AI-Based Personalization Engines Market Size, Share & Trends Analysis Report By Component (Software, Services), By Application (Website Personalization, Display Ads Personalization), By Technology, By Deployment, By End Use, By Region, And Segment Forecasts, 2025 - 2033

AI-Based Personalization Engines Market Summary

Industries such as e-commerce, healthcare, and finance increasingly adopt these engines to improve customer engagement and conversion rates through personalized recommendations and dynamic pricing strategies. For instance, Shein uses artificial intelligence to personalize the shopping experience by analyzing customer data such as browsing history, purchase behavior, and real-time user interactions. These AI-driven insights enable the company to deliver tailored product recommendations, customized promotions, and dynamic pricing, thereby enhancing customer engagement and increasing conversion rates. The rise of digital platforms and omnichannel retail further amplifies demand, as companies prioritize seamless, customized interactions across websites, mobile apps, and social media.

Moreover, integrating AI personalization engines with emerging technologies like natural language processing and computer vision enhances their ability to predict and adapt to individual preferences more accurately. Businesses also focus on real-time data analytics and automated decision-making to optimize marketing campaigns and inventory management, addressing challenges such as overstocking or irrelevant content delivery. In addition, the competitive landscape drives organizations to differentiate their offerings by refining customer loyalty programs and hyper-targeted advertising, creating sustained demand for advanced personalization solutions.

In addition, regulatory frameworks, including data privacy laws such as GDPR, shape the market by requiring transparent and ethical use of consumer data. Compliance mandates encourage the development of secure, anonymized data-handling practices while maintaining personalization effectiveness. Simultaneously, expanding AI applications in travel, automotive, and entertainment sectors introduce new use cases for personalized experiences, ensuring continuous innovation and scalability. These factors sustain market growth, balancing technological advancement with evolving consumer expectations and regulatory requirements.

The increasing availability of big data and advancements in cloud computing infrastructure significantly contribute to the growth of AI-based personalization engines. Organizations leverage vast customer data from diverse touchpoints to train algorithms that deliver highly relevant and timely recommendations. Cloud platforms provide scalable computing power and storage, enabling real-time processing and deployment of personalization models without heavy upfront investments. Additionally, the rise of edge computing allows personalization engines to operate closer to the end-user, reducing latency and enhancing user experience.

Component Insights

The software segment led the market with a revenue share of over 60% of global revenue in 2024 due to its ability to offer scalable and flexible solutions that integrate easily with existing digital platforms. Software products enable businesses to deploy AI algorithms for customer segmentation, recommendation engines, and personalized content delivery without heavy upfront infrastructure investments. This accessibility drives widespread adoption across industries seeking to enhance user engagement and conversion rates. Additionally, software solutions often come with continuous updates and improvements, allowing companies to keep pace with evolving customer preferences and technological advancements without significant downtime or additional capital expenditure.

The services segment is predicted to experience significant growth in the forecast years as organizations increasingly require expert support to implement and optimize AI personalization engines. Services such as consulting, system integration, customization, and ongoing maintenance become essential to tailor solutions to specific business needs. This trend reflects the growing complexity of AI deployments and the demand for specialized knowledge to maximize return on investment. Furthermore, managed services and training offerings help companies overcome skill gaps and accelerate the adoption of AI-driven personalization, ensuring smoother transitions and higher operational efficiency.

Application Insights

The website personalization segment accounted for the largest revenue share in 2024 by enabling businesses to deliver dynamic content and product recommendations tailored to individual visitors. This approach enhances user experience and increases conversion rates by adapting website interfaces and offers based on real-time behavior and preferences. The effectiveness of website personalization in driving sales and customer loyalty sustains its market leadership. Moreover, advancements in AI allow for the integration of behavioral analytics and predictive modeling, enabling websites to anticipate user needs and present highly relevant content, further deepening customer engagement.

The display ads personalization segment is expected to grow at the highest CAGR during the forecast period as advertisers leverage AI to create targeted ad campaigns. AI engines optimize ad placements and messaging by analyzing user data and behavior patterns, improving relevance and engagement. This capability reduces advertising costs and increases campaign effectiveness, making it a preferred strategy for digital marketers. The rise of programmatic advertising platforms and real-time bidding further accelerates this growth by enabling automated and data-driven ad buying processes that maximize ROI.

Technology Insights

The machine learning and deep learning segment accounted for the largest revenue share in 2024 due to its ability to analyze vast amounts of data and uncover complex patterns that drive accurate personalization. These technologies enable continuous learning from user interactions, improving recommendation relevance over time. Deep learning models, in particular, excel at processing unstructured data such as images and text, enhancing the quality of personalized content. Their scalability and adaptability make them suitable for diverse applications across industries. As a result, businesses rely heavily on these advanced AI techniques to deliver tailored experiences that increase customer engagement and retention.

The hybrid recommendation systems segment is expected to grow at the highest CAGR over the forecast period, driven by combining the strengths of collaborative filtering and content-based filtering to provide more precise and relevant suggestions. This approach addresses limitations inherent in individual methods, such as the cold start problem and limited content scope. Hybrid systems comprehensively understand customer needs by integrating multiple data sources, including user behavior, preferences, and item attributes. Companies such as Netflix and Amazon successfully use hybrid models to enhance user satisfaction and drive sales. The increasing demand for accurate, context-aware recommendations fuels the adopting of hybrid systems across various sectors.

Deployment Insights

The cloud segment accounted for the prominent market revenue share in 2024 as cloud-based AI personalization engines offer advantages such as scalability, cost efficiency, and ease of integration. Cloud platforms allow businesses to process large volumes of data in real time and deploy updates quickly, supporting agile personalization strategies. This model suits companies of all sizes looking to leverage AI without heavy infrastructure costs. Furthermore, cloud services provide robust security features and compliance certifications, addressing concerns related to data privacy and regulatory requirements, which encourages broader adoption.

The on-premises segment is anticipated to grow significantly during the forecast period as organizations with stringent data security and compliance requirements seek greater control over their AI personalization systems. Industries such as banking, healthcare, and government prefer on-premises solutions to safeguard sensitive customer information and meet regulatory obligations. This demand drives investment in customizable, secure AI platforms. Additionally, on-premises setups allow for greater customization and integration with legacy systems, which is important for enterprises with complex IT environments or those operating in regions with limited cloud infrastructure.

End Use Insights

The retail & e-commerce segment accounted for the largest revenue share in 2024. This growth is driven by the extensive use of recommendation engines, personalized promotions, and dynamic pricing to boost sales. These sectors benefit from AI’s ability to analyze customer behavior and preferences, delivering tailored shopping experiences that increase customer satisfaction and loyalty. The continuous growth of online shopping fuels ongoing demand for personalization technologies. Moreover, integrating AI with mobile commerce and social media platforms enhances cross-channel personalization, enabling retailers to engage customers seamlessly across multiple touchpoints.

The healthcare segment is anticipated to grow at the highest CAGR during the forecast period as AI-powered personalization engines help providers deliver tailored patient experiences and improve care outcomes. Personalized recommendations assist in treatment planning, medication management, and wellness programs by analyzing complex patient data. The rise of digital health platforms and telemedicine increases the need for AI solutions that can adapt to individual health profiles. Patients today expect more customized interactions, making personalization essential for patient engagement and satisfaction. Healthcare organizations leverage AI to enhance service quality, optimize resource allocation, and support preventive care initiatives.

Regional Insights

North America AI-based personalization engines market dominated with a revenue share of over 30% in 2024, driven by advanced digital infrastructure, early adoption of AI technologies, and the presence of major technology companies. The region’s strong focus on innovation and customer experience encourages widespread implementation of AI personalization across various industries. Additionally, significant investments in AI research and development by the private and public sectors support continuous advancements in personalization technologies.

U.S. AI-Based Personalization Engines Market Trends

The U.S. AI-based personalization engines market is expected to grow significantly in 2024 as enterprises invest heavily in AI-driven personalization to improve omnichannel customer experiences. Retail, healthcare, and media sectors prioritize AI solutions to differentiate their offerings and meet evolving consumer expectations, supporting sustained market expansion. Furthermore, the U.S. benefits from a mature startup ecosystem and access to large volumes of consumer data, accelerating innovation and adoption of AI personalization engines.

Europe AI-Based Personalization Engines Market Trends

The AI-based personalization engines market in Europe is expected to grow significantly over the forecast period, driven by regulatory frameworks emphasizing data privacy and ethical AI use. Automotive, luxury retail, and financial services companies adopt AI personalization while ensuring compliance with GDPR and other standards, balancing innovation with consumer trust. The region also sees growing collaboration between industry and academia, promoting research that advances responsible AI personalization practices.

Asia Pacific AI-Based Personalization Engines Market Trends

The AI-based personalization engines market in the Asia Pacific region is anticipated to grow at the fastest CAGR over the forecast period due to rapid digital transformation, growing e-commerce penetration, and government initiatives promoting AI adoption. Emerging economies and tech startups actively deploy AI personalization engines to cater to diverse and expanding consumer bases, driving dynamic market growth. In addition, increasing smartphone penetration and internet accessibility fuel demand for personalized digital experiences, making the region a key focus for AI personalization providers.

Key AI-Based Personalization Engines Company Insights

Some key companies in the AI-based personalization engines industry are IBM Corporation, Google LLC, Amazon Web Services, Inc., and Microsoft.

• Amazon Web Services, Inc. is a cloud computing provider offering scalable infrastructure and AI-driven services that support advanced personalization solutions. Through its machine learning platform, Amazon Personalize, Amazon Web Services, Inc. enables businesses to build real-time, tailored user experiences across retail, media, and finance industries. The platform leverages user behavior and contextual data to deliver highly accurate recommendations. Amazon Web Services, Inc.'s extensive integration capabilities and global reach make it a key player in the AI-based personalization engine market.

• Microsoft provides a suite of AI and cloud-based tools through its Azure platform, empowering enterprises to implement intelligent personalization at scale. With services such as Azure Machine Learning and Azure Personalizer, the company supports dynamic content delivery and user experience optimization based on behavioral insights. Microsoft's focus on responsible AI and seamless integration with its ecosystem enhances its competitiveness in the AI-based personalization engine market.

Recent Developments

• In May 2025, CueZen, an AI-driven personalization platform for the healthcare sector, secured USD 5 million in a funding round led by Point72 Ventures, with additional support from Fortson VC, Pack VC, and Nextinfinity. This capital injection aims to accelerate the company's customer acquisition efforts and enhance its platform’s capabilities, enabling health enterprises to deliver more tailored digital experiences. CueZen’s technology leverages artificial intelligence to analyze user data and optimize personalized health interventions, addressing the growing demand for customized digital health solutions.

• In May 2025, Snowplow launched Snowplow Signals, a real-time customer intelligence platform designed to accelerate the development and deployment of AI-driven customer experiences. Snowplow Signals delivers applications with access to comprehensive, real-time, and reliable customer data, enabling enhanced hyper-personalization of user journeys. The platform also helps AI agents address the “cold start problem,” facilitating more relevant and effective customer interactions. This innovation represents a significant advancement in leveraging real-time data to optimize AI-powered engagement strategies.

• In May 2025, Hapbee Technologies, Inc., a company specializing in non-chemical, frequency-based wearable wellness technology, announced the release of its newly redesigned mobile application. The updated app incorporates an AI-powered discovery engine, introduces 13 new Vibes, and offers real-time, in-app customer support. These enhancements align with Hapbee Technologies, Inc.'s strategic focus on improving user experience, increasing personalization, and strengthening sustained customer engagement within the digital wellness sector.

 AI-Based Personalization Engines Market Report Scope

Global AI-Based Personalization Engines Market Report Segmentation

This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI-based personalization engines market report based on component, application, technology, deployment, end use, and region.

• Component Outlook (Revenue, USD Million, 2021 - 2033)

  • Software

  • Services

• Application Outlook (Revenue, USD Million, 2021 - 2033)

  • Website Personalization

  • Email Personalization

  • Display Ads Personalization

  • Social Media Personalization

  • Other

• Technology Outlook (Revenue, USD Million, 2021 - 2033)

  • Collaborative Filtering

  • Content-Based Filtering

  • Hybrid Recommendation Systems

  • Machine Learning and Deep Learning

  • Natural Language Processing (NLP)

  • Others

• Deployment Outlook (Revenue, USD Million, 2021 - 2033)

  • On-premises

  • Cloud

• End Use Outlook (Revenue, USD Million, 2021 - 2033)

  • BFSI

  • Media & Entertainment

  • Healthcare

  • IT & Telecom

  • Retail & E-commerce

  • Automotive

  • Travel & Hospitality

  • Education

  • Others

• Regional Outlook (Revenue, USD Million, 2021 - 2033)

  • North America

    • U.S.

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

  • Asia Pacific

    • China

    • Japan

    • India

    • South Korea

    • Australia

  • Latin America

    • Brazil

  • Middle East and Africa (MEA)

    • UAE

    • KSA

    • South Africa