Cloud AI - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)

The Cloud AI Market size is estimated at USD 67.56 billion in 2024, and is expected to reach USD 274.54 billion by 2029, growing at a CAGR of 32.37% during the forecast period (2024-2029).

The COVID-19 pandemic caused several organizations to accelerate their migrations to public cloud solutions since cloud service elasticity could meet unexpected spikes in service demand. Migrations to the cloud considerably helped companies reinvent how they conduct their businesses during COVID-19. The requirement for AI services has grown, and many cloud providers offer AI services. As a result, the cloud market recorded more growth significantly in the healthcare segment last year. Cloud AI technology was being used considerably to fight COVID-19.

Key Highlights

• With the growing number of enterprises and competition among them, companies are rigorously trying to integrate artificial intelligence (AI) technology with their application, analytics, business, and services. Moreover, companies are engaged in reducing their operational costs to ascend profit margins, owing to which artificial over the cloud is becoming popular, which is, in turn, expected to fuel the market growth over the forecast period.
• The rising trend of multi-cloud functioning and the growing need for cloud-based intelligence services also increase the demand for AI cloud solutions. According to IBM, 98% of the organization's plan will adopt multi-cloud architectures by last year. Only 41% have a multi-cloud management strategy, and just 38% have procedures and tools to operate a multi-cloud environment. This is poised to create a massive opportunity for cloud AI services.
• The driving factors in the studied market include rising big data volume, increasing demand for virtual assistants, and growing adoption of cloud-based services and applications.
• According to Cisco Systems Inc, the volume of big data is poised to increase from 51 exabytes in 2016 to 403 exabytes in the last year, representing a growth rate of almost seven times. The volume is expected to increase gradually in the forecast period, increasing the impact of the driver in the forecast period as companies tend to adopt cloud AI solutions to arrive at insights from such data.
• The market for cloud computing platforms has benefited from the pandemic. Using cloud technologies has made it easier to do internet business as the economy slowly revives. The cloud is hastening the deployment of full-scale AI, which hastens the adoption of and spending on Cloud-AI.

Cloud Artificial Intelligence (AI) Market Trends

Growing Adoption of Cloud-based Service and Application

• The adoption of cloud AI in government agencies is driven by the enormous capabilities of the platform, which allows government bodies to scale massive jobs, including data mining, and can directly impact public challenges. Furthermore, the initial inhibitions for data privacy reasons to adopt cloud computing are being overcome and are expected to gain further traction.
• The deployment of cloud AI has matured in recent years with the emergence and steady acceptance of the cloud, artificial intelligence (AI), the Internet of Things (IoT), blockchain, and other new technologies. Several government agencies have leveraged the competition between three cloud service providers, Microsoft Azure, Amazon Web Services, and Google Cloud Platform, to provision large clusters of servers, implement Hadoop and data lakes and employ hundreds of data scientists.
• The exhaustive participation of companies has increased the awareness amongst governments across the world regarding the development of the cloud from being a location to store data to a set of capabilities in all of an organization's environments that can reduce costs and deliver innovation and flexibility.
• Companies like IBM have worked closely with agencies at various levels of government to advance the application of cloud, AI, blockchain, and other new technologies. IBM also introduced the Government Cloud Virtual Summit, where various government leaders addressed how cloud AI services can help respond to natural disasters and improve public safety after a cybersecurity breach.
• Machine learning models are trained, hosted, and used to make predictions and provide insights on cloud AI platforms like Google Cloud and AWS. Cloud computing can make wise decisions on its own if AI is implemented in it. The Google Cloud Platform (GCP), which encompasses infrastructure, data and analytics, and other services, is the main revenue source for Alphabet's Cloud business. Last year, Google Cloud had USD 19 billion as income which represents 7.5% of Google's overall earnings.

North America Holds Major Share

• North America is expected to dominate the global cloud AI market, owing to its status as one of the early adopters of the technology. The other factor is that most of the major players in the market are US-based. Cloud adoption among the regional end-user is also quite high. Hence, the investment in the studied market is too high. The region is also a key region dominating the global hybrid cloud and IaaS market.
• Market players operating in the region are investing in innovating additional and unique features to their offerings, mainly to gain a competitive advantage and expand their customer target base. This is also expected to bring advancement in the regional and global markets. This factor expands the market scope further.
• For instance, US-based SoundHound Inc. offers Houndify, an independent AI platform that enables developers and business owners to deploy a conversational interface anywhere to retain control of their brand and users while differentiating and innovating. The company recently added SoundHound music recognition technology to its Houndify voice AI platform. It also strategically partnered with Honda Motor Co. Ltd to accelerate development.
• As regional organizations increasingly migrate their processes and applications to the cloud, vendors operating in the market may have to offer next-level customer experience (CX), performance, and productivity to gain a competitive edge. Companies add intelligence to the available data by using a broadened set of analytics tools that incorporate technologies such as AI, machine learning (ML), augmented reality (AR), and big data.
• Also, the Government of Canada has a "cloud-first" strategy, whereby cloud services are identified and evaluated as the principal delivery option when initiating information technology investments, initiatives, strategies, and projects. The cloud is also expected to allow the Government of Canada to harness private-sector providers' innovation to make its information technology more agile.
• Cloud vendors are further strengthening the demand for AI by offering a number of services and tools that make it easier to develop, test, enhance, and operate AI systems without big upfront investments. These include hardware optimized for machine learning, APIs that automate speech recognition and text analysis, productivity-boosting automated machine learning modeling systems, and AI development workflow platforms.

Cloud Artificial Intelligence (AI) Industry Overview

The high market consolidation has increased the competition among prominent players such as Microsoft, IBM, Google, Amazon, etc. The other players are actively expanding their product portfolio and geographical presence to capture a significant market share. The players operating in this market are investing hugely in artificial intelligence-related technologies and innovating their products, leading them to gain a sustainable competitive advantage. Due to this, there is always high competition between players to innovate and introduce new products.

In October 2022, at Oracle CloudWorld, Nvidia and Oracle announced an expanded, multiyear agreement to support clients' accelerated adoption of artificial intelligence (AI). Through the partnership, Nvidia's entire accelerated computing stack will be made available to Oracle Cloud Infrastructure (OCI), including GPUs, systems, and software.

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