Cloud AI Market Size, Share & Industry Trends Analysis Report By Type, By Industry, By Technology (Solution Deep Learning, Machine Learning, Natural Language Processing), By Regional Outlook and Forecast, 2023-2029

The Global Cloud AI Market size is expected to reach $395.8 billion by 2029, rising at a market growth of 38.4% CAGR during the forecast period.

Cloud AI combines the computing power of the cloud with AI algorithms to offer businesses advantages, including quicker processing, increased efficiency, and cost savings. The growing use of AI and machine learning technology by companies in various industries is one of the major factors driving the expansion of the market. As a result, organizations seek methods to use these technologies as they increase to gain a competitive advantage, and cloud AI offers a practical and scalable means of doing so.



AI and cloud computing are combined daily via digital assistants like Google Home, Siri, and Alexa from Amazon. The AI capabilities are employed in cloud computing to enhance business processes' strategic, effective, and insight-driven nature. Data and applications are presented in the cloud using cloud computing, giving enterprises greater agility and flexibility. Now that cloud computing and AI capabilities are integrated, businesses may find trends, manage their information, provide better customer experiences, and streamline workflows.

According to studies commissioned by one of the world's top providers of cloud services, cloud, and AI will be crucial and intertwined. More than three-quarters of the early adopters of the technology believe that AI is crucial to the success of their organizational strategy. Similarly, most early adopters agree that cloud services are crucial to AI endeavors. Most respondents choose Platform as a Service (PaaS) and Software as a Service (SaaS) to create and distribute AI solutions.

COVID-19 Impact Analysis

The need for artificial intelligence in the healthcare industry has grown significantly in response to the pandemic crisis issues. Numerous tools and models offered by the technology improve the capabilities of conventional analytics and decision-making. This enhances the precision and effectiveness of diagnosis, therapy, and forecasting. Additionally, throughout the outbreak, companies in the transportation, logistics, manufacturing, and retail sectors, among others, made large investments in technology to maintain a balance between supply and demand. As a result, the market grew significantly due to the outbreak, which is anticipated to continue following the crisis.

Market Growth Factors

Rising adoption of cloud-based applications and services

Since the advent and continuous use of the Internet of Things (IoT), cloud, blockchain, artificial intelligence (AI), and other cutting-edge technologies, the deployment of cloud AI has advanced. In order to deploy massive server clusters, deploy Hadoop and data lakes, and hire several data scientists, many government agencies have taken advantage of the competition among the three major cloud service providers. Governments worldwide are now more aware of the cloud's evolution from a place to store data to a set of capabilities that can lower costs and foster innovation and flexibility in all environments of an organization due to the extensive participation of businesses. This will further support the growth of the cloud AI market in the upcoming years.

Increased focus of AI data centers over parallel computing

Commercial servers widely embrace parallel computing as data mining, artificial intelligence, and virtual reality development. Due to their parallel architecture and countless cores that allow them to process several instructions at once, GPUs are well-suited for parallel computing. Furthermore, since artificial neural networks generally perform more effectively when run in parallel, the parallel computing approach is appropriate for implementing deep learning training and interface. During the anticipated period, it is anticipated that the market for cloud AI will rise due to the rising demand for parallel computing.

Market Restraining Factors

Challenges associated with open-source platforms

Due to the high costs associated with purchasing and licensing commercial software, many small and growing businesses use these platforms. In addition, software security is increased by spotting and fixing flaws that could go undetected when the source code is publicly accessible. Open-source platforms can also be easily tested before implementation, qualifying them for quick prototyping and experimentation. Some examples of open-source software include the DNS, Sendmail, and Apache servers, as well as HTML and Perl. Under the most demanding circumstances, these platforms have proven dependable and strong.

Technology Outlook

Based on technology, the cloud AI market is characterized into deep learning, machine learning, natural language processing, and others. In 2022, the deep learning segment held the highest revenue share in the cloud AI market. Predictive analytics and image & speech recognition are just two of the many applications deep learning is increasingly using. Data scientists and developers can build and train their neural networks using the deep learning platforms and technologies made accessible by cloud service providers. Deep-learning solutions will likely become more necessary as firms look to automate processes and derive insights from their data.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

Type Outlook

On the basis of type, the cloud AI market is classified into solution and services. In 2022, the solution segment witnessed the largest revenue share in the cloud AI market by cloud AI market. One of the main factors driving the market's growth is the rising accessibility of cloud-based AI solutions from key tech players like Microsoft, Amazon, and Google. These companies invest a lot of money in developing cloud AI platforms and offering them as a service to businesses of all sizes, making it easier for organizations to access and employ AI solutions without spending a lot of money on equipment and staff.

Vertical Outlook

By vertical, the cloud AI market is divided into healthcare, retail, BFSI, IT & telecommunication, government, manufacturing, automotive & transportation, and others. In 2022, the BFSI segment projected a prominent revenue share in the cloud AI market 2022. Artificial intelligence will likely be used in the sector for various risk management applications, including asset & liability management (ALM), credit risk, liquidity risk, and market risk analysis. The increasing use of this technology in the BFSI sector to identify fraud, make trading decisions, use credit scoring software, analyze the effects of financial markets, and manage risk, among other things, is predicted to accelerate the expansion of the Cloud AI market.

Regional Outlook

Region wise, the cloud AI market is analyzed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region led the cloud AI market by generating the largest revenue share. Businesses across various industries that use AI and machine learning are responsible for the region's rapid growth. It encompasses sectors adopting AI to increase operational effectiveness, cut costs, and spur innovation, such as healthcare, banking, and retail. A sizable and highly skilled labor force in North America is well-suited to create and execute AI solutions. Numerous colleges and research centers in North America are at the cutting edge of AI R&D, turning out a regular stream of gifted people who drive commercial innovation.

The Cardinal Matrix - Cloud AI Market Competition Analysis

The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation, Apple, Inc., and Google, LLC is the major forerunner in the Cloud AI Market. Companies such as IBM Corporation, NVIDIA Corporation, Oracle Corporation are some of the key innovators in Cloud AI Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Apple, Inc., Google LLC (Alphabet, Inc.), IBM Corporation, Intel Corporation, Microsoft Corporation, Oracle Corporation, MicroStrategy, Inc., NVIDIA Corporation, Salesforce, Inc. and QlikTech International AB.

Recent Strategies Deployed in Cloud AI Market

Partnerships, Collaborations and Agreements:

• Apr-2023: IBM came into an agreement with Moderna, Inc., a biotechnology company that pioneered messenger RNA therapeutics and vaccines. Under this agreement, Moderna would explore next-generation technologies comprising artificial intelligence and quantum computing for advancing and accelerating mRNA research and science. In addition, Moderna would be able to take advantage of multi-year research efforts in generative AI for therapeutics that help scientists better understand how molecules behave and facilitate the creation of new ones.
• Apr-2023: Microsoft partnered with Siemens Digital Industries Software for advanced generative artificial intelligence to enable industrial companies in driving efficiency and innovation throughout the engineering, designing, manufacturing, and operational lifecycle of products. Following the partnership, the companies are combining Siemens' Teamcenter product lifecycle management (PLM) software with Microsoft Teams, the language models in Azure OpenAI Service, and other Azure AI features to improve cross-functional collaboration. The incorporation of AI into technological platforms will fundamentally alter how we work and how every company conducts business.
• Apr-2023: Microsoft came into collaboration with Epic, for utilizing the power of generative artificial intelligence to enhance the efficiency and accuracy of EHRs. The collaboration enabled the deployment of Epic systems on the Azure cloud infrastructure. EHRs can be made more comprehensive, accurate, and user-friendly by utilizing AI algorithms to automatically fill in any information that is missing, freeing up doctors to concentrate on patient care.
• Mar-2023: NVIDIA announced that Google Cloud incorporates the released L4 GPU and Vertex AI to speed up the work of companies developing a growing number of generative AI applications. The G2 virtual machines made available in private preview by Google Cloud made it the first cloud service provider to provide NVIDIA's L4 Tensor Core GPU. Additionally, Vertex AI, which currently supports developing, tuning, and deploying sizable generative AI models, will include optimized support for L4 GPUs.
• Mar-2023: NVIDIA extended its collaboration with Oracle for including running strategic NVIDIA AI applications on the new Oracle Cloud Infrastructure (OCI) Supercluster. As the first hyper-scale cloud service provider, NVIDIA has chosen OCI to provide NVIDIA DGX CloudTM, an AI supercomputing service, at a significant scale. Additionally, NVIDIA is operating NVIDIA AI Foundations on OCI, one of its brand-new generative AI cloud services that are accessible through DGX Cloud. OCI is the first platform to make an AI supercomputer available at scale to tens of thousands of users across all sectors. This is a crucial skill as an increasing number of businesses need computational power for their particular AI use cases.
• Mar-2023: NVIDIA partnered with Adobe, a computer software company, for unlocking the power of generative AI for further advancing creative workflows. Together, the companies would develop a new generation of advanced generative AI models with a focus on deep integration into applications used by leading marketers and creators.
• Mar-2023: Microsoft teamed up with Teradata, following which the latter company combined Teradata VantageCloud, a cloud analytics and data platform, with Microsoft Azure Machine Learning. With Azure ML's capacity to streamline and expedite the ML lifecycle, along with VantageCloud's scalability, openness, and analytics platform, ClearScape Analytics, users may be able to fully realize the value of their data even in the most complex and demanding scenarios.
• Jan-2023: Microsoft extended its partnership with Persistent Systems for the next phase of its growth. The partnership would allow both companies to develop additional capabilities for a world that is cloud-native and AI-first. Persistent set up of a business unit focused on Microsoft Azure. There are more than 3,000 Azure and Microsoft certifications, as well as 50 patents and assets, in this partnership. Persistent would make use of the powerful analytics built inside the Microsoft Viva platform to improve the employee experience. The Viva platform would change how Persistent understands and interacts with its employees in real-time given the flexible work arrangements made possible by the pandemic. By mapping important organizational KPIs, the platform will also offer predictive insights and equip every employee with what they need to succeed.
• Jan-2023: IBM teamed up with Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) for launching an AI Center of Excellence. The center would advance collaboration for improving the adoption of AI technology and helping drive sustainability. In addition, the center aims to develop carbon-neutral solutions to combat climate change, existing energy solutions, and further natural language processing (NLP) for Arabic dialects.
• Dec-2022: NVIDIA announced a partnership with Deutsche Bank for increasing the utilization of machine learning and artificial intelligence in the financial services sector. The development of a wide variety of AI-powered services that adhere to regulatory requirements has been hastened by combining Deutsche Bank's knowledge of the financial sector with NVIDIA's leadership in AI and accelerated computing. By integrating AI and ML to streamline and expedite cloud migration choices, for instance, the partnership enhanced Deutsche Bank's journey toward cloud transformation.
• Dec-2022: Intel and SAP announced its collaboration with UST, a provider of digital transformation solutions. Under this collaboration, UST would assess and enable the Industry 4.0 digital transformation journey for SMEs in northern Malaysia. The collaboration will hasten the conversion of neighborhood businesses into "intelligent enterprises," enabling them to offer Industry 4.0 experiences that are streamlined and automated and essential for success in a contemporary economy that is focused on growth.
• Nov-2022: Intel came into collaboration with Deci, a deep learning company, for accelerating the journey towards more scalable AI. The companies further optimize deep learning inference by fusing Intel processor technology with Deci's proprietary Automated Neural Architecture Construction (AutoNAC) technology. This allows developers everywhere to build, optimize, and deploy more precise, quick, and efficient models for the edge, data center, and cloud. Together, Deci and Intel are taking important strides towards allowing ground-breaking deep learning inference on CPUs, a departure from the norm because GPUs have typically been the go-to computing platform for AI activities.
• Nov-2022: Google Cloud came into partnership with Hartford HealthCare for advancing the health system's digital transformation, enhance care delivery, and improve data analytics. Together, the companies would open up the potential of the latter company's patient data that is difficult to utilize and access because it is unstructured or hard to find in rising complex EHRs. For solving this challenge, Hartford would utilize Google Cloud's Healthcare Data Engine and HDE accelerators that use AI and ML for making healthcare data more actionable and accessible.
• Aug-2022: Intel collaborated with Aible for helping teams across industries to utilize artificial intelligence and provide fast and measurable business impact. This collaboration includes engineering improvements and a ground-breaking benchmarking program that improves Aible's capacity to provide its industrial clients with quick outcomes. Aible's technology offers a serverless-first approach when combined with Intel CPUs, enabling developers to create and execute applications without having to manage servers and to create modern applications with enhanced agility and lower total cost of ownership (TCO).
• Jul-2022: Google Cloud came into collaboration with Vodafone for introducing an Artificial Intelligence platform developed for enabling the next-generation of AI use cases, comprising optimizing customer experiences, product recommendations, and customer loyalty. The AI Booster Platform, which was in development for 18 months, would embed more AI and ML technologies into the company's overall operations.
• May-2022: Oracle PartnerNework has been joined by Temenos, a cloud banking platform following which Temenos Explainable AI (XAI) would be offered on Oracle Cloud Infrastructure. The partnership enabled Temenos' robust Explainable AI and machine learning capabilities to be deployed via Oracle Cloud Marketplace for Oracle's international clients, including financial services organizations globally. Temenos XAI uses cutting-edge innovation to deliver transparency, assisting companies in explaining to consumers and authorities in plain language how AI-based decisions are made.

Product Launches and Product Expansions:

• Apr-2023: Microsoft announced the expansion of its Copilot artificial intelligence suite to its Viva suite of employee engagement tools. The company would also introduce its Viva Glint employee engagement data aggregator tool. With Copilot, Microsoft Viva accelerates this new performance equation where engagement and productivity work together to improve company outcomes and success.
• Mar-2023: NVIDIA launched a set of cloud services for accelerating the enterprise adoption of generative AI. The set of cloud services would allow businesses to refine, build, and operate custom large language models and generative AI models, trained with their properties data created for unique domain-specific tasks. Using the NVIDIA NeMoTM language service and the NVIDIA Picasso image, video, and 3D service, businesses may create custom, domain-specific, generative AI apps for intelligent chat and customer assistance, expert content production, digital simulation, and other uses. Separately, NVIDIA unveiled new models for its biology-focused NVIDIA BioNeMoTM cloud service.
• Mar-2023: NVIDIA unveiled NVIDIA DGX Cloud, an AI supercomputing service, which offers immediate access to software and infrastructure to enterprises that require advanced models for generative AI and other groundbreaking applications for training. NVIDIA DGX AI supercomputing clusters with NVIDIA AI software are made available through DGX Cloud. The service eliminates the difficulty of purchasing, building, and managing on-premises technology by enabling every business to access its own AI supercomputer using a straightforward online browser.
• Mar-2023: Salesforce announced the launch of Generative AI for CRM for Einstein GPT. The system would be able to produce code, write emails, and compose customer service replies. Additionally, it enables ChatGPT's compatibility with Salesforce's Slack.
• Mar-2023: Google announced the launch of new features for deepening its focus into generative AI. The features would help users in creating text in Docs and Gmail utilizing its AI technology. Google is testing AI products and would make them accessible to a limited number of Workspace users that comprises Google's productivity tools and Gmail.
• Oct-2022: Google Cloud launched Medical Imaging Suite, the new technology that can help with interoperability and accessibility of radiology and other imaging data. The new portfolio comprises components focused on lab, storage, dashboards, datasets, and AI pipelines for imaging. It is designed for providing flexible options for on-prem, cloud, or edge deployment for enabling organizations to fulfill diverse data security, sovereignty, and privacy requirements while delivering policy enforcement and centralized management with Google Distributed Cloud, enabled by Anthos.
• Oct-2022: IBM expanded its embeddable AI software portfolio by launching three new libraries, created for helping IBM Ecosystem partners, developers, and clients more quickly, easily, and cost-effectively build their AI-powered solutions and bring them to market. The AI libraries have been created in IBM Research and designed for offering an easily scalable way of building speech-to-text, natural language processing, and text-to-speech capabilities into applications across multi and hybrid cloud environments, to independent software vendors throughout industries.

Acquisitions and Mergers:

• Mar-2023: Apple took over WaveOne, a startup engaged in developing AI algorithms for video compression. Apple added WaveOne to its technology portfolio and the AI-powered video codec enabled Apple to provide more efficient streaming on its services such as Apple TV+.
• Jan-2023: Qlik is acquiring Talend, a company focused on data integration and data integrity. Qlik and Talend offer comprehensive and complementary capabilities because of their market-leading solutions in real-time data and application interaction, data governance, data quality, transformation, analytics, artificial intelligence, and machine learning. The productivity of both data environments and data personnel would rise, giving customers access to a greater selection of solutions. This will encourage the strategic use of data and help businesses get over organizational data challenges.
• Dec-2022: Oracle announced the acquisition of Newmetrix, a cloud-based platform that leverages AI for highlighting construction problems focused on project safety. The acquisition added some important technologies and use some intellectual property that extended and expanded the company's Construction Intelligence Cloud. In addition, it helped the company to enhance its capabilities in utilizing AI and ML for creating more predictive behavior.

Scope of the Study

By Type

• Solution
• Services

By Industry

• IT & Telecom
• Government
• Manufacturing
• BFSI
• Automotive & Transportation
• Healthcare & Life Sciences
• Retail
• Others

By Technology

• Deep Learning
• Machine Learning
• Natural Language Processing
• Others

By Geography

• North America
• US
• Canada
• Mexico
• Rest of North America

• Europe
• Germany
• UK
• France
• Russia
• Spain
• Italy
• Rest of Europe

• Asia Pacific
• China
• Japan
• India
• South Korea
• Singapore
• Malaysia
• Rest of Asia Pacific

• LAMEA
• Brazil
• Argentina
• UAE
• Saudi Arabia
• South Africa
• Nigeria
• Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

• Apple, Inc.
• Google LLC (Alphabet, Inc.)
• IBM Corporation
• Intel Corporation
• Microsoft Corporation
• Oracle Corporation
• MicroStrategy, Inc.
• NVIDIA Corporation
• Salesforce, Inc.
• QlikTech International AB

Unique Offerings

• Exhaustive coverage
• The highest number of Market tables and figures
• Subscription-based model available
• Guaranteed best price
• Assured post sales research support with 10% customization free