Retailers using artificial intelligence (AI) and machine learning (ML) technologies performed better than their competitors. Both in 2023 and 2024, retail companies using this kind of technologies saw a two-digit growth of their sales compared to the respective previous years. Similarly, their annual profit grew by roughly eight percent, outperforming retailers who did not use AI or ML solutions.

Global Artificial Intelligence in the Retail market is expected to hit USD 20.05 billion in 2026 and will grow to CAGR by 39% between 2020 and 2026. Digitalization in retail is much more than just linking objects. It's about turning data into observations that guide decisions that produce better market results.

Ai in Retail is Undergoing Significant Transformations With the Integration of Retail AI. Companies are Leveraging Artificial Intelligence in Retail To Enhance Strategies, Improve Outcomes, And Boost Online Customer Engagement. AI Retail Solutions Like Machine Learning and Deep Learning are Commonly Used, Providing A Personalized User Experience. AI for Retail, Including Computer Vision, Is Improving Customer Experience and Inventory Management. The Use of AI Retail Technology is Expected To Surge, With Investments in AI-Powered Retail Analytics Increasing.

This statistic shows the machine learning use cases in the retail industry worldwide as of 2019. During the survey period, 45 percent of respondents are deploying machine learning for customer engagement in their organizations.

Machine Learning Market size was valued at USD 10.24 Billion in 2024 and is projected to reach USD 200.08 Billion by 2031, growing at a CAGR of 10.9% from 2024 to 2031.

Key Market Drivers:

Increasing Data Volume and Complexity: The explosion of digital data is fueling ML adoption across industries. Organizations are leveraging ML to extract insights from vast, complex datasets. According to the European Commission, the volume of data globally is projected to grow from 33 zettabytes in 2018 to 175 zettabytes by 2025. For instance, on September 15, 2023, Google Cloud announced new ML-powered data analytics tools to help enterprises handle increasing data complexity.

Advancements in AI and Deep Learning Algorithms: Continuous improvements in AI algorithms are expanding ML capabilities. Deep learning breakthroughs are enabling more sophisticated applications. The U.S. National Science Foundation reported a 63% increase in AI research publications from 2017 to 2021. For instance, on August 24, 2023, DeepMind unveiled Graphcast, a new ML weather forecasting model achieving unprecedented accuracy.

America AI in the Retail Market is Segmented by Channel (Omnichannel, Brick and Mortar, Pure-play Online Retailers), Solution (Software (On-premise and Cloud) and Service), Application (Apparel and Footwear, Food and Grocery, Electronics and Home Appliances, Home Improvement, and Other Applications), and Technology (Machine Learning, Natural Language Processing, Chatbots, Image and Video Analytics, and Swarm Intelligence).

The global retail business management software market is projected to reach a value of $1,196.7 million by 2033, exhibiting a CAGR of 7.5% during the forecast period (2025-2033). The market growth is primarily driven by the increasing adoption of cloud-based solutions, rising need for real-time inventory management, and growing demand for data analytics to enhance customer experience. Key trends shaping the market include the integration of artificial intelligence (AI) and machine learning (ML) for advanced data analysis, the shift towards omnichannel retailing, and the increasing use of mobile devices for in-store operations. The North American region is expected to hold a significant market share due to the presence of a large number of retail businesses and a high adoption rate of technology. The Asia Pacific region is projected to witness the highest growth rate, driven by the rapidly expanding retail sector in countries such as China and India. Major players in the market include HotSchedules, Applied Predictive Technologies, BayBridgeDigital, and Computer Resource Center, among others. These companies are focusing on offering comprehensive solutions that meet the evolving needs of retail businesses, such as inventory management, customer relationship management (CRM), and point-of-sale (POS) systems.

The global retail analytics market, valued at $2769.9 million in 2025, is projected to experience robust growth, driven by the increasing adoption of data-driven decision-making within the retail sector. This expansion is fueled by several key factors. Firstly, the proliferation of big data from various sources, including point-of-sale systems, customer relationship management (CRM) platforms, and e-commerce websites, provides retailers with unprecedented insights into consumer behavior. Secondly, advancements in artificial intelligence (AI) and machine learning (ML) are enabling more sophisticated analytical techniques, leading to improved forecasting accuracy, personalized marketing campaigns, and optimized supply chain management. Finally, the rising demand for enhancing customer experience and operational efficiency is pushing retailers to invest heavily in retail analytics solutions. The market is segmented across various analytical domains, including finance, human resources, operations, merchandising, pricing, customer analytics, promotional planning, yield, and inventory analysis. Key players like IBM, Oracle, and SAP are at the forefront, offering comprehensive solutions, while specialized vendors cater to niche analytical needs. Geographical expansion is significant, with North America and Europe currently holding substantial market shares but with considerable growth potential in Asia-Pacific and other emerging economies due to increasing digitalization and retail infrastructure development. The forecast period (2025-2033) anticipates a continued high CAGR (8.6%), suggesting sustained market growth. However, the market faces challenges. Data security concerns, the complexity of implementing and integrating analytics solutions, and the need for skilled professionals to interpret and act upon insights present significant hurdles. Despite these restraints, the long-term outlook remains positive, as the ability of retail analytics to improve profitability, customer loyalty, and operational effectiveness will remain a critical competitive advantage for retailers of all sizes. The continued evolution of technologies like cloud computing and the Internet of Things (IoT) will further accelerate market growth by facilitating the collection, processing, and analysis of even larger datasets.

AI In Social Media Market size was valued at USD 2.07 Billion in 2023 and is anticipated to reach USD 13.46 Billion by 2031, growing at a CAGR of 29.04% from 2024 to 2031.

Global AI In Social Media Market Dynamics

The key market dynamics that are shaping the AI In Social Media Market include:

Key Market Drivers:
Growing Demand for Personalization: The need for personalized user experiences is driving the adoption of AI Over 65% of consumers report increased loyalty to brands that offer personalized content, highlighting the importance of tailored interactions in social media engagement.
Advancements in AI Technologies: Continuous improvements in artificial intelligence, particularly in natural language processing and machine learning, are enabling more effective sentiment analysis and content moderation, which are crucial for maintaining user engagement and safety.

The data-driven retail solutions market is experiencing robust growth, fueled by the increasing adoption of advanced analytics and the urgent need for retailers to enhance customer experiences and operational efficiency. The market, estimated at $15 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% through 2033, reaching approximately $50 billion. This expansion is driven primarily by the rising volume of consumer data generated through various touchpoints – e-commerce platforms, mobile apps, loyalty programs, and in-store interactions. Retailers leverage this data to personalize marketing campaigns, optimize pricing strategies, improve supply chain management, and predict future demand more accurately. The shift toward omnichannel retail strategies necessitates robust data analytics capabilities, further driving market growth. Large enterprises are currently the leading adopters, but small and medium-sized enterprises (SMEs) are increasingly investing in these solutions to compete effectively. The market is segmented by solution type (software, hardware, services), application (customer relationship management, inventory management, pricing optimization), and deployment mode (cloud, on-premises). Competitive landscape analysis shows a mix of established players like Oracle and Microsoft alongside emerging technology firms focusing on AI and machine learning for retail insights. The key restraints to market growth include concerns regarding data security and privacy, the high initial investment cost for implementing data-driven solutions, and the lack of skilled professionals proficient in data analytics and interpretation. However, these challenges are being addressed through advancements in data encryption and privacy-preserving technologies, alongside increasing investments in training and development programs to bridge the skills gap. Future growth will be shaped by the continued adoption of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to enhance predictive modeling, personalized recommendations, and real-time inventory management. Regional growth will be led by North America and Europe due to higher technological adoption and established retail infrastructure, but significant growth potential exists in Asia-Pacific driven by rapid e-commerce expansion and a burgeoning middle class.

Artificial Intelligence In Retail Market size was valued at USD 7.1 billion in 2021 and is poised to grow from USD 8.41 billion in 2022 to USD 45.74 billion by 2030, growing at a CAGR of 18.45% in the forecast period (2023-2030).

The Artificial Intelligence (AI) In Retail Market is projected to grow at 30.1% CAGR, reaching $44.43 Billion by 2029. Where is the industry heading next? Get the sample report now!

Artificial Intelligence & Advanced Machine Learning Market size valued $137.93 Bn in 2023 & expected to reach $1790.43 Bn by 2032, at CAGR 29.2% from 2024-2032.

Market Overview and Drivers: The global image recognition in retail market is anticipated to reach a value of USD XX million by 2033, exhibiting a CAGR of XX% from 2025 to 2033. The market is driven by the rising adoption of artificial intelligence (AI) and machine learning (ML) technologies, which enable retailers to enhance customer experience, optimize operations, and reduce costs. Additionally, the growing demand for personalized shopping experiences and the need for theft prevention are further contributing to the market growth. Segments and Regional Trends: The market is segmented into two types: on-premises and cloud-based, and three applications: security and surveillance, vision analytics, and others. Geographically, North America holds the largest market share due to the early adoption of technology and the presence of leading technology companies. However, the Asia Pacific region is expected to witness the highest growth rate, driven by the rapidly growing retail sector and increasing government initiatives to promote digitalization. Major players in the market include IBM, AWS, Google, Microsoft, Trax, Intelligence Retail, VistBasic, Snap2Insight, Intel, NVidia Corporation, NEC, DEDI LLC, and others. Image recognition technology is rapidly transforming the retail industry, empowering businesses to enhance customer experiences, streamline operations, and gain valuable insights. This report provides a comprehensive analysis of the Image Recognition in Retail market, highlighting key trends, drivers, challenges, and growth opportunities.

Market Overview: The global Applied AI in Retail & E-commerce Market is anticipated to reach USD 19942.01 million by 2033, exhibiting a remarkable CAGR of 30.86% during the forecast period of 2025-2033. This market is driven by the increasing adoption of AI technologies, particularly machine learning and natural language processing (NLP) for enhanced customer experiences, optimized supply chain management, and improved sales and marketing strategies. Segmentation and Trends: The Technology segment of the market is dominated by Machine Learning, followed by NLP, Computer Vision, Speech Recognition, and Predictive Analytics. Key applications include Customer Service & Support, Sales & Marketing, Supply Chain Management, Price Optimization, Payment Processing, and Product Search & Discovery. Deployment options include On-Premise and Cloud-Based. The Cloud-Based segment is expected to grow rapidly due to its flexibility, cost-effectiveness, and scalability. End-users are primarily Retailers, E-commerce Platforms, Consumer Goods Manufacturers, and Logistics & Supply Chain Companies. North America holds the largest market share due to early adoption of AI technologies and a mature e-commerce industry. However, the Asia Pacific region is projected to witness significant growth in the coming years due to rising internet penetration and increasing disposable income. Recent developments include: August 2023:The Singapore MIT-Alliance for Research and Technology (SMART), a research enterprise in Singapore, has launched a new interdisciplinary research group working on rise of artificial intelligence and other new technologies. , September 2023:Zomato, a leading online meal delivery service, has introduced ‘Zomato AI’, an interactive chatbot to make food ordering process more convenient & personalized.. Potential restraints include: . Collection & analysis of customer data for AI applications raise privacy concerns, . Restraint impact analysis. Notable trends are: Growing number of wholesalers are adopting cloud-native software is expected to drive market growth..

Artificial intelligence is used in retail companies around the world. In a 2023 survey carried out in the United States and the EMEA region, nearly 40 percent of retail directors stated they used artificial intelligence (AI), computer vision (CV), and machine vision (MV) for selected operations and departments. Another 35 percent of respondents reported to have already scaled up this type of technology, while 15 percent of surveyed retail directors projected that it would be implemented within the next 12 months.

In the United Kingdom, retailers are inevitably using Artificial Intelligence (AI) technologies to help with data and analytics in their business. The use of AI in e-commerce was also widely adopted at 83 percent, while 77 percent of UK retailers were deploying AI tech in customer services such as chatbots. From a supply chain perspective, AI was adopted only by half of the UK retailers surveyed in this study. 57 percent of retailers benefitted from AI in warehousing stock management area, while warehousing robotics and logistics were only adopted by less than half of retailers as of 2019.

Global Data Science Platform Market Size and Forecast

Global Data Science Platform Market size was valued at USD 101.34 Billion in 2024 and is projected to reach USD 739.07 Billion by 2031 growing at a CAGR of 31.10% from 2024 to 2031.

Global Data Science Platform Market Drivers

AI and Machine Learning Integration: As AI and machine learning technologies become more widely adopted, demand for data science platforms grows. The United States Bureau of Labour Statistics predicts a 36% increase in data scientist jobs between 2021 and 2031, underlining the growing need for advanced platforms to develop and scale intelligent applications.

Demand for Business Intelligence and Analytics: As firms rely more on data-driven decision-making, there is a greater need for advanced analytics and business intelligence capabilities. Data science platforms provide critical tools for these roles, resulting in market growth, as evidenced by a predicted CAGR of 27.6% from 2022 to 2027.

The global Retail Analytics Services market, valued at $4042.9 million in 2025, is poised for significant growth over the forecast period (2025-2033). While the provided CAGR is missing, a conservative estimate, considering the increasing adoption of data-driven strategies within the retail sector and advancements in analytics technologies, would place it between 10% and 15%. This growth is fueled by several key drivers. The increasing need for retailers to optimize pricing, enhance supply chain efficiency, and personalize customer experiences is driving the demand for sophisticated analytics solutions. The rise of e-commerce and omnichannel retailing further exacerbates the need for real-time data analysis and insights to understand consumer behavior and preferences across various touchpoints. Furthermore, the proliferation of big data and the development of advanced analytical tools, such as AI and machine learning, are enabling retailers to extract more valuable insights from their data, leading to improved decision-making and operational efficiency. Market segmentation reveals strong demand across both SMEs and large enterprises, with merchandising, pricing, and performance analysis being the most sought-after services. Leading players like IBM, Oracle, and Microsoft are shaping the market landscape through continuous innovation and strategic partnerships, while specialized analytics providers cater to niche needs. However, factors such as the high cost of implementation and the need for skilled personnel to manage and interpret complex analytics outputs could pose challenges to market expansion. The geographical distribution of the market shows a strong presence in North America and Europe, driven by the advanced retail infrastructure and high adoption of digital technologies. However, the Asia-Pacific region is expected to witness significant growth, fueled by rapid economic development and the expanding e-commerce sector in countries like China and India. The competitive landscape is characterized by a mix of large technology companies offering comprehensive solutions and specialized analytics providers focusing on specific retail segments. The future success of players in this market will depend on their ability to provide customized solutions tailored to specific retail needs, leverage cutting-edge technologies, and demonstrate a clear return on investment for their clients. Ongoing innovations in areas such as predictive analytics, customer journey mapping, and fraud detection will continue to shape market trends and propel the growth of the Retail Analytics Services sector.