AI-based Recommendation System Global Market Report 2024

The AI-based recommendation system market size has grown rapidly in recent years. It will grow from $2.01 billion in 2023 to $2.21 billion in 2024 at a compound annual growth rate (CAGR) of 10.1%. The expansion observed in the historical period can be attributed to several factors, including the rising demand for personalized recommendations, increased availability of data, the need for efficient workforce management solutions, growth in e-commerce activities, heightened demand for cross-selling and upselling strategies, as well as the application of recommendation systems in education and e-learning sectors.

The AI-based recommendation system market size is expected to see rapid growth in the next few years. It will grow to $3.28 billion in 2028 at a compound annual growth rate (CAGR) of 10.4%. The projected growth in the forecast period can be attributed to several key factors, including the increasing adoption of streaming services, the expanded integration of recommendation systems within healthcare practices, compliance with regulatory requirements, the growing scope of digital advertising, and the optimization of content delivery networks (CDNs). Major trends anticipated in the forecast period encompass the dominance of personalization strategies, real-time recommendation capabilities, adaptive learning models, multi-modal recommendation approaches, enhanced user feedback mechanisms, and the analysis of social influence.

The anticipated expansion of digital advertising is poised to drive the growth trajectory of the AI-based recommendation system market in the foreseeable future. Digital advertising encompasses promotional activities conducted through online platforms, spanning various media formats such as text, image, audio, and video across websites, streaming services, and other digital channels. This growth surge in digital advertising is attributed to its broad audience reach, precise targeting capabilities, measurable outcomes, cost-efficiency, and personalized approach. AI-based recommendation systems play a pivotal role in digital advertising by augmenting targeting precision, personalization, and overall campaign efficacy, thus fostering user engagement and conversion rates. For instance, Oracle Corporation, a leading US-based computer software company, projects a substantial increase in global digital advertising spending from $378 billion in 2020 to an estimated $646 billion by 2024, underscoring the driving force behind the expansion of the AI-based recommendation system market.

Prominent players in the AI-based recommendation system market are actively innovating technologies such as recommender system support to elevate the efficiency and efficacy of recommendation engines. These systems, powered by algorithms or software tools, analyze user data and preferences to generate tailored recommendations for products, services, content, or other items of interest. An illustration of such innovation is the January 2024 launch of recommender system support by Arthur, a US-based AI performance platform, heralding a significant advancement in AI technology. This novel technology aims to revolutionize the utilization of recommender systems in online businesses, elevating customer satisfaction levels and driving revenue growth. Leveraging AI capabilities, this solution enhances recommendation engines' accuracy and customization, featuring functionalities such as model overview page, metrics dashboard, data drift monitoring, advanced querying, and filtering, thereby enhancing the overall user experience through personalized recommendations.

In July 2021, Microsoft Corporation, a renowned US-based technology conglomerate, completed the acquisition of Suplari Inc. for an undisclosed sum. This strategic move by Microsoft is geared towards augmenting business insights for finance and procurement leaders through the integration of Suplari's AI-driven technology. Suplari Inc., based in the US, specializes in developing AI-based recommendation systems tailored for optimizing sourcing, forecasting, and risk management processes, aligning with Microsoft's objective to empower effective corporate spending analysis and management.

Major companies operating in the ai-based recommendation system market are Alphabet Inc, Microsoft Corporation, Alibaba Group Holding Limited (Alibaba), Meta Platforms Inc., Amazon Web Services, Huawei Technologies Co. Ltd, Tencent Holdings Limited, Intel Corporation, International Business Machines Corporation, Oracle Corp, SAP SE, Netflix, Hewlett Packard Enterprise (HPE), Salesforce Inc, Adobe Inc., Sentient Technologies, RecomTech, Kibo Commerce, SmartRecs, AIRecom, IntelliChoice, Unbxd Inc., Coveo Solutions Inc., Algonomy Software Pvt. Ltd., Recolize GmbH, Dynamic Yield Inc., IntelliSuggest, RecomAId, SuggestAI, AIAdvise.

North America was the largest region in the AI-based recommendation system market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the ai-based recommendation system market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The countries covered in the ai-based recommendation system market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

An AI-based recommendation system refers to a technology leveraging artificial intelligence (AI) algorithms and machine learning techniques to analyze extensive datasets, user preferences, and behavioral patterns. Its objective is to furnish personalized recommendations and suggestions to users. By tailoring suggestions to individual preferences, interests, and needs, these systems amplify user experiences, boost engagement, and elevate customer satisfaction levels across diverse industries and applications.

The primary types of AI-based recommendation systems include collaborative filtering, content-based filtering, and hybrid recommendation approaches. Collaborative filtering, a pivotal technique in recommendation systems, predicts a user's preference for an item by analyzing the preferences or behaviors of other users. Its deployments span across on-premise and cloud environments, with applications extending to diverse sectors such as e-commerce platforms, online education, social networking, finance, news and media, healthcare, among others.

The AI-based recommendation system market research report is one of a series of new reports that provides AI-based recommendation system market statistics, including AI-based recommendation system industry global market size, regional shares, competitors with a AI-based recommendation system market share, detailed AI-based recommendation system market segments, market trends and opportunities, and any further data you may need to thrive in the AI-based recommendation system industry. This AI-based recommendation system market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The AI-based recommendation system market consists of revenues earned by entities by providing services such as data collection, data preprocessing, machine learning models, algorithm training and tuning, feedback collection and analysis, monitoring, and maintenance. The market value includes the value of related goods sold by the service provider or included within the service offering. The AI-based recommendation system market also includes sales of data storage systems, data processing tools, user interfaces, feedback loops, ranking and filtering, and feature extraction. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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