In 2021, the market for no-code AI platforms had a US$2,581.3 Million valuation. The no-code AI platform market is anticipated to develop at a CAGR of 28.1% from 2022 to 2032, reaching US$ 38,518.0 Million.
No-code AI platforms are designed to give users who are not programmers, beginners, or who may not have the best understanding of AI implementation the tools and resources they need to develop their own AI models and projects without writing a single line of code.
People with AI skills can also use no-code AI platforms to speed up their productivity. The platform has user-friendly features like drag-and-drop that make the process simpler for people who aren’t programmers.
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Key Takeaways: No-Code AI Platform Market
- By solution, the no-code AI tool segment had generated a share of nearly US$ 1,840.4 Mn in 2021.
- By industry, the BFSI segment exhibited the highest CAGR of 2% in 2021.
- By technology, the predictive analysis segment is set to witness the fastest growth at a CAGR of 7% in the forecast period.
- The top 5 key players in the global no-code AI platform market are set to generate about 35% of the share in the assessment period.
- The India no-code AI platform market is expected to showcase the highest CAGR of 5% in the forecast period.
“Increasing use of no-code AI platforms in non-technical fields to automate processes which are often deemed repetitive and mundane is expected to drive the market,” says an FMI analyst.
The ability of No-Code AI Platforms to Enable Domain Experts to Develop AI Projects Will Aid the Growth
No-code AI platforms provide users with several drag-and-drop, user-friendly options, and features to build AI models, ML programs, and automated processes. Due to their simplification, businesses can easily build chatbots for themselves and even software developers who do not have expertise in AI can implement novel features in their software solutions by using no-code AI platforms.
Cyber security professionals can find bugs and errors in their systems and improve the accuracy when they are analyzing their data. AI can also help individuals and businesses to accomplish their tasks in a more efficient manner, as well as improve those tasks which their software and products could not do.
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More Valuable Insights on No-Code AI Platform Market
In this report by Future Market Insights, no-code AI platform has been segmented into four sections: by solution no code AI tools: (cloud-based and on-premises); services (professional services (consulting services, support and maintenance, training and education, software development) and managed services), technology (Natural Language Processing (NLP), Computer Vision, Predictive Analytics), enterprise size (Small and medium enterprises (SME) and large enterprises), industry (BFSI, IT & telecom, retail, healthcare, manufacturing, government, education and others), and region (North America, Latin America, Europe, East Asia, South Asia & Pacific, and Middle East & Africa), to help readers understand and evaluate lucrative opportunities in the no-code AI platform demand outlook.
No-Code AI Platform Outlook by Category
By Solution:
No-code AI tools
- Cloud-Based
- On-Premises
Services
- Professional Services
- Managed Services
By Technology:
- Natural Language Processing (NLP)
- Computer Vision
- Predictive Analytics
By Enterprise Size:
- Small and Mid-Sized Enterprises (SMEs)
- Large Enterprises
By Industry:
- BFSI
- IT & Telecom
- Retail
- Healthcare
- Manufacturing
- Government
- Education
- Others
By Region:
- North America
- Latin America
- Europe
- South Asia & Pacific
- East Asia
- Middle East & Africa
Table of Content
1. Executive Summary | No-Code AI Platform Market
1.1. Global Market Outlook
1.2. Demand Side Trends
1.3. Supply Side Trends
1.4. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition
3. Key Market Trends
3.1. Key Trends Impacting the Market
3.2. Solution Innovation / Development Trends
3.3. Key Success Factors
4. Pricing Analysis
4.1. Types of pricing models, By Solution
4.2. Global pricing analysis benchmark
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