The global automated machine learning market size is expected to reach USD ~1,838 million by 2025, growing at a CAGR of +34.0% during the forecast period

Automated Machine Learning Market Size, Share - Industry Report

Automated Machine Learning Market Size, Share, Scope and Forecast

<h2>Market Size and Evolution</h2>
<p>The automated machine learning market has witnessed significant growth over the past few years, and this trend is expected to continue in the coming years.</p>
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<p>The global automated machine learning market size is expected to reach USD ~1,838 million by 2025, growing at a CAGR of +34.0% during the forecast period.</p>
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<p>The increasing demand for predictive analytics, the growing adoption of artificial intelligence (AI) and machine learning (ML), and the rising need for automated tools to manage data complexities are some of the key factors driving the market growth.</p>
<h2>Key Players</h2>
<ul>
<li>DataRobot Inc.</li>
<li>H2O.ai Inc.</li>
<li>dotData Inc.</li>
<li>EdgeVerve Systems Limited</li>
<li>Amazon Web Services Inc.</li>
<li>Squark</li>
<li>Big Squid Inc.</li>
<li>SAS Institute Inc.</li>
<li>Microsoft Corporation</li>
<li>Determined.ai Inc.</li>
</ul>
<h2><strong style=""color: #000000;"">Market Segmentation</strong></h2>
<h3><strong>By Offering</strong></h3>
<ul>
<li>Platform</li>
<li>Service</li>
</ul>
<h3><strong>By Deployment Type</strong></h3>
<ul>
<li>On-Premises</li>
<li>Cloud</li>
</ul>
<h3><strong>By Enterprise Size</strong></h3>
<ul>
<li>Large Enterprise</li>
<li>SME</li>
</ul>
<h3><strong>By Application</strong></h3>
<ul>
<li>Fraud Detection</li>
<li>Sales &amp; Marketing Management</li>
<li>Medical Testing</li>
<li>Transport Optimization</li>
</ul>
<h3><strong>By Industry</strong></h3>
<ul>
<li>BFSI</li>
<li>IT &amp; Telecom</li>
<li>Healthcare</li>
<li>Government</li>
<li>Retail</li>
<li>Manufacturing</li>
</ul>
<h2>Trends and Drivers</h2>
<p>The increasing need for automated machine learning solutions in various industries, such as healthcare, retail, and finance, is a major trend driving the market growth. The growing adoption of cloud-based solutions, the rising demand for personalized and predictive analytics, and the increasing need for data-driven decision-making are also fueling the market growth. Moreover, the emergence of explainable AI and the integration of AI with other technologies, such as Internet of Things (IoT) and blockchain, are creating new opportunities for the market players.</p>
<h2>Opportunities and Threats</h2>
<p>The automated machine learning market presents numerous opportunities for the market players, such as the increasing demand for automation, the rising adoption of cloud-based solutions, and the growing need for predictive analytics. However, the market is also facing several challenges, such as the lack of skilled professionals and the high cost of implementation. Moreover, the increasing concerns over data privacy and security, and the lack of transparency in AI algorithms pose a significant threat to the market growth.</p>
<h2>Regulatory and Legal Issues</h2>
<p>The regulatory and legal issues affecting the automated machine learning market are related to data privacy and security. The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are some of the regulations that companies need to comply with while collecting, processing, and storing personal data. The lack of transparency and accountability in AI algorithms is also a major concern, and regulatory bodies are working towards addressing these issues.</p>
<h2>Target Demographics</h2>
<p>The automated machine learning market is targeted towards various industries, such as healthcare, finance, retail, and manufacturing. The target demographics for this market include data scientists, business analysts, and decision-makers who are looking for automated solutions to manage their data complexities. These demographics prefer cloud-based solutions that are easy to use, cost-effective, and scalable.</p>
<h2>Pricing Trends</h2>
<p>The pricing trends in the automated machine learning market vary across different segments. The pricing models are typically based on the number of users, the volume of data, and the level of customization required. The cloud-based solutions are generally priced on a subscription basis, while the on-premise solutions are priced on a perpetual license basis.</p>
<h2>Conclusion</h2>
<p>The automated machine learning market is experiencing significant growth, driven by the increasing demand for predictive analytics, the growing adoption of AI and ML, and the rising need for automated tools to manage data complexities. The market is highly competitive, with several large and small players offering advanced solutions. However, the market is also facing several challenges, such as the lack of skilled professionals and the high cost of implementation. The market presents numerous opportunities for the players, such as the increasing demand for automation&nbsp;and the rising adoption of cloud-based solutions. However, the market also faces threats such as the lack of transparency in AI algorithms and concerns over data privacy and security.</p>
<p>As the market evolves, it is expected that the demand for automated machine learning solutions will continue to grow, driven by the increasing need for data-driven decision-making and the emergence of new technologies. The market players will need to focus on developing advanced solutions that meet the changing needs of the customers and comply with the regulatory and legal requirements. Additionally, they will need to address the challenges of the market, such as the lack of skilled professionals, by investing in training programs and collaborations with academic institutions.</p>
<p>In conclusion, the automated machine learning market presents significant growth opportunities for the market players, driven by the increasing demand for automation and predictive analytics. However, the market also faces challenges such as the lack of skilled professionals and concerns over data privacy and security. The players will need to focus on developing advanced solutions that meet the changing needs of the customers while complying with the regulatory and legal requirements.</p>