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The cloud artificial intelligence (AI) market size is forecast to increase by USD 12.61 billion at a CAGR of 24.1% between 2023 and 2028. The market is experiencing significant growth, driven by the integration of advanced algorithms and human intelligence. Speech recognition technology, a key application of AI, is revolutionizing digital media and communication. In the healthcare sector, AI is being used for diagnostics, enabling more accurate and efficient medical decisions. Machine learning (ML), deep learning, and neural networks are at the heart of these advancements, enabling systems to learn from data and make intelligent decisions. However, challenges persist, including the need for cybersecurity measures to protect sensitive data and the increasing competition from open-source platforms. As businesses continue to adopt AI for various applications, the market is expected to grow further, transforming industries and enhancing human capabilities.
Algorithms, Deep Learning, and Beyond Cloud Artificial Intelligence (AI) is revolutionizing the business world by integrating human intelligence with advanced algorithms and machine learning (ML) techniques. This transformation is reshaping various industries, from digital media to healthcare diagnostics, cybersecurity, and IT services. Algorithms, the backbone of AI, are the set of instructions that enable computers to perform specific tasks. In the cloud, these algorithms are executed on hyperscale platforms, enabling businesses to process massive amounts of data in real-time. This leads to improved decision-making capabilities, enhanced productivity, and significant cost savings. Machine Learning (ML) and Deep Learning (DL), subsets of AI, are increasingly being adopted for business applications. ML algorithms learn from data and improve their performance over time, while DL algorithms can identify complex patterns and relationships within data, making them invaluable for speech recognition, image recognition, and natural language processing. Neural networks, a type of ML model inspired by the human brain, are being used for generative AI applications, enabling businesses to create personalized content and experiences for their customers.
Moreover, these AI models can learn from data and generate new, original content, leading to increased engagement and loyalty. Cloud AI is also making significant strides in the areas of diagnostics and cybersecurity. In diagnostics, AI algorithms can analyze medical images and patient data to identify diseases and potential health risks, leading to earlier and more accurate diagnoses. In cybersecurity, AI models can analyze network traffic and user behavior to detect threats and prevent cyberattacks. Business decisions are being augmented by AI, with predictive analytics and data management playing a crucial role. Predictive analytics uses historical data and ML algorithms to identify trends and make future predictions, enabling businesses to make informed decisions and stay ahead of the competition. Data management ensures that businesses have access to accurate and relevant data, which is essential for effective decision-making. Cloud AI is also transforming IT services, with automation being a key area of focus. Automation using AI algorithms can help businesses streamline their operations, reduce manual effort, and improve efficiency. Human capital management is another area where cloud AI is being used to automate repetitive tasks, freeing up human resources for more strategic initiatives. The integration of AI with cloud infrastructure and IT services is leading to significant cost savings for businesses.
Furthermore, by moving AI workloads to the cloud, businesses can avoid the upfront costs of purchasing and maintaining expensive hardware and infrastructure. Additionally, cloud AI services offer pay-as-you-go pricing models, allowing businesses to only pay for the resources they use. Cloud AI also offers enhanced security features, including threat detection and data encryption. Threat detection using AI algorithms can help businesses identify and respond to cyber threats in real-time, while data encryption ensures that sensitive data is protected both in transit and at rest. In conclusion, cloud AI is transforming the business landscape by integrating human intelligence with advanced algorithms and ML techniques. From speech recognition and diagnostics to cybersecurity and business decisions, cloud AI is enabling businesses to gain insights from data, automate processes, and make informed decisions. With its cost savings, security features, and scalability, cloud AI is a game-changer for businesses of all sizes.
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD billion" for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.
The software segment is estimated to witness significant growth during the forecast period. Artificial Intelligence (AI) software, which mimics human learning and behavior, is revolutionizing various industries by automating processes, personalizing services, and generating valuable insights. Hyperscale cloud platforms have become the backbone of AI development, enabling businesses to build new software or expand existing applications with AI capabilities.
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The software segment was the largest segment and valued at USD 2.8 billion in 2018. This includes automating decision-making processes in IT services, data analytics, human capital management, and cloud management. The shift towards digitization has been a driving force behind industrial reforms, particularly in sectors like healthcare. For instance, 93% of healthcare organizations in the US have adopted a digital transformation strategy, deploying AI, cloud computing, and enterprise resource planning software to maintain electronic health records and improve patient care. Hence, such factors are fuelling the growth of this segment during the forecast period.
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North America is estimated to contribute 50% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. The North American market for cloud Artificial Intelligence (AI) has witnessed significant growth due to the region's technological maturity and early adoption of advanced technologies. The industrial sector's strong presence and penetration of leading companies in the region contribute to the market's expansion. With advanced economies generating and consuming vast amounts of data, the demand for cloud AI solutions is high.
Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
Emergence of technologically advanced devices is notably driving market growth. The cloud AI market has witnessed significant advancements with the integration of algorithms and machine learning (ML) technologies in various applications. Speech recognition and diagnostics are two primary areas where ML and deep learning have made a substantial impact. In digital media, ML algorithms enable personalized recommendations and content delivery, enhancing user experience. Human intelligence is being augmented through neural networks and deep learning, leading to improved cybersecurity and business decisions.
Cloud-based speech recognition solutions offer real-time transcription capabilities, making them essential for industries like healthcare and education. The hybrid cloud model, which combines the benefits of both digital media and cybersecurity, is gaining popularity. Machine learning algorithms in cybersecurity help detect and respond to threats in real-time, ensuring data security. The increasing adoption of smart devices and IoT is driving the demand for cloud AI solutions, allowing seamless integration and sharing of data across connected devices. Thus, such factors are driving the growth of the market during the forecast period.
Growing 5G adoption and mobile penetration is the key trend in the market. Artificial Intelligence (AI) in the cloud has gained significant traction in various industries, driven by advancements in algorithms such as machine learning (ML) and deep learning. Human intelligence is being augmented through AI applications in speech recognition, diagnostics, and business decisions. In digital media, AI algorithms are used for content recommendation and personalization.
Cybersecurity also benefits from AI with threat detection and anomaly identification. Neural networks and deep learning enable advanced capabilities such as image and speech recognition. These technologies are transforming industries and enhancing human capabilities, making businesses more efficient and effective. Cloud AI is revolutionizing various sectors, from healthcare to finance, by providing access to powerful computing resources and advanced algorithms. Thus, such trends will shape the growth of the market during the forecast period.
Challenges from open-source platforms is the major challenge that affects the growth of the market. In today's digital age, cloud-based Artificial Intelligence (AI) solutions have gained significant traction due to their flexibility and cost-effectiveness. Open-source AI algorithms, such as machine learning (ML), deep learning, and neural networks, are widely used in various industries for speech recognition, diagnostics, cybersecurity, and business decisions. These open-source platforms offer several advantages over commercial software.
The availability of source code allows for continuous improvement through community collaboration, ensuring the identification and elimination of potential vulnerabilities. Furthermore, open-source AI tools are free, making them an attractive option for small and emerging enterprises with limited budgets. In the digital media sector, open-source AI algorithms are utilized for speech recognition, while in healthcare, they are employed for diagnostics. In cybersecurity, these algorithms aid in threat detection and response, and in business decisions, they provide valuable insights through predictive analytics. Hence, the above factors will impede the growth of the market during the forecast period.
The market forecasting report includes the adoption lifecycle of the market, covering from the innovator's stage to the laggard's stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.
Customer Landscape
Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Amazon.com Inc: The company offers Cloud AI products such as Amazon Polly, Amazon Transcribe, and Amazon SageMaker.
The market research and growth report also includes detailed analyses of the competitive landscape of the market and information about key companies, including:
Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
Artificial Intelligence (AI) in the cloud market is witnessing significant growth due to the integration of advanced algorithms such as machine learning (ML) and deep learning into various industries. These technologies enable speech recognition in digital media, diagnostics in healthcare, cybersecurity threat detection, and automation of business decisions. AI in the cloud also offers functionalities like predictive analytics for personalization and productivity, cost savings through IT infrastructure optimization, and dynamic cloud services for self-managing IT workloads. Hyperscale cloud platforms provide ML-based models and GPUs for enterprise datacenters, enabling AI tools to process large datasets and power applications like self-healing networks, virtualization, and public, private, and hybrid cloud solutions. The integration of AI into IT services, data analytics, human capital management, and business intelligence is revolutionizing the way organizations operate, streamlining workloads and automating repetitive tasks. Moreover, AI is being used for non-repetitive tasks such as threat detection, integration, and talent gap management in various sectors. AI-powered chatbots are transforming customer service in retail, while financial organizations are using AI for inventory management and lowering costs. The future of AI in the cloud market lies in the continuous development of generative AI, neural networks, and self-managing cloud services, enabling businesses to make informed decisions and stay competitive in the digital age.
Market Scope |
|
Report Coverage |
Details |
Page number |
149 |
Base year |
2023 |
Historic period |
2018 - 2022 |
Forecast period |
2024-2028 |
Growth momentum & CAGR |
Accelerate at a CAGR of 24.1% |
Market growth 2024-2028 |
USD 12.61 billion |
Market structure |
Fragmented |
YoY growth 2023-2024(%) |
19.1 |
Regional analysis |
North America, Europe, APAC, South America, and Middle East and Africa |
Performing market contribution |
North America at 50% |
Key countries |
US, China, UK, Germany, and Japan |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Key companies profiled |
Amazon.com Inc., AIBrain Inc., Alphabet Inc., Baidu Inc., Cisco Systems Inc., H2O.ai Inc., Informatica Inc., Infosys Ltd., Intel Corp., International Business Machines Corp., Microsoft Corp., Nuance Communications Inc., NVIDIA Corp., Oracle Corp., Salesforce Inc., SoundHound AI Inc., Verint Systems Inc., VMware Inc., Wipro Ltd., and ZTE Corp. |
Market dynamics |
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for forecast period |
Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
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1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Component
7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Opportunity/Restraints
10 Competitive Landscape
11 Competitive Analysis
12 Appendix
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