Cloud Computing Market Growth | Industry Analysis, Size & Forecast Report

Dataset updated: Jun 27, 2024

Dataset authored and provided by: Mordor Intelligence

License: https://www.mordorintelligence.com/privacy-policy

Time period covered: 2019 - 2029

Area covered: Global

Variables measured: CAGR, Market size, Market share analysis, Global trends, Industry forecast

Description: The Cloud Computing Market size is estimated at USD 0.68 trillion in 2024, and is expected to reach USD 1.44 trillion by 2029, growing at a CAGR of 16.40% during the forecast period (2024-2029).

Report Attribute

Quantitative Units: Revenue in USD Billion, Volumes in Units, Pricing in USD

Regions and Countries Covered:

Industry Segmentation Covered:

By Cloud Computing: IaaS, SaaS, PaaS

By End-User: IT and Telecom, BFSI, Retail and Consumer Goods, Manufacturing, Healthcare, Media and Entertainment

Market Players Covered: Amazon Web Services, Google LLC, Microsoft Corporation, Alibaba Cloud, and Salesforce

According to Cognitive Market Research, the global Artificial Intelligence in Retail market size is USD 4951.2 million in 2023and will expand at a compound annual growth rate (CAGR) of 39.50% from 2023 to 2030.

Enhanced customer personalization to provide viable market output
Demand for online remains higher in Artificial Intelligence in the Retail market.
The machine learning and deep learning category held the highest Artificial Intelligence in Retail market revenue share in 2023.
North American Artificial Intelligence In Retail will continue to lead, whereas the Asia-Pacific Artificial Intelligence In Retail market will experience the most substantial growth until 2030.

Market Dynamics of the Artificial Intelligence in the Retail Market

Key Drivers for Artificial Intelligence in Retail Market

Enhanced Customer Personalization to Provide Viable Market Output

A primary driver of Artificial Intelligence in the Retail market is the pursuit of enhanced customer personalization. A.I. algorithms analyze vast datasets of customer behaviors, preferences, and purchase history to deliver highly personalized shopping experiences. Retailers leverage this insight to offer tailored product recommendations, targeted marketing campaigns, and personalized promotions. The drive for superior customer personalization not only enhances customer satisfaction but also increases engagement and boosts sales. This focus on individualized interactions through A.I. applications is a key driver shaping the dynamic landscape of A.I. in the retail market.

January 2023 - Microsoft and digital start-up AiFi worked together to offer Smart Store Analytics. It is a cloud-based tracking solution that helps merchants with operational and shopper insights for intelligent, cashierless stores.

Source-techcrunch.com/2023/01/10/aifi-microsoft-smart-store-analytics/

Improved Operational Efficiency to Propel Market Growth

Another pivotal driver is the quest for improved operational efficiency within the retail sector. A.I. technologies streamline various aspects of retail operations, from inventory management and demand forecasting to supply chain optimization and cashier-less checkout systems. By automating routine tasks and leveraging predictive analytics, retailers can enhance efficiency, reduce costs, and minimize errors. The pursuit of improved operational efficiency is a key motivator for retailers to invest in AI solutions, enabling them to stay competitive, adapt to dynamic market conditions, and meet the evolving demands of modern consumers in the highly competitive artificial intelligence (AI) retail market.

January 2023 - The EY Retail Intelligence solution, which is based on Microsoft Cloud, was introduced by the Fintech business EY to give customers a safe and efficient shopping experience. In order to deliver insightful information, this solution makes use of Microsoft Cloud for Retail and its technologies, which include image recognition, analytics, and artificial intelligence (A.I.).

Source-www.ey.com/en_gl/news/2023/01/ey-announces-launch-of-retail-solution-that-builds-on-the-microsoft-cloud-to-help-achieve-seamless-consumer-shopping-experiences

Key Restraints for Artificial Intelligence in Retail Market

Data Security Concerns to Restrict Market Growth

A prominent restraint in Artificial Intelligence in the Retail market is the pervasive concern over data security. As retailers increasingly rely on A.I. to process vast amounts of customer data for personalized experiences, there is a growing apprehension regarding the protection of sensitive information. The potential for data breaches and cyberattacks poses a significant challenge, as retailers must navigate the delicate balance between utilizing customer data for AI-driven initiatives and safeguarding it against potential security threats. Addressing these concerns is crucial to building and maintaining consumer trust in A.I. applications within the retail sector.

Key Trends for Artificial Intelligence in Retail Market

Surge in Voice-Enabled Shopping Interfaces Reshaping Retail Experiences

Voice-enabled A.I. assistants such as Amazon Alexa and Google Assistant are revolutionizing the way consumers engage with retail platforms. Shoppers can now utilize voice commands to search, compare, and purchase products, thereby streamlining and accelerating the buying process. Retailers...

The OLAP (Online Analytical Processing) database systems market is experiencing robust growth, driven by the increasing need for advanced business intelligence and data analytics capabilities across diverse sectors. The market's expansion is fueled by several key factors. Firstly, the proliferation of big data necessitates efficient and scalable solutions for analyzing complex datasets, a strength of OLAP systems. Secondly, the growing adoption of cloud-based solutions is enabling organizations of all sizes to leverage these powerful tools without significant upfront investments. This shift towards cloud-based OLAP is further propelled by the desire for enhanced flexibility, scalability, and cost-effectiveness. Thirdly, the rising demand for real-time business intelligence and data-driven decision-making is significantly driving the market's growth trajectory. This necessitates faster query processing speeds and sophisticated analytical functionalities, which are core competencies of modern OLAP database systems. Finally, the increasing penetration of business analytics software into SMEs, coupled with the continued dominance of large enterprises adopting such systems, expands the market's addressable potential. While the market is flourishing, certain challenges remain. Data security and privacy concerns continue to be paramount, requiring robust security protocols and compliance with stringent regulations. The complexity associated with implementing and managing OLAP systems, particularly in large organizations, presents another hurdle. Furthermore, the ongoing evolution of analytical technologies, including the emergence of newer technologies like in-memory analytics, requires vendors to continuously innovate and adapt to remain competitive. Despite these challenges, the long-term growth outlook for the OLAP database systems market remains positive, driven by the unwavering demand for data-driven insights across a broad range of industries and applications. The diverse range of vendors, including both established players and innovative startups, underscores the market's dynamism and continuous evolution. We project continued strong growth throughout the forecast period, fueled by technological advancements and broadening adoption.

The Big Data Services market, valued at $32.51 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 27.81% from 2025 to 2033. This explosive growth is fueled by several key drivers. The increasing volume and variety of data generated across industries necessitate sophisticated solutions for storage, processing, and analysis. The rise of cloud computing provides scalable and cost-effective infrastructure for Big Data initiatives, further accelerating market expansion. Furthermore, the growing adoption of advanced analytics techniques, such as machine learning and artificial intelligence, is driving demand for Big Data services to extract valuable insights from complex datasets. This allows businesses to make more informed decisions, optimize operations, and gain a competitive edge. While data security and privacy concerns represent a potential restraint, the market's overall trajectory remains strongly positive. The market is segmented by service type (consulting, implementation, integration, managed services), deployment model (cloud, on-premise), organization size (small, medium, large), and industry vertical (BFSI, healthcare, retail, manufacturing). Key players like IBM, Microsoft, Oracle, and Amazon Web Services are fiercely competitive, investing heavily in research and development to maintain market leadership. The forecast period (2025-2033) anticipates continued high growth, driven by increasing digital transformation across sectors. Businesses are leveraging Big Data to personalize customer experiences, improve operational efficiency, and develop new revenue streams. The expansion into emerging economies will also contribute significantly to market expansion, as these regions adopt Big Data technologies at a rapid pace. However, the successful implementation of Big Data initiatives relies on skilled professionals. Addressing the talent gap through robust training and development programs will be crucial for sustaining this rapid growth. Competitive pricing strategies and the emergence of innovative service offerings will shape the competitive landscape. The market’s long-term outlook remains exceptionally strong, driven by technological advancements and the ever-increasing reliance on data-driven decision-making. Recent developments include: May 2023 : Microsoft has introduced Microsft fabric an softend-to-end, Unified Analytics Platform, which enables organisations to integrate all data and analytical tools they need, Where By making it possible for data and business professionals to unlock their potential, as well as lay the foundation for an era of Artificial Intelligence, fabric creates a single unified product that brings together technologies like Azure Data Factory, Azure Synapse Analytics, and Power BI., November 2022: Amazon Web Services, Inc. (AWS) released five new features in its database and analytics portfolios. These updates enable users to manage and analyze data at a petabyte scale more efficiently and quickly, simplifying the process for customers to operate the high-performance database and analytics workloads at scale., October 2022: Oracle introduced the Oracle Network Analytics Suite, which includes a new cloud-native portfolio of analytics tools. This suite enables operators to make more automated and informed decisions regarding the performance and stability of their entire 5G network core by combining network function data with machine learning and artificial intelligence.. Key drivers for this market are: Increasing Cloud Adoption And Rise In The Data Volume Generated, Increasing Demand For Improving Organization's Internal Efficiency; Growing Adoption of Private Cloud. Potential restraints include: Increasing Cloud Adoption And Rise In The Data Volume Generated, Increasing Demand For Improving Organization's Internal Efficiency; Growing Adoption of Private Cloud. Notable trends are: Growing Adoption of Private Cloud is Driving the Market.

According to Cognitive Market Research, the global Cloud Aimarket size is USD 55921.2 million in 2023 and will expand at a compound annual growth rate (CAGR) of 33.50% from 2023 to 2030.

North America held the major market of more than 40% of the global revenue with a market size of USD 22368.48 million in 2023 and will grow at a compound annual growth rate (CAGR) of 31.7% from 2023 to 2030
European market of more than 30% of the global revenue with a market size of USD 16776.36 million in 2023 and will grow at a compound annual growth rate (CAGR) of 32.0% from 2023 to 2030
Asia-Pacific held the fastest market of more than 23% of the global revenue with a market size of USD 12861.88 million in 2023 and will grow at a compound annual growth rate (CAGR) of 35.5% from 2023 to 2030.
Latin America market than 5% of the global revenue with a market size of USD 2796.06 million in 2023 and will grow at a compound annual growth rate (CAGR) of 32.9% from 2023 to 2030.
The Middle East and Africa market of more than 2.00% of the global revenue with a market size of USD 1118.42 million in 2023 and will grow at a compound annual growth rate (CAGR) of 33.2% from 2023 to 2030
The demand for Cloud AI is rising due to its scalability flexibility cost-efficiency, and accessibility.
Demand for Solution remains higher in the Cloud Aimarket.
The Healthcare & Life Sciences category held the highest Cloud AI market revenue share in 2023.

Digital Transformation Imperative to Provide Viable Market Output

The primary driver propelling the Cloud AI market is the imperative for digital transformation across industries. Organizations are increasingly leveraging cloud-based AI solutions to streamline operations, enhance customer experiences, and gain actionable insights from vast datasets. The scalability and flexibility offered by cloud platforms empower businesses to deploy and manage AI applications seamlessly, fostering innovation and efficiency. As companies prioritize modernization to stay competitive, the integration of AI on cloud infrastructure becomes instrumental in achieving strategic objectives, driving the growth of the Cloud AI market.

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.

(Source:www.oemupdate.com/automation/siemens-and-microsoft-partner-to-drive-cross-industry-ai-adoption/#:~:text=Microsoft%20and%20Siemens%20have%20partnered,generative%20AI%20to%20industries%20worldwide.)

Proliferation of Big Data to Propel Market Growth

The proliferation of big data serves as another key driver for the Cloud AI market. As businesses accumulate unprecedented volumes of data, cloud-based AI solutions emerge as indispensable tools for extracting meaningful insights and patterns. The scalability of cloud platforms allows organizations to process and analyze massive datasets efficiently. Cloud AI applications, such as machine learning and data analytics, enable businesses to derive actionable intelligence from this wealth of information. With the increasing recognition of data as a strategic asset, the demand for cloud-based AI solutions to harness and derive value from big data continues to fuel the expansion of the Cloud AI market.

Apr-2023: Microsoft came into collaboration with Epic, to utilize 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.

(Source:blogs.microsoft.com/blog/2023/08/22/microsoft-and-epic-expand-ai-collaboration-to-accelerate-generative-ais-impact-in-healthcare-addressing-the-industrys-most-pressing-needs/#:~:text=Epic%20and%20Microsoft's%20expanded%20collaboration,to%20SlicerDi)

Market Restraints of the Cloud AI

Data Security Concerns to Restrict Market Growth

One significant restraint in the Cloud AI market revolves around data security concerns. As organizations migrate sensitive data to cloud environments for AI processing, there is a heightened awareness and apprehension regarding the protection of this valuable information. Potential vulnerabilities, data breaches, and the risk of unauthorized access pose challenges, especially in industries with stringent privacy regulations. Add...

The OLAP (Online Analytical Processing) database systems market is experiencing robust growth, driven by the increasing demand for advanced business intelligence (BI) and data analytics capabilities across diverse industries. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $40 billion by 2033. This expansion is fueled by several key factors: the proliferation of big data, the growing adoption of cloud-based solutions offering scalability and cost-effectiveness, and the increasing need for real-time data analysis to support faster, more informed decision-making. Furthermore, the rising adoption of embedded analytics within various applications further contributes to market growth. Major players like Microsoft, Oracle, IBM, and SAP dominate the market, offering comprehensive solutions catering to diverse organizational needs. However, the market also sees a significant presence from specialized vendors offering niche functionalities and cloud-native solutions, fostering healthy competition and innovation. The market is segmented by deployment type (cloud, on-premise), organization size (small, medium, large), industry vertical (BFSI, healthcare, retail, manufacturing), and geographical region (North America, Europe, Asia Pacific, etc.). While data security and integration complexities present some restraints, the overall market outlook remains highly positive due to the ever-increasing reliance on data-driven strategies across all business domains. The competitive landscape is characterized by a blend of established players with comprehensive suites and emerging vendors focusing on specialized areas, such as specific industry verticals or advanced analytical techniques. The ongoing development of advanced analytical features like machine learning integration within OLAP systems is a major driver of market growth. The shift towards cloud-based deployments continues to accelerate, driven by the advantages of scalability, pay-as-you-go pricing models, and reduced infrastructure management overhead. The increasing demand for self-service BI tools that empower business users to perform their own analysis without requiring extensive technical expertise also contributes significantly to the market’s expansion. Regional variations in adoption rates exist, with North America and Europe currently holding larger market shares due to higher technological adoption and maturity. However, rapidly developing economies in the Asia-Pacific region are demonstrating significant growth potential, presenting lucrative opportunities for market participants.

The in-memory OLAP database market is experiencing robust growth, driven by the increasing need for real-time business intelligence and the proliferation of big data. The market's Compound Annual Growth Rate (CAGR) —let's conservatively estimate this at 15% based on industry trends in similar data analytics segments— indicates a significant expansion from its 2025 value. This growth is fueled by several key factors: the demand for faster query processing speeds enabling quicker, more informed decision-making; the rise of cloud-based deployments offering scalability and cost-effectiveness; and the increasing adoption of advanced analytics techniques requiring the speed and efficiency of in-memory processing. Major players like Altibase, IBM, Microsoft, Oracle, and SAP are heavily invested in this space, driving innovation and competition, which further accelerates market expansion. Segmentation within the market likely includes solutions tailored to specific industries (e.g., finance, healthcare) and deployment models (cloud, on-premise). While challenges like data security and integration complexities exist, the overall market trajectory points towards continued, significant growth. The forecast period (2025-2033) promises substantial opportunities for vendors capable of delivering robust, scalable, and secure in-memory OLAP solutions. The continued adoption of artificial intelligence (AI) and machine learning (ML) technologies will further fuel demand, as these applications heavily rely on rapid data processing. Companies are actively seeking solutions to improve operational efficiency, gain competitive advantages, and make real-time adjustments based on market dynamics. This translates into higher investment in advanced database technologies, making in-memory OLAP a crucial component of modern business intelligence strategies. Further market segmentation will likely emerge based on specific data volume handling capabilities and specialized analytical functions, leading to even greater market diversification in the coming years.

The Operational Database Management Systems (OPDBMS) software market is experiencing robust growth, driven by the increasing adoption of cloud computing, the rise of big data analytics, and the expanding need for real-time data processing across diverse industries. The market, estimated at $50 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $150 billion by 2033. This expansion is fueled by several key factors. Organizations are increasingly migrating their on-premise databases to cloud-based solutions offered by major players like Oracle, Microsoft, Amazon Web Services, and Google, attracted by the scalability, cost-efficiency, and enhanced security features these platforms provide. Furthermore, the surge in data volume necessitates advanced database technologies capable of handling real-time analytics and high-velocity data streams, further boosting demand for sophisticated OPDBMS solutions. The market is segmented by deployment (cloud, on-premise), database type (relational, NoSQL), and industry vertical (BFSI, healthcare, retail, etc.), each presenting unique growth opportunities. However, the market faces challenges such as the complexity of managing hybrid database environments, data security concerns, and the need for skilled professionals to implement and maintain these systems. Despite these restraints, the long-term outlook for the OPDBMS software market remains exceptionally positive, fueled by ongoing technological innovation and the persistent demand for efficient and scalable data management solutions. The competitive landscape is highly dynamic, with established players like Oracle and Microsoft competing alongside emerging cloud-native providers and specialized NoSQL database vendors. The market is characterized by strategic alliances, acquisitions, and the continuous development of new features and functionalities. The ongoing focus on improving database performance, security, and scalability is driving innovation within the sector. Companies are investing heavily in research and development to create more efficient, intelligent, and adaptable database management systems capable of meeting the ever-evolving needs of businesses. The geographical distribution of the market shows strong growth in North America and Europe, but Asia-Pacific is expected to witness the most significant expansion during the forecast period due to increased digitalization efforts and a growing number of technology-driven businesses in this region.

The Data Visualization Platform market is experiencing robust growth, driven by the increasing need for businesses to derive actionable insights from ever-expanding datasets. The market, estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $50 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of big data across various industries necessitates efficient tools for analysis and interpretation. Secondly, the rising adoption of cloud-based solutions and advanced analytics techniques, such as artificial intelligence and machine learning, is further boosting market growth. The Smart City Systems and Ultimate Digital Materialization Space applications are significant drivers, demanding sophisticated visualization capabilities for managing complex data streams and optimizing resource allocation. While data security concerns and the need for skilled professionals represent potential restraints, the overall market outlook remains positive, with significant opportunities for both established players and emerging market entrants. The market segmentation reveals a diverse landscape. Within application segments, Smart City Systems and Ultimate Digital Materialization Space lead the way, reflecting the growing importance of data-driven decision-making in urban planning and digital transformation initiatives. In terms of types, Flow Analysis and Mixed Data Analysis are currently dominant, however, Database Analysis is expected to experience significant growth due to the increasing volume and complexity of structured data. North America currently holds the largest market share, followed by Europe and Asia-Pacific. However, rapid technological advancements and increasing digitalization in emerging economies are expected to drive significant growth in Asia-Pacific and other regions over the forecast period. Key players, including Zoomdata, Tableau, JOS, Sisense, Periscope Data, Looker, Domo, and Microsoft, are constantly innovating to enhance their offerings and maintain a competitive edge in this rapidly evolving market. The competitive landscape is characterized by both intense competition and strategic partnerships, further fueling innovation and market expansion.

The advanced and predictive analytics market is experiencing robust growth, driven by the increasing adoption of big data technologies and the need for businesses across diverse sectors to gain actionable insights from complex datasets. The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% during the forecast period (2025-2033), reaching approximately $150 billion by 2033. This significant expansion is fueled by several key factors, including the escalating demand for improved decision-making, the proliferation of cloud-based analytics solutions offering enhanced scalability and cost-effectiveness, and the growing importance of data-driven strategies across industries. The Banking and Financial Services, Insurance, and Healthcare sectors are currently major contributors, leveraging advanced analytics for fraud detection, risk management, personalized customer experiences, and predictive maintenance. However, significant growth potential exists in other sectors like Retail (Consumer Goods) and Transportation and Logistics, as these industries increasingly adopt data-driven approaches to optimize operations, enhance supply chain management, and improve customer satisfaction. Technological advancements, such as the rise of artificial intelligence (AI) and machine learning (ML) algorithms, are further accelerating market growth. These technologies enable the development of sophisticated predictive models capable of identifying trends, patterns, and anomalies in large datasets, providing businesses with a competitive edge. Despite this growth, challenges remain, including concerns regarding data security and privacy, the need for skilled data scientists and analysts, and the complexities involved in implementing and integrating advanced analytics solutions into existing business processes. Furthermore, the high initial investment costs associated with adopting advanced analytics solutions can pose a barrier to entry for smaller businesses. Nevertheless, the long-term benefits of improved efficiency, enhanced decision-making, and increased profitability are driving sustained investment and market expansion across diverse geographical regions, with North America and Europe currently leading the market.