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The Automated Machine Learning Market grew from USD 1.63 billion in 2023 to USD 2.21 billion in 2024. It is expected to continue growing at a CAGR of 35.70%, reaching USD 13.88 billion by 2030. Speak directly to the analyst to clarify any post sales queries you may have.
Automated Machine Learning (AutoML) refers to the process of automating the tasks of applying machine learning to real-world problems, making it accessible to users who have limited expertise in data science. The scope of AutoML includes feature engineering, model selection, hyperparameter tuning, and deployment, significantly reducing the time and effort required from data professionals. The necessity of AutoML is driven by the demand for faster insights and decisions in today's data-driven business environment, where expertise in model selection and tuning is scarce. Its application spans various sectors, including finance, healthcare, retail, and marketing, helping businesses improve predictive accuracy and operational efficiency. End-use scope ranges from start-ups and SMEs to large enterprises seeking to leverage data in a cost-effective manner. Key factors influencing growth include the increasing adoption of AI, rising demand for advanced analytical techniques, and the need for democratization of data analytics. Opportunities lie in expanding application areas, particularly in realms like IoT analytics and personalized medicine, offering lucrative growth potential for stakeholders. To seize these opportunities, businesses should focus on developing user-friendly interfaces and enhancing algorithm efficiency. Nevertheless, challenges such as data privacy concerns, high initial setup costs, and a lack of skilled personnel could impede market growth. Also, there is a need for continuous learning and adaptation to new data types and structures. Potential areas for innovation include real-time AutoML solutions and developing AutoML tools for edge computing scenarios. Insights into market nature suggest a competitive landscape with leading tech companies and emerging startups driving advancements. To sustain growth, businesses should engage in continuous R&D, form strategic partnerships, and focus on customer training to bridge expertise gaps. Leveraging these insights can enable businesses to maximize the benefits of AutoML while effectively navigating its challenges.
Understanding Market Dynamics in the Automated Machine Learning Market
The Automated Machine Learning Market is rapidly evolving, shaped by dynamic supply and demand trends. These insights provide companies with actionable intelligence to drive investments, develop strategies, and seize emerging opportunities. A comprehensive understanding of market dynamics also helps organizations mitigate political, geographical, technical, social, and economic risks while offering a clearer view of consumer behavior and its effects on manufacturing costs and purchasing decisions.- Market Drivers
- Increasing demand for data-driven insights for decision-making
- Expanding democratization of machine learning capabilities
- Market Restraints
- Interpretability and transparency issues associated with AutoML platforms
- Market Opportunities
- Advancements in artificial intelligence (AI) and machine learning (ML) technologies
- Growing integration of AutoML with DevOps practices that enhance the development of machine learning models
- Market Challenges
- Security and privacy concerns of AutoML platforms
Exploring Porter’s Five Forces for the Automated Machine Learning Market
Porter’s Five Forces framework further strengthens the insights of the Automated Machine Learning Market, delivering a clear and effective methodology for understanding the competitive landscape. This tool enables companies to evaluate their current competitive standing and explore strategic repositioning by assessing businesses’ power dynamics and market positioning. It is also instrumental in determining the profitability of new ventures, helping companies leverage their strengths, address weaknesses, and avoid potential pitfalls.Applying PESTLE Analysis to the Automated Machine Learning Market
External macro-environmental factors deeply influence the performance of the Automated Machine Learning Market, and the PESTLE analysis provides a comprehensive framework for understanding these influences. By examining Political, Economic, Social, Technological, Legal, and Environmental elements, this analysis offers organizations critical insights into potential opportunities and risks. It also helps businesses anticipate changes in regulations, consumer behavior, and economic trends, enabling them to make informed, forward-looking decisions.Analyzing Market Share in the Automated Machine Learning Market
The Automated Machine Learning Market share analysis evaluates vendor performance. This analysis provides a clear view of each vendor’s standing in the competitive landscape by comparing key metrics such as revenue, customer base, and other critical factors. Additionally, it highlights market concentration, fragmentation, and trends in consolidation, empowering vendors to make strategic decisions that enhance their market position.Evaluating Vendor Success with the FPNV Positioning Matrix in the Automated Machine Learning Market
The Automated Machine Learning Market FPNV Positioning Matrix is crucial in evaluating vendors based on business strategy and product satisfaction levels. By segmenting vendors into four quadrants - Forefront (F), Pathfinder (P), Niche (N), and Vital (V) - this matrix helps users make well-informed decisions that best align with their unique needs and objectives in the market.Strategic Recommendations for Success in the Automated Machine Learning Market
The Automated Machine Learning Market strategic analysis is essential for organizations aiming to strengthen their position in the global market. A comprehensive review of resources, capabilities, and performance helps businesses identify opportunities for improvement and growth. This approach empowers companies to navigate challenges in the increasingly competitive landscape, ensuring they capitalize on new opportunities and align with long-term success.Key Company Profiles
The report delves into recent significant developments in the Automated Machine Learning Market, highlighting leading vendors and their innovative profiles. These include Aible, Inc., Akkio Inc., Altair Engineering Inc., Alteryx, Amazon Web Services, Inc., Automated Machine Learning Ltd., BigML, Inc., Databricks, Inc., Dataiku, DataRobot, Inc., Google LLC by Alphabet Inc., H2O.ai, Inc., Hewlett Packard Enterprise Company, InData Labs Group Limited, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, QlikTech International AB, Runai Labs Ltd., Salesforce, Inc., SAS Institute Inc., ServiceNow, Inc., SparkCognition, Inc., STMicroelectronics, Tata Consultancy Services Limited, TAZI AI, Tellius, Inc., Weidmuller Limited, Wolfram, and Yellow.ai.Market Segmentation & Coverage
This research report categorizes the Automated Machine Learning Market to forecast the revenues and analyze trends in each of the following sub-markets:- Automation Type
- Data Processing
- Feature Engineering
- Modeling
- Visualization
- Deployment
- Cloud
- On-premises
- Application
- Automotive, Transportations, and Logistics
- Banking, Financial Services, and Insurance
- Government & Defense
- Healthcare & Life Sciences
- It & Telecommunications
- Media & Entertainment
- Region
- Americas
- Argentina
- Brazil
- Canada
- Mexico
- United States
- California
- Florida
- Illinois
- New York
- Ohio
- Pennsylvania
- Texas
- Asia-Pacific
- Australia
- China
- India
- Indonesia
- Japan
- Malaysia
- Philippines
- Singapore
- South Korea
- Taiwan
- Thailand
- Vietnam
- Europe, Middle East & Africa
- Denmark
- Egypt
- Finland
- France
- Germany
- Israel
- Italy
- Netherlands
- Nigeria
- Norway
- Poland
- Qatar
- Russia
- Saudi Arabia
- South Africa
- Spain
- Sweden
- Switzerland
- Turkey
- United Arab Emirates
- United Kingdom
- Americas
The report provides a detailed overview of the market, exploring several key areas:
- Market Penetration: A thorough examination of the current market landscape, featuring comprehensive data from leading industry players and analyzing their reach and influence across the market.
- Market Development: The report identifies significant growth opportunities in emerging markets and assesses expansion potential within established segments, providing a roadmap for future development.
- Market Diversification: In-depth coverage of recent product launches, untapped geographic regions, significant industry developments, and strategic investments reshaping the market landscape.
- Competitive Assessment & Intelligence: A detailed analysis of the competitive landscape, covering market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, technological advancements, and innovations in manufacturing by key market players.
- Product Development & Innovation: Insight into groundbreaking technologies, R&D efforts, and product innovations that will drive the market in future.
Additionally, the report addresses key questions to assist stakeholders in making informed decisions:
- What is the current size of the market, and how is it expected to grow?
- Which products, segments, and regions present the most attractive investment opportunities?
- What are the prevailing technology trends and regulatory factors influencing the market?
- How do top vendors rank regarding market share and competitive positioning?
- What revenue sources and strategic opportunities guide vendors' market entry or exit decisions?
Table of Contents
1. Preface
2. Research Methodology
4. Market Overview
5. Market Insights
6. Automated Machine Learning Market, by Automation Type
7. Automated Machine Learning Market, by Deployment
8. Automated Machine Learning Market, by Application
9. Americas Automated Machine Learning Market
10. Asia-Pacific Automated Machine Learning Market
11. Europe, Middle East & Africa Automated Machine Learning Market
12. Competitive Landscape
List of Figures
List of Tables
Companies Mentioned
The leading players in the Automated Machine Learning market, which are profiled in this report, include:- Aible, Inc.
- Akkio Inc.
- Altair Engineering Inc.
- Alteryx
- Amazon Web Services, Inc.
- Automated Machine Learning Ltd.
- BigML, Inc.
- Databricks, Inc.
- Dataiku
- DataRobot, Inc.
- Google LLC by Alphabet Inc.
- H2O.ai, Inc.
- Hewlett Packard Enterprise Company
- InData Labs Group Limited
- Intel Corporation
- International Business Machines Corporation
- Microsoft Corporation
- Oracle Corporation
- QlikTech International AB
- Runai Labs Ltd.
- Salesforce, Inc.
- SAS Institute Inc.
- ServiceNow, Inc.
- SparkCognition, Inc.
- STMicroelectronics
- Tata Consultancy Services Limited
- TAZI AI
- Tellius, Inc.
- Weidmuller Limited
- Wolfram
- Yellow.ai
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 195 |
| Published | October 2024 |
| Forecast Period | 2024 - 2030 |
| Estimated Market Value ( USD | $ 2.21 Billion |
| Forecasted Market Value ( USD | $ 13.88 Billion |
| Compound Annual Growth Rate | 35.7% |
| Regions Covered | Global |
| No. of Companies Mentioned | 31 |
