No-Code Machine Learning Market Report 2026

No-Code Machine Learning Market Overview

• No-Code Machine Learning market size has reached to $1.45 billion in 2025 • Expected to grow to $5.49 billion in 2030 at a compound annual growth rate (CAGR) of 30.5% • Growth Driver: Rising IoT Adoption Driving Growth In No-Code Machine Learning Market • Market Trend: Advancements In No-Code Machine Learning • North America was the largest region in 2025 and Asia-Pacific is the fastest growing region.

What Is Covered Under No-Code Machine Learning Market?

No-code machine learning refers to the practice of developing, deploying, and managing machine learning models without writing any code. This approach typically involves using graphical interfaces, drag-and-drop tools, and pre-built templates provided by no-code platforms. These platforms abstract the complexities of programming and data science, enabling users, often non-technical professionals, to build and use machine learning models by following intuitive steps. The main offering of no-code machine learning offerings include platforms and services. A no-code machine learning platform is a software tool that enables users to create, train, and deploy machine learning models without writing any code, using a visual interface to simplify the process for non-technical users. It can be deployed both on the cloud and on-premise and is used by various industries such as banking, financial services and insurance (BFSI), healthcare, retail, information technology (IT), telecom, manufacturing, and government. It is used for various applications, including predictive analytics, process automation, data visualization, business intelligence, customer relationship management, and supply chain optimization.

What Is The No-Code Machine Learning Market Growth Forecast?

The no-code machine learning market size is expected to see exponential growth in the next few years. It will grow to $5.49 billion in 2030 at a compound annual growth rate (CAGR) of 30.5%. The growth in the forecast period can be attributed to integration with predictive analytics tools, growth in business intelligence platforms, demand for rapid model deployment, adoption across healthcare and bfsI sectors, emergence of self-service ml platforms. Major trends in the forecast period include low-code/no-code adoption, automated model tuning, citizen data scientist enablement, drag-and-drop AI workflows, pre-built ml templates.

Global No-Code Machine Learning Market Segmentation

1) By Offering: Platform, Services 2) By Deployment Mode: Cloud-Based, On-Premise 3) By Industry Vertical: Banking, Financial Services And Insurance (BFSI), Healthcare, Retail, Information Technology(IT) And Telecom, Manufacturing, Government 4) By Application: Predictive Analytics, Process Automation, Data Visualization, Business Intelligence, Customer Relationship Management, Supply Chain Optimization Subsegments: 1) By Platform: Automated Machine Learning Platforms (AutoML), Drag-and-Drop Machine Learning Platforms, Model Deployment Platforms, Data Preparation Platforms, Visualization Aand Reporting Platforms, Integration Platforms for APIs And Data Sources 2) By Services: Consulting Services, Implementation Services, Training and Education Services, Support And Maintenance Services, Custom Solution Development Services

What Is The Driver Of The No-Code Machine Learning Market?

The rising adoption of the internet of things (IoT) is expected to propel the growth of the no-code machine learning market going forward. The Internet of Things (IoT) refers to the network of interconnected devices and systems that communicate and exchange data with each other over the Internet to automate processes and enhance operational efficiency. The adoption of IoT is due to its ability to improve operational efficiency, provide real-time data insights, enable automation and remote monitoring, reduce costs, improve decision-making, and drive innovation across various industries by connecting and optimizing a wide range of devices and systems. No-code machine learning is increasingly being used in the Internet of Things (IoT) to facilitate creating, deploying, and managing machine learning models without deep technical expertise. For instance, in December 2023, according to the Organisation for Economic Co operation and Development (OECD), a France-based intergovernmental organization, in its Measuring the Internet of Things report, stated that 33 % of businesses in OECD countries had adopted IoT technologies, up from 28 % in 2022, reflecting a year on year increase of 5 percentage points. Therefore, the rise in adoption of the internet of things (IoT) is driving the growth of the no-code machine learning industry.

Key Players In The Global No-Code Machine Learning Market

Major companies operating in the no-code machine learning market are Apple Create ML, Microsoft Azure Machine Learning Studio, Amazon Web Services, SAS Viya, DataRobot Inc, LityxIQ, H2O.ai, Dataiku DSS, C3 AI Suite, RapidMiner Studio, BigML Inc., Google Teachable Machine, Edge Impulse, Microsoft Lobe, KNIME Analytics Platform, MonkeyLearn, Akkio AI, Obviously AI, Runway ML, Fritz AI, Sway AI, PyCaret, Ever AI, Neural Designer

Global No-Code Machine Learning Market Trends and Insights

Major companies operating in the no-code machine learning market are focused on developing advanced technology to improve workflow automation, such as no-code machine learning tools. No-code machine learning tools allow users to create and deploy machine learning models without writing code, making the technology more accessible to non-technical users. For instance, in December 2023, Amazon, a US-based technology company, launched SageMaker Canvas, a no-code machine learning tool designed to enable users without coding experience to build machine learning models. Targeted at business analysts and non-technical users, this tool features a user-friendly interface for easy model creation, data preparation, and training. Critical applications include customer churn prediction, fraud detection, and inventory optimization.

What Are Latest Mergers And Acquisitions In The No-Code Machine Learning Market?

In July 2024, Forwrd.ai, a US-based data-science automation platform, acquired LoudnClear.AI for an undisclosed amount. The acquisition will allow LoudnClear.AI to continue building on its vision of enabling revenue operations and business teams to quickly analyze unstructured data and better understand customer sentiment using NLP, machine learning, and AI. LoudnClear.AI is an Israel-based provider of no-code machine learning capabilities.

Regional Insights

North America was the largest region in the no-code machine learning market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in this market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in this market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

What Defines the No-Code Machine Learning Market?

The no-code machine learning market consists of revenues earned by entities by providing services such as model building, data preparation, data visualization, model training and evaluation. The market value includes the value of related goods sold by the service provider or included within the service offering. The no-code machine learning market also includes sales of data preparation tools, automated machine learning solutions, drag-and-drop workflow builders and predictive analytics tools. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

How is Market Value Defined and Measured?

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified). The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

What Key Data and Analysis Are Included in the No-Code Machine Learning Market Report 2026?

The no-code machine learning market research report is one of a series of new reports from The Business Research Company that provides market statistics, including industry global market size, regional shares, competitors with the market share, detailed market segments, market trends and opportunities, and any further data you may need to thrive in the no-code machine learning industry. The market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future state of the industry.