The AI In Infrastructure And Platforms As A Service Market is being driven by Imperative to manage escalating IT complexity
The AI In Infrastructure And Platforms As A Service Market is expected to grow at a CAGR of 21.1% during 2024 and 2029. During this period, the market is also expected to show a growth of USD 62704.1 million. The global AI in Infrastructure and Platforms as a Service (PaaS) market is witnessing a significant shift, with cloud platforms evolving from simple endpoints for AI models into advanced, AI-driven governance and management layers. As enterprises expand their use of foundation models from providers such as OpenAI, Anthropic, Cohere, and open source communities, they encounter new challenges related to risk management, cost optimization, and compliance. To address these complexities, there is a growing need for a centralized control plane capable of managing the entire lifecycle of AI assets. In response, Infrastructure as a Service (IaaS) and PaaS providers are integrating intelligent services into their platforms, offering enterprises a more streamlined and efficient approach to AI asset management.
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The market is segmented based on
According to Technavio, There are several factors that are causing the market to flourish during the forecast period, which are as follows:
However, the market also witnesses some limitations, which are as follows:
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Market Scope |
|
Report Coverage |
Details |
Page number |
240 |
Base year |
2024 |
Historic period |
2019-2023 |
Forecast period |
2025-2029 |
Growth momentum & CAGR |
Accelerate at a CAGR of 21.1% |
Market growth 2025-2029 |
USD 62704.1 million |
Market structure |
fragmentation |
YoY growth 2024-2025(%) |
19.4 |
Key countries |
US, China, UK, South Korea, France, Germany, India, Canada, Italy, and Japan |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
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The AI Infrastructure and Platforms as a Service market encompasses various components including AI platform security, AI model management, AI data annotation, AI algorithm training, and AI infrastructure cost. Key performance indicators include AI model accuracy, bias detection, explainability tools, model retraining, and performance metrics. System reliability, scalability solutions, infrastructure design, and platform integration are crucial for optimal AI performance. AI data preprocessing, feature engineering, model optimization, and platform monitoring ensure efficient resource utilization and deployment automation. Infrastructure upgrades, maintenance, compliance standards, risk assessment, governance framework, and model lifecycle management are essential for ensuring the effectiveness and reliability of AI systems.
The AI Infrastructure and Platforms as a Service market encompasses companies that provide AI infrastructure, cloud-based AI services, machine learning APIs, and deep learning frameworks. This sector falls under the broader IT software market, which comprises firms involved in the development and production of all types of software, including cloud-based solutions. According to Technavio, the global IT software market size is determined by the consolidated revenue of these companies. This market segment includes application software firms specializing in enterprise and technical solutions, excluding those producing interactive home entertainment software or database management software classified under systems software.. Industries are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.
Technavio Research
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