Infrastructure-as-a-Service (IaaS)
Deployment Models Covered:
• Public Cloud
• Private Cloud
• Hybrid Cloud
Sizes of Business Covered:
• Small and Medium-sized Enterprises
• Large Enterprises
Applications Covered:
• Healthcare
• Retail
• Finance
• Manufacturing
• Education
• Marketing and Advertising
• Customer Service
• Human Resources (HR)
• Transportation and Logistics
• Other Applications
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o 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 2022, 2023, 2024, 2026, and 2030
- 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
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o 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 Application Analysis
3.7 Emerging Markets
3.8 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 AI Created Saas Market, By Type of AI Technology
5.1 Introduction
5.2 Machine Learning (ML) as a Service
5.3 Natural Language Processing (NLP) as a Service
5.4 Computer Vision as a Service
5.5 Speech Recognition and AI-driven Voice Assistants
5.6 Robotic Process Automation (RPA) as a Service
5.7 Other Types of AI Technologies
6 Global AI Created Saas Market, By Functionality
6.1 Introduction
6.2 Analytics and Insights
6.3 Customer Engagement
6.4 Predictive Analytics
6.5 Content Creation
6.6 Security and Fraud Prevention
7 Global AI Created Saas Market, By Delivery Method
7.1 Introduction
7.2 Platform-as-a-Service (PaaS)
7.3 Software-as-a-Service (SaaS)
7.4 Infrastructure-as-a-Service (IaaS)
8 Global AI Created Saas Market, By Deployment Model
8.1 Introduction
8.2 Public Cloud
8.3 Private Cloud
8.4 Hybrid Cloud
9 Global AI Created Saas Market, By Size of Business
9.1 Introduction
9.2 Small and Medium-sized Enterprises
9.3 Large Enterprises
10 Global AI Created Saas Market, By Application
10.1 Introduction
10.2 Healthcare
10.3 Retail
10.4 Finance
10.5 Manufacturing
10.6 Education
10.7 Marketing and Advertising
10.8 Customer Service
10.9 Human Resources (HR)
10.10 Transportation and Logistics
10.11 Other Applications
11 Global AI Created Saas Market, By Geography
11.1 Introduction
11.2 North America
11.2.1 US
11.2.2 Canada
11.2.3 Mexico
11.3 Europe
11.3.1 Germany
11.3.2 UK
11.3.3 Italy
11.3.4 France
11.3.5 Spain
11.3.6 Rest of Europe
11.4 Asia Pacific
11.4.1 Japan
11.4.2 China
11.4.3 India
11.4.4 Australia
11.4.5 New Zealand
11.4.6 South Korea
11.4.7 Rest of Asia Pacific
11.5 South America
11.5.1 Argentina
11.5.2 Brazil
11.5.3 Chile
11.5.4 Rest of South America
11.6 Middle East & Africa
11.6.1 Saudi Arabia
11.6.2 UAE
11.6.3 Qatar
11.6.4 South Africa
11.6.5 Rest of Middle East & Africa
12 Key Developments
12.1 Agreements, Partnerships, Collaborations and Joint Ventures
12.2 Acquisitions & Mergers
12.3 New Product Launch
12.4 Expansions
12.5 Other Key Strategies
13 Company Profiling
13.1 Adobe
13.2 Alteryx
13.3 Amazon Web Services (AWS)
13.4 C3.ai
13.5 Cortexica
13.6 DataRobot
13.7 Freshworks
13.8 Google Cloud
13.9 Hootsuite
13.10 HubSpot
13.11 IBM
13.12 Kaltura
13.13 LogMeIn
13.14 Microsoft
13.15 MonkeyLearn
13.16 Pega Systems
13.17 Salesforce
13.18 Sentient Technologies
13.19 UiPath
13.20 Zendesk
List of Tables
1 Global AI Created Saas Market Outlook, By Region (2022-2030) ($MN)
2 Global AI Created Saas Market Outlook, By Type of AI Technology (2022-2030) ($MN)
3 Global AI Created Saas Market Outlook, By Machine Learning (ML) as a Service (2022-2030) ($MN)
4 Global AI Created Saas Market Outlook, By Natural Language Processing (NLP) as a Service (2022-2030) ($MN)
5 Global AI Created Saas Market Outlook, By Computer Vision as a Service (2022-2030) ($MN)
6 Global AI Created Saas Market Outlook, By Speech Recognition and AI-driven Voice Assistants (2022-2030) ($MN)
7 Global AI Created Saas Market Outlook, By Robotic Process Automation (RPA) as a Service (2022-2030) ($MN)
8 Global AI Created Saas Market Outlook, By Other Types of AI Technologies (2022-2030) ($MN)
9 Global AI Created Saas Market Outlook, By Functionality (2022-2030) ($MN)
10 Global AI Created Saas Market Outlook, By Analytics and Insights (2022-2030) ($MN)
11 Global AI Created Saas Market Outlook, By Customer Engagement (2022-2030) ($MN)
12 Global AI Created Saas Market Outlook, By Predictive Analytics (2022-2030) ($MN)
13 Global AI Created Saas Market Outlook, By Content Creation (2022-2030) ($MN)
14 Global AI Created Saas Market Outlook, By Security and Fraud Prevention (2022-2030) ($MN)
15 Global AI Created Saas Market Outlook, By Delivery Method (2022-2030) ($MN)
16 Global AI Created Saas Market Outlook, By Platform-as-a-Service (PaaS) (2022-2030) ($MN)
17 Global AI Created Saas Market Outlook, By Software-as-a-Service (SaaS) (2022-2030) ($MN)
18 Global AI Created Saas Market Outlook, By Infrastructure-as-a-Service (IaaS) (2022-2030) ($MN)
19 Global AI Created Saas Market Outlook, By Deployment Model (2022-2030) ($MN)
20 Global AI Created Saas Market Outlook, By Public Cloud (2022-2030) ($MN)
21 Global AI Created Saas Market Outlook, By Private Cloud (2022-2030) ($MN)
22 Global AI Created Saas Market Outlook, By Hybrid Cloud (2022-2030) ($MN)
23 Global AI Created Saas Market Outlook, By Size of Business (2022-2030) ($MN)
24 Global AI Created Saas Market Outlook, By Small and Medium-sized Enterprises (2022-2030) ($MN)
25 Global AI Created Saas Market Outlook, By Large Enterprises (2022-2030) ($MN)
26 Global AI Created Saas Market Outlook, By Application (2022-2030) ($MN)
27 Global AI Created Saas Market Outlook, By Healthcare (2022-2030) ($MN)
28 Global AI Created Saas Market Outlook, By Retail (2022-2030) ($MN)
29 Global AI Created Saas Market Outlook, By Finance (2022-2030) ($MN)
30 Global AI Created Saas Market Outlook, By Manufacturing (2022-2030) ($MN)
31 Global AI Created Saas Market Outlook, By Education (2022-2030) ($MN)
32 Global AI Created Saas Market Outlook, By Marketing and Advertising (2022-2030) ($MN)
33 Global AI Created Saas Market Outlook, By Customer Service (2022-2030) ($MN)
34 Global AI Created Saas Market Outlook, By Human Resources (HR) (2022-2030) ($MN)
35 Global AI Created Saas Market Outlook, By Transportation and Logistics (2022-2030) ($MN)
36 Global AI Created Saas Market Outlook, By Other Applications (2022-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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