PUBLISHER: The Business Research Company | PRODUCT CODE: 1994526
PUBLISHER: The Business Research Company | PRODUCT CODE: 1994526
Cold start recommendation artificial intelligence refers to methods used to provide relevant recommendations when historical user or item data is minimal or unavailable. These methods depend on alternative inputs such as demographic information, item characteristics, contextual signals, or hybrid recommendation frameworks. The technology enables the delivery of useful and accurate recommendations even in data-limited initial stages.
The primary components of cold start recommendation artificial intelligence include software, hardware, and services. Software refers to AI-driven systems that produce personalized recommendations for new users or items with minimal historical data by utilizing machine learning algorithms. These solutions are deployed through cloud-based, on-premises, hybrid cloud, and other models and are designed for small and medium enterprises as well as large enterprises. They are applied in industries such as e-commerce and retail, media and entertainment streaming, social media, travel and hospitality, and others, and serve retailers, online platforms, content providers, financial institutions, and additional end users.
Tariffs are impacting the cold start recommendation artificial intelligence market by increasing costs of imported high-performance computing hardware, GPUs, and advanced data processing infrastructure required for model training and deployment. Technology providers and digital platforms in North America and Europe are most affected due to dependence on imported semiconductor components, while Asia-Pacific faces pricing pressure on AI infrastructure exports. These tariffs are increasing operational costs and slowing large-scale deployment of recommendation systems. However, they are also encouraging cloud-based optimization, regional data center investments, and development of more compute-efficient recommendation algorithms.
The cold start recommendation artificial intelligence (AI) market research report is one of a series of new reports from The Business Research Company that provides cold start recommendation artificial intelligence (AI) market statistics, including cold start recommendation artificial intelligence (AI) industry global market size, regional shares, competitors with a cold start recommendation artificial intelligence (AI) market share, detailed cold start recommendation artificial intelligence (AI) market segments, market trends and opportunities, and any further data you may need to thrive in the cold start recommendation artificial intelligence (AI) industry. This cold start recommendation artificial intelligence (AI) 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 cold start recommendation artificial intelligence (AI) market size has grown exponentially in recent years. It will grow from $1.55 billion in 2025 to $1.98 billion in 2026 at a compound annual growth rate (CAGR) of 27.4%. The growth in the historic period can be attributed to growth of new digital platforms with limited user data, increasing reliance on personalization for user engagement, expansion of e-commerce and streaming platforms, early adoption of recommendation engines, rising availability of user attribute data.
The cold start recommendation artificial intelligence (AI) market size is expected to see exponential growth in the next few years. It will grow to $5.25 billion in 2030 at a compound annual growth rate (CAGR) of 27.7%. The growth in the forecast period can be attributed to increasing deployment of AI-driven personalization systems, growing demand for real-time recommendation accuracy, expansion of cross-platform data utilization, rising adoption of privacy-preserving recommendation models, increasing investments in advanced AI model optimization. Major trends in the forecast period include increasing adoption of hybrid recommendation models, rising use of context-aware onboarding techniques, growing integration of transfer learning across domains, expansion of user and item profiling solutions, enhanced focus on cold start performance optimization.
The increasing demand for personalized user experiences is expected to support the growth of the cold start recommendation artificial intelligence (AI) market going forward. Personalized user experiences involve customizing interactions, content, or recommendations based on individual user preferences and behavioral patterns. Demand for personalized user experiences is rising due to the widespread adoption of AI and data analytics that enable real-time insights into user behavior and preferences. Cold start recommendation AI enhances personalized user experiences by accurately generating relevant recommendations for new users who have limited historical interaction data. For example, in February 2025, according to SAP SE, a Germany-based software company, in 2024, 64% of U.S. consumers stated that AI improved their retail experiences, reflecting a 25% increase in positive sentiment compared to 2023. Therefore, the growing need for personalized user experiences is expected to drive the expansion of the cold start recommendation artificial intelligence (AI) market.
Leading companies operating in the cold start recommendation artificial intelligence (AI) market are focusing on deploying real-time, context-aware recommendation engines, such as semantic search and embedding-based recommendation models, to deliver relevant personalization for new users and new content without relying on historical interaction data. Context-aware recommendation engines are AI systems that generate personalized recommendations by using real-time contextual signals such as user intent, location, device, session behavior, and content attributes instead of relying solely on historical interaction data. For example, in November 2023, Google LLC, a US-based technology company, launched new Vertex AI Search capabilities for media and entertainment companies. The solution uses generative AI to understand video, audio, and text content, supports semantic search across large media catalogs, and delivers personalized content recommendations in data-sparse scenarios. These capabilities help media platforms improve viewer engagement and content discovery during onboarding, though recommendation accuracy may evolve as richer user interaction data accumulates.
In June 2025, OpenAI Inc., a US-based provider of advanced generative AI models and AI platform services, acquired the team from Crossing Minds for an undisclosed amount. With this acquisition, OpenAI aimed to strengthen its personalization and recommendation system capabilities, including improving cold-start recommendation performance by incorporating Crossing Minds' specialized expertise in AI-driven user intent understanding and recommendation technologies into its products and research initiatives. Crossing Minds Inc. is a US-based provider of AI-powered recommendation systems designed to analyze user behavior data and deliver personalized product suggestions for e-commerce and digital platforms.
Major companies operating in the cold start recommendation artificial intelligence (AI) market are Amazon Web Services Inc., Microsoft Corporation, Meta Platforms Inc., Alibaba Group Holding Limited, Tencent Holdings Limited, Accenture plc, International Business Machines Corporation (IBM), Oracle Corporation, SAP SE, Salesforce Inc., Adobe Inc., Databricks Inc., Outbrain Inc., Itransition Group, DataRobot Inc., Bloomreach Inc., Algolia SAS, Coveo Solutions Inc., H2O.AI Inc., DevCom Software Ltd., Qloo Inc., Algoscale Technologies Inc., Zactra Technologies Inc., Personyze Inc.
North America was the largest region in the cold start recommendation artificial intelligence (AI) market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the cold start recommendation artificial intelligence (AI) market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
The countries covered in the cold start recommendation artificial intelligence (AI) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
The cold start recommendation artificial intelligence (AI) consists of revenues earned by entities by providing solutions such as hybrid and context-aware recommendation design services, onboarding and preference elicitation services, similarity modeling and clustering services, transfer learning and cross-domain recommendation services, and model training and optimization services. The market value includes the value of related goods sold by the service provider or included within the service offering. The cold start recommendation artificial intelligence (AI) includes sales of knowledge-based recommendation tools, user and item profiling products, data enrichment and feature engineering tools, similarity modeling and clustering products, and transfer learning-based recommendation products. 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.
Cold Start Recommendation Artificial Intelligence (AI) Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.
This report focuses cold start recommendation artificial intelligence (AI) market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
Where is the largest and fastest growing market for cold start recommendation artificial intelligence (AI) ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The cold start recommendation artificial intelligence (AI) market global report from the Business Research Company answers all these questions and many more.
The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.
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