 
					Worldwide AI Life-Cycle Software Market Shares, 2021: Machine Learning Accelerates
Description
						Worldwide AI Life-Cycle Software Market Shares, 2021: Machine Learning Accelerates
This IDC study presents a view of worldwide artificial intelligence life-cycle software revenue broken down by vendor for the historical year 2021."The artificial intelligence life-cycle software market achieved significant growth in 2021 in spite of economic headwinds, growing 47% to $4.7 billion," says Dave Schubmehl, research VP, AI and Automations Software research at IDC. "The AI life-cycle software platforms market in 2021 saw continued growth in all segments of the market, providing enterprises with capabilities for model building, training, and inferencing. The combination of new and easy-to-use tools and capabilities for creating, building, deploying, and monitoring ML models has seen widespread adoption and increasing maturity. Facilities for ML operations, workflow collaboration, and a better understanding of deployment practices and available choices are enabling end users to move models from experimentation to production more quickly than ever before as well as opening up machine learning to organizations that have never previously developed their own models."
Please Note: Extended description available upon request.
							
						
					
				This IDC study presents a view of worldwide artificial intelligence life-cycle software revenue broken down by vendor for the historical year 2021."The artificial intelligence life-cycle software market achieved significant growth in 2021 in spite of economic headwinds, growing 47% to $4.7 billion," says Dave Schubmehl, research VP, AI and Automations Software research at IDC. "The AI life-cycle software platforms market in 2021 saw continued growth in all segments of the market, providing enterprises with capabilities for model building, training, and inferencing. The combination of new and easy-to-use tools and capabilities for creating, building, deploying, and monitoring ML models has seen widespread adoption and increasing maturity. Facilities for ML operations, workflow collaboration, and a better understanding of deployment practices and available choices are enabling end users to move models from experimentation to production more quickly than ever before as well as opening up machine learning to organizations that have never previously developed their own models."
Please Note: Extended description available upon request.
Table of Contents
										11 Pages
									
							- IDC Market Share Figure
- Executive Summary
- Advice for Technology Suppliers
- MLOps and ModelOps
- Trustworthy AI
- Democratization of AI
- Market Share
- Who Shaped the Year
- Market Context
- AI-Enabled Digital Transformations
- Democratization of AI
- Post-Pandemic Recovery
- Open Source–Driven Adoption and Path to Consolidation
- Expanding Ecosystem
- Significant Market Developments
- Methodology
- Market Definition
- AI Life-Cycle Software
- Data Labeling Software
- AI Build Software
- MLOps Software
- Trustworthy AI Software
- Related Research
Pricing
Currency Rates 
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