노코드 머신러닝 시장 규모, 점유율, 성장 분석 : 구성요소별, 도입 형태별, 용도별, 기업 규모별, 최종사용자별, 지역별 - 업계 예측(2026-2033년)

Global No-Code Machine Learning Market size was valued at USD 14.82 Billion in 2024 and is poised to grow from USD 19.03 Billion in 2025 to USD 140.59 Billion by 2033, growing at a CAGR of 28.4% during the forecast period (2026-2033).

The global no-code machine learning market is revolutionizing how enterprises build, train, and deploy predictive models without requiring coding skills, effectively democratizing data science. This shift addresses the shortage of AI talent while meeting the growing demand for analytics, empowering business analysts to spearhead projects. Cloud services and subscription models have lowered barriers to entry, enabling quicker prototyping of models across industries such as retail and healthcare. The integration of model-explainability tools is also crucial, as regulatory pressures demand transparency in AI decision-making. By providing visual explanations and bias diagnostics, organizations can justify choices to stakeholders. As AI-driven automation simplifies model creation through intuitive interfaces, the user base expands, fueling continued adoption and innovation in this dynamic market.

Top-down and bottom-up approaches were used to estimate and validate the size of the Global No-Code Machine Learning market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets 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.

Global No-Code Machine Learning Market Segments Analysis

Global no-code machine learning market is segmented by component, deployment, application, enterprise size, end user and region. Based on component, the market is segmented into Platforms and Services. Based on deployment, the market is segmented into Cloud-Based and On-Premises. Based on application, the market is segmented into Predictive Analytics, Computer Vision, Natural Language Processing and Recommendation Systems. Based on enterprise size, the market is segmented into Large Enterprises and Small & Medium Enterprises. Based on end user, the market is segmented into BFSI, Healthcare, Retail and Manufacturing. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.

Driver of the Global No-Code Machine Learning Market

The Global No-Code Machine Learning market is significantly driven by the ability of organizations to create and deploy machine learning solutions without needing extensive coding skills, facilitating rapid prototyping and iteration. This user-friendly approach allows cross-functional teams to tackle analytical problems independently, minimizing dependence on specialized developers and accelerating the time it takes to realize value. Consequently, business units can more frequently experiment with predictive models, stimulating innovation and boosting demand for no-code platforms. Furthermore, the simplified workflow enhances collaboration between data scientists and domain experts, aligning model assumptions with business goals and bolstering confidence in the solutions produced.

Restraints in the Global No-Code Machine Learning Market

Numerous businesses exercise caution towards the no-code machine learning market due to the often opaque decision-making processes associated with these models. This lack of transparent reasoning can erode stakeholder trust in the outcomes generated, leading to concerns about regulatory compliance, especially in sensitive sectors like finance and healthcare. Consequently, organizations might opt to delay or restrict the implementation of no-code solutions, favoring more conventional methods that provide clearer model explainability. Furthermore, the challenges in tracing feature contributions create weak audit trails, which can dissuade adoption in environments that demand strict governance. This hesitation ultimately hampers the broader acceptance of no-code machine learning technologies.

Market Trends of the Global No-Code Machine Learning Market

The Global No-Code Machine Learning market is witnessing a transformative trend as enterprises embrace AI-powered self-service analytics, enabling business users to independently design, train, and evaluate machine-learning models. This shift towards user-friendly interfaces, coupled with the reduction of reliance on traditional coding, democratizes access to advanced analytics, allowing non-technical staff to swiftly adapt to market dynamics with predictive insights integrated into their workflows. As vendors enhance their platforms with features like pre-trained model libraries and automated deployment processes, organizations globally are cultivating a culture where analytics is embedded across all functions, fostering agility and informed decision-making throughout the enterprise.

Table of Contents

Introduction

• Objectives of the Study
• Market Definition & Scope

Research Methodology

• Research Process
• Secondary & Primary Data Methods
• Market Size Estimation Methods

Executive Summary

• Global Market Outlook
• Key Market Highlights
• Segmental Overview
• Competition Overview

Market Dynamics & Outlook

• Macro-Economic Indicators
• Drivers & Opportunities
• Restraints & Challenges
• Supply Side Trends
• Demand Side Trends
• Porters Analysis & Impact
  • Competitive Rivalry
  • Threat of Substitute
  • Bargaining Power of Buyers
  • Threat of New Entrants
  • Bargaining Power of Suppliers

Key Market Insights

• Key Success Factors
• Market Impacting Factors
• Top Investment Pockets
• Ecosystem Mapping
• Market Attractiveness Index 2025
• PESTEL Analysis
• Regulatory Landscape

Global No-Code Machine Learning Market Size by Component & CAGR (2026-2033)

• Market Overview
• Platforms
• Services

Global No-Code Machine Learning Market Size by Deployment & CAGR (2026-2033)

• Market Overview
• Cloud-Based
• On-Premises

Global No-Code Machine Learning Market Size by Application & CAGR (2026-2033)

• Market Overview
• Predictive Analytics
• Computer Vision
• Natural Language Processing
• Recommendation Systems

Global No-Code Machine Learning Market Size by Enterprise Size & CAGR (2026-2033)

• Market Overview
• Large Enterprises
• Small & Medium Enterprises

Global No-Code Machine Learning Market Size by End User & CAGR (2026-2033)

• Market Overview
• BFSI
• Healthcare
• Retail
• Manufacturing

Global No-Code Machine Learning Market Size & CAGR (2026-2033)

• North America (Component, Deployment, Application, Enterprise Size, End User)
  • US
  • Canada
• Europe (Component, Deployment, Application, Enterprise Size, End User)
  • Germany
  • Spain
  • France
  • UK
  • Italy
  • Rest of Europe
• Asia Pacific (Component, Deployment, Application, Enterprise Size, End User)
  • China
  • India
  • Japan
  • South Korea
  • Rest of Asia-Pacific
• Latin America (Component, Deployment, Application, Enterprise Size, End User)
  • Mexico
  • Brazil
  • Rest of Latin America
• Middle East & Africa (Component, Deployment, Application, Enterprise Size, End User)
  • GCC Countries
  • South Africa
  • Rest of Middle East & Africa

Competitive Intelligence

• Top 5 Player Comparison
• Market Positioning of Key Players, 2025
• Strategies Adopted by Key Market Players
• Recent Developments in the Market
• Company Market Share Analysis, 2025
• Company Profiles of All Key Players
  • Company Details
  • Product Portfolio Analysis
  • Company's Segmental Share Analysis
  • Revenue Y-O-Y Comparison (2023-2025)

Key Company Profiles

• Microsoft Corporation
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Google LLC
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Amazon Web Services, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• IBM Corporation
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• DataRobot, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Dataiku SAS
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• H2O.ai, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Alteryx, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Salesforce, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• SAP SE
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Oracle Corporation
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Akkio Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Obviously AI
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Levity AI GmbH
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• RapidMiner, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• KNIME AG
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Pecan AI Ltd.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• QlikTech International AB
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Zoho Corporation
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments
• Aible, Inc.
  • Company Overview
  • Business Segment Overview
  • Financial Updates
  • Key Developments

Conclusion & Recommendations