Cloud AI Industry Forecast (2024-2029) By Offering, Technology Type, Hosting Type, Organization Size, Business Function, Verticals And Region

Dublin, Dec. 16, 2024 (GLOBE NEWSWIRE) -- The "Cloud AI market Forecast to 2029" report has been added to ResearchAndMarkets.com's offering.
The cloud AI market will grow from USD 80.30 billion in 2024 to USD 327.15 billion by 2029 at a compounded annual growth rate (CAGR) of 32.4% during the forecast period. Some of the significant cloud AI market vendors profiled in this report include google (US), IBM (US), AWS (US), Microsoft (US), Oracle (US), Nvidia (US), Salesforce (US), SAP (Germany), Alibaba Cloud (China), HPE (US), and Intel (US).

This research report estimates the market size and growth potential for many segments based on offering, technology type, hosting type, organization size, business function, verticals, and region. It contains a thorough competition analysis of the major market participants, information about their businesses, essential observations about their product and service offerings, current trends, and critical market strategies.

Cloud AI transforms technology use across industries, including manufacturing, healthcare, finance, and retail. For instance, hospitals employ cloud AI to forecast health trends and quickly evaluate medical data, assisting physicians in making better decisions for their patients.
More businesses are using cloud AI since it offers powerful computing and data analysis without needing hardware investments. This allows companies to use AI for real-time insights, predictions, and automation, helping them work more efficiently, save money, and focus on core operations.

By offering, the AI as a service segment holds the highest CAGR during the forecast period
AI-as-a-Service (AIaaS) is expected to grow the highest in the cloud AI market. It gives businesses access to advanced AI tools without investing in expensive infrastructure or specialized knowledge. A key advantage of AIaaS is its scalability and flexibility. Businesses can quickly change their AI capabilities as required, which works well for companies of all sizes. It also makes AI accessible to smaller businesses that don't have the resources to create and manage their systems. AIaaS providers often have simple interfaces and tools that make it easier to connect with existing systems, so businesses don't need extensive technical skills.
AIaaS is becoming more popular as businesses try to improve customer experiences and run their operations more efficiently. The growth of AutoML (automated machine learning) and pre-trained models in AIaaS is helping this trend by making it easier to develop and use AI applications. As businesses embrace data-driven decision-making, AIaaS will be crucial in navigating data complexities and driving innovation.
Based on vertical, the BFSI segment holds the largest market share during the forecast period
Banks and financial services use cloud AI to improve security, customer service, and efficiency. Cloud AI helps them analyze data instantly, which is essential for detecting fraud, managing risks, and providing personalized services for each customer. AI models process large amounts of data in real-time to find unusual patterns and reduce the risks of financial crimes. Cloud AI improves customer service by offering personalized advice and chatbots, making banking faster and more effective in meeting the growing demand for digital services.
In insurance, cloud AI speeds up claims processing, predicts risks, and examines data, making work quicker and decisions more accurate. It also allows businesses to adjust resources without significant upfront investments in IT systems. This flexibility helps companies to adapt to changing market demands and follow new regulations. Overall, cloud AI improves security, lets companies offer personalized services, and helps them operate more efficiently to meet customer needs and keep up with a fast-changing digital world.
Based on the business function, the operations & supply segment holds the highest CAGR during the forecast period.
Cloud AI transforms how companies manage logistics, inventories, and efficiency in operations and supply chains. Companies could use AI systems to obtain real-time data about their supply chain, improve inventory management, and better predict demand. This reduces expenses, increases flexibility, and helps to satisfy customers' needs better. AI also helps businesses find potential problems and improve delivery routes, making the supply chain faster and more responsive.
Recent trends in the cloud AI market for operations and supply chain chains include the integration of Internet of Things (IoT) devices for real-time data collection, which enhances visibility across the supply chain. More businesses are using AI to automate tasks such as order processing and inventory management so their employees can focus on making key decisions. AI also helps with predictive maintenance, keeping equipment running smoothly and reducing expensive downtime. As companies work to be more eco-friendly, AI helps them cut waste and use resources more efficiently.

Key Attributes

Market Dynamics

• Drivers
  • Increasing Advancements in Generative AI and Intelligent Automation
  • Rising Adoption of Cloud-based Services and Applications
  • Growing Importance of Data-Driven Decision-Making
• Restraints
  • Data Privacy and Security Concerns
  • Limited Internet Connectivity
• Opportunities
  • Expansion into SMEs
  • Integration with Emerging Technologies
• Challenges
  • Complexity of AI Integration
  • High Costs of AI Implementation

Case Study Analysis

• Case Study 1: Siemens Connected Frontline Workers and Engineers for Real-Time Problem-Solving Using Azure AI
• Case Study 2: Accelerated Collection and Analysis of Investment Information for Edgar Finance with Help of IBM
• Case Study 3: Automating Support Request Triage with Salesforce AI

List of Companies Profiled

• Google
• IBM
• AWS
• Microsoft
• Oracle
• Nvidia
• Salesforce
• SAP
• Alibaba Cloud
• HPE
• Intel
• Tencent Cloud
• Openai
• Baidu
• Huawei
• C3 AI
• Cloudera
• Altair
• Infracloud Technologies
• Cloudminds
• Datarobot
• Cohere
• Glean
• H2O.AI
• Scale AI
• Inflection AI
• Anyscale
• Frame.AI
• Dataiku
• Yellow.AI
• Viso.AI

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• Cloud AI Market

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