Global AI-Based Personalization Engines Market Size, Share & Industry Analysis Report By Component (Software, and Services), By Deployment (Cloud, and On-premises), By Application, By Technology, By End Use, By Regional Outlook and Forecast, 2025 - 2032

The Global AI-Based Personalization Engines Market size is estimated at $436.28 billion in 2025 and is expected to reach $618.58 billion by 2032, rising at a market growth of 5.1% CAGR during the forecast period (2025-2032). The projected growth of the market is justified by rising demand for tailored digital experiences across e-commerce, media, banking, and healthcare. Increasing adoption of AI, big data analytics, and cloud platforms enable real-time customer insights, driving higher engagement, conversion rates, and long-term enterprise investment in personalization technologies.

Key Highlights:

• The North America AI-Based Personalization Engines market dominated Global AI-Based Personalization Engines Market in 2024, accounting for a 35.92% revenue share in 2024.
• The U.S. AI-Based Personalization Engines market is projected to maintain its leadership in North America, reaching a market size of USD 1.47 billion by 2032.
• Among the End Use segments, the Retail & E-commerce segment dominated the global market, contributing a revenue share of 26.87% in 2024.
• In terms of Technology, Machine Learning & Deep Learning segments are expected to lead the global market, with a projected revenue share of 25.07% by 2032.
• Website Personalization emerged as the leading Application in 2024, capturing a 39.14% revenue share, and is projected to retain its dominance during the forecast period.
• The Cloud segment in Deployment is poised to grow at the market in 2032 with a market size of USD 3.88 billion and is projected to maintain its dominant position throughout the forecast period.

Growing assurance from consumers has transformed the AI-based personalization engines and evolved the advancements in digital data and AI technologies. As compared to the conventional ways comprises of rule-based or static segmentation methods modern personalization uses ML, deep learning and real-time data processing to provide predictive, dynamic and context-aware experiences at a personal scale. Starting from the initial predictive analytics and recommender systems, these engines regularly train from the user input to customized content, recommendations, and services in real time. Key technology providers like IBM and Salesforce have spurred this transformation by implanting AI-driven personalization into combined consumer data platforms, giving congruous and relatable engagement in various digital channels.

Standard personalization trends are very much focused on delivering experiences that adapt instantly to user context, operate seamlessly across multiple channels, and proactively anticipate user needs rather than simply responding to past behavior. What was once limited to commercial applications is now extending into public sector digital services, signaling that personalized digital experiences have become a baseline expectation for users everywhere. As competition intensifies, organizations are differentiating themselves through strong data integration, real-time AI decision-making, advanced predictive capabilities, and responsible data governance. With continued investment in these areas, AI-based personalization engines are evolving into core digital infrastructure, enabling organizations to deliver consistent, trusted, and highly tailored experiences across industries.

The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In June, 2025, SAP SE announced the partnership with Phenom, making its AI-driven Intelligent Talent Experience platform an SAP Endorsed App. Integrated with SAP SuccessFactors, it enables hyper-personalized hiring through automation, improving candidate engagement, recruiter efficiency, and application conversion rates while reducing time-to-hire and manual workflows across global enterprises. Additionally, In May, 2025, Salesforce, Inc. announced the partnership with Bouygues Telecom, an internet service provider to deploy Agentforce AI agents within its CRM, enhancing customer service through automation and personalization. Integrated with Data Cloud, the system enables 360-degree customer insights, streamlining operations and empowering advisors to focus on empathetic, high-value interactions that strengthen customer relationships.

Based on the Analysis presented in the KBV Cardinal matrix; Google LLC, Microsoft Corporation, Amazon Web Services, Inc. are the forerunners in the AI-Based Personalization Engines Market. Companies such as Oracle Corporation, Salesforce, Inc., and IBM Corporation are some of the key innovators in AI-Based Personalization Engines Market. In February, 2025, Google LLC announced the partnership with Glance, an AI company to launch generative AI-powered experiences on smartphone lock screens and ambient TV screens. Using Google’s Gemini and Imagen models, Glance will enable hyper-personalized content and commerce, transforming phones into AI-powered devices through its upcoming platform, "Glance AI," starting in the U.S. market.

COVID 19 Impact Analysis

The COVID-19 pandemic positively impacted on the AI-based personalization engines market as businesses accelerated digital transformation and shifted customer engagement to online channels. Lockdowns and mobility restrictions increased reliance on digital platforms, boosting demand for real-time, intelligent personalization. Growth in e-commerce, online media, and digital services strengthened adoption as companies sought to enhance user experience and conversion rates. Personalization engines became central to marketing and CRM strategies by enabling data-driven decision-making and targeted campaigns. Cloud-based AI personalization solutions gained traction due to scalability and cost efficiency. Remote work and distributed operations further supported their deployment. Overall, the pandemic reinforced the strategic importance of AI-driven personalization and supported long-term market growth. Thus, the COVID-19 pandemic had a positive impact on the market.

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above 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 to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.

End Use Outlook

Based on End Use, the AI-Based Personalization Engines Market is segmented into Retail & E-commerce, BFSI, IT & Telecom, Media & Entertainment, Healthcare, Travel & Hospitality, Education, Automotive, and Other End Use. The BFSI segment attained 15% revenue share in the market in 2024. The banking, financial services, and insurance sector leverages AI-based personalization engines to enhance customer engagement, service delivery, and relationship management. Personalization technologies enable financial institutions to analyze transaction behavior, financial goals, risk profiles, and interaction histories to tailor product recommendations, communication strategies, and digital experiences.

Application Outlook

Based on Application, the AI-Based Personalization Engines Market is segmented into Website Personalization, Display Ads Personalization, Social Media Personalization, Email Personalization, and Other Application. The Display Ads Personalization segment attained 24% revenue share in the market in 2024. Display ads personalization focuses on tailoring visual advertising content to specific audience segments or individual users across digital platforms. AI-based personalization engines analyze demographic data, online behavior, purchase patterns, and contextual signals to deliver targeted advertisements that align with user preferences and interests. This application enables advertisers to optimize ad relevance, messaging, and creative formats while minimizing wasted impressions.

Regional Outlook

Region-wise, the AI-Based Personalization Engines Market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment recorded 36% revenue share in the market in 2024. North America and Europe remain at the forefront of the AI-based personalization engines market, supported by well-established digital ecosystems and early adoption of advanced AI technologies. In North America, organizations across industries such as retail, BFSI, and media actively use real-time and predictive personalization to improve customer engagement and drive better conversion results. Europe follows closely, with steady adoption led by large enterprises and a strong focus on data privacy, regulatory compliance, and ethical AI, all of which significantly influence how personalization solutions are developed and deployed across the region.

Asia Pacific and LAMEA are gaining momentum as high-growth markets, driven by rising investments in digital platforms and AI-powered engagement solutions. Asia Pacific, with key contributions from countries such as China, India, and Japan, is experiencing rapid digital expansion, widespread mobile-first usage, and a growing e-commerce landscape that fuels demand for scalable personalization technologies. Meanwhile, LAMEA remains at an earlier stage of adoption but is steadily progressing as digital transformation initiatives across sectors like retail, banking, and government services increase, positioning the region as a promising long-term market for AI-based personalization engines.

Recent Strategies Deployed in the Market

• Jun-2025: Adobe, Inc. unveiled LLM Optimizer, an enterprise tool helping brands enhance visibility and engagement across AI-powered browsers and chat services. It tracks AI-driven traffic, benchmarks performance, and provides real-time, actionable content optimization recommendations. Integrated with Adobe Experience Manager, it supports marketers in adapting to rising consumer use of generative AI interfaces.
• May-2025: SAP SE unveiled new Business AI tools, expanding Joule’s capabilities, introducing AI agents, and enhancing Business Data Cloud features. These innovations aim to boost productivity, simplify cloud migration, and personalize enterprise processes, making AI more actionable and scalable across business functions
• May-2025: Salesforce, Inc. acquired Informatica, a software company to enhance its AI-driven data platform. The integration will combine Informatica’s cloud-native data management and governance with Salesforce’s AI capabilities, enabling smarter, secure, and scalable autonomous AI agents for personalized customer experiences across enterprises.
• May-2025: Salesforce, Inc. acquired Convergence.ai to enhance Agent force, its AI-powered CRM platform. This integration enables real-time customer intent analysis, personalized support, and automated workflows, transforming customer service. Agent force’s AI-driven features will improve agent productivity and customer experiences across industries, marking a significant step in AI-powered CRM innovation.
• Mar-2025: Amazon Web Services, Inc. unveiled “Interests,” a new generative AI feature that personalizes shopping by turning natural language prompts into relevant product suggestions. Using large language models, it offers tailored recommendations, restock alerts, and deal updates, enhancing user experience. Initially, it's available to select U.S. users via the Amazon app and mobile site.

List of Key Companies Profiled

• Amazon Web Services, Inc. (Amazon.com, Inc.)
• Google LLC
• IBM Corporation
• Microsoft Corporation
• Twilio Inc.
• Adobe, Inc.
• SAP SE
• Salesforce, Inc.
• Oracle Corporation
• Optimizely, Inc.

Global AI-Based Personalization Engines Market Report Segmentation

By Component

• Software
• Services

By Deployment

• Cloud
• On-premises

By Application

• Website Personalization
• Display Ads Personalization
• Social Media Personalization
• Email Personalization
• Other Application

By Technology

• Machine Learning & Deep Learning
• Hybrid Recommendation Systems
• Collaborative Filtering
• Content-Based Filtering
• Natural Language Processing (NLP)
• Other Technology

By End Use

• Retail & E-commerce
• BFSI
• IT & Telecom
• Media & Entertainment
• Healthcare
• Travel & Hospitality
• Education
• Automotive
• Other End Use

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

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