Artificial Intelligence (AI)-Driven Product Recall Prediction Market Report 2025

The artificial intelligence (AI)-driven product recall prediction market size has grown rapidly in recent years. It will grow from $1.36 billion in 2024 to $1.71 billion in 2025 at a compound annual growth rate (CAGR) of 25.3%. The growth during the historical period can be credited to several factors, including the globalization of supply chains, stricter safety compliance demands, heightened consumer awareness regarding product safety, increased digitization within manufacturing processes, and a growing number of product recalls.

The artificial intelligence (AI)-driven product recall prediction market size is expected to see rapid growth in the next few years. It will grow to $4.16 billion in 2029 at a compound annual growth rate (CAGR) of 25%. The projected growth in the forecast period can be attributed to heightened regulatory pressures, increasing product complexity, a growing need for real-time traceability, wider adoption of cloud-based solutions, and rising investments in AI-driven risk prediction. Key trends expected during this period include progress in machine learning algorithms, the integration of cloud platforms, expanded technology use in the pharmaceutical sector, advancements in AI-powered analytics, and improvements in predictive maintenance techniques.

The increasing adoption of automation in supply chain management is anticipated to drive growth in the AI-driven product recall prediction market. Automation involves utilizing technology and systems to streamline, oversee, and manage supply chain processes with limited human input, thereby enhancing accuracy and efficiency. As companies aim to minimize errors and improve the handling of inventory and order fulfillment, the need for automation continues to grow. AI-powered product recall prediction supports these efforts by detecting potential product issues early, enabling quicker recall actions, reducing financial losses, and promoting smoother operations. For example, in July 2025, Orange Connex, a U.S.-based technology-enabled fourth-party logistics provider, reported that AI-driven predictive analytics could lower forecasting errors by 50% and reduce operational expenses by 20-30%, with 47% of mid-sized firms already implementing AI to enhance their workflows. As a result, the growing reliance on automation in supply chain operations is contributing to the expansion of the AI-driven product recall prediction market.

Growing investments in digital technologies are expected to support the expansion of the AI-driven product recall prediction market. These investments involve allocating resources toward hardware, software, connectivity, and services designed to strengthen digital capabilities, foster innovation, and boost operational efficiency. As more businesses adopt advanced tools such as AI and analytics to streamline operations and enhance performance, spending on digital technologies continues to rise. Such investments provide the essential data infrastructure and analytical tools that allow AI systems to identify and predict potential product defects in real time. For example, in July 2024, the UK’s Office for National Statistics reported that annual investment in digital infrastructure reached \$12.46 billion USD (£9.2 billion) in 2022, marking a 22.9% increase over the previous year. This upward trend in digital technology investment is therefore playing a key role in driving growth in the AI-driven product recall prediction market.

Leading companies in the AI-driven product recall prediction market are prioritizing the development of innovative tools, such as AI-powered predictive quality analytics, to improve product safety, lower operational risks, and reduce the costs associated with recalls. These solutions utilize artificial intelligence to analyze data and forecast potential product defects, allowing organizations to take preventive measures and maintain quality standards. For example, in October 2024, ETQ LLC, a U.S.-based provider of cloud-native quality management software, introduced the ETQ Reliance predictive quality analytics solution. Developed in collaboration with Acerta Analytics Solutions, this AI-enhanced tool integrates with ETQ’s quality management system (QMS) and uses machine learning along with real-time manufacturing data to identify and address defects early in the production process. It automates alerts for quality risks, speeds up root cause analysis, and supports proactive issue resolution. By combining AI capabilities with human decision-making, the solution helps decrease scrap, rework, and recall incidents while enhancing product quality and operational performance.

Major players in the artificial intelligence (ai)-driven product recall prediction market are Amazon Web Services Inc., Siemens AG, Honeywell International Inc., PTC Inc., Elisa Industriq Oy, DataRobot Inc., Dataiku Ltd., ETQ Inc., Augury Services Private Limited, Uptake Technologies Inc., Sight Machine Inc., LandingAI Inc., MachineMetrics Inc., Falkonry Inc., TrendMiner NV, Agroknow S.A., Acerta Analytics Solutions Inc., Predictronics Corporation, Smarteeva Ltd., QualityLine Production Technologies Ltd.

North America was the largest region in the artificial intelligence (AI)-driven product recall prediction market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence (AI)-driven product recall prediction report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the artificial intelligence (AI)-driven product recall prediction market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the information technology sector, particularly in hardware manufacturing, data infrastructure, and software deployment. Higher duties on imported semiconductors, circuit boards, and networking equipment have raised production and operational costs for tech firms, cloud service providers, and data centers. Companies relying on globally sourced components for laptops, servers, and consumer electronics are facing longer lead times and increased pricing pressures. In parallel, tariffs on specialized software tools and retaliatory measures from key international markets have disrupted global IT supply chains and reduced overseas demand for U.S.-developed technologies. To navigate these challenges, the sector is accelerating investments in domestic chip fabrication, diversifying supplier bases, and adopting AI-driven automation to enhance operational resilience and cost efficiency.

AI-powered product recall prediction involves leveraging artificial intelligence algorithms and machine learning models to evaluate historical data, product performance metrics, and consumer feedback. The goal is to forecast potential defects or safety issues before products are released to the market or cause significant harm. This method allows companies to identify high-risk items in advance, minimize financial risks, improve consumer safety, and ensure smoother compliance with regulatory requirements.

The core components of AI-driven product recall prediction include software, hardware, and services. Software encompasses a range of digital tools, analytics platforms, and applications designed to process and manage data, thereby enhancing decision-making and operational effectiveness across industries. These software solutions can be hosted either on-premises or via the cloud, catering to organizations of all sizes, from small businesses to large enterprises. This technology is applied in sectors such as automotive, food and beverage, pharmaceuticals, consumer electronics, and retail, and is used by various stakeholders including manufacturers, distributors, retailers, and more.

The artificial intelligence (AI)-driven product recall prediction market research report is one of a series of new reports that provides artificial intelligence (AI)-driven product recall prediction market statistics, including artificial intelligence (AI)-driven product recall prediction industry global market size, regional shares, competitors with a artificial intelligence (AI)-driven product recall prediction market share, detailed artificial intelligence (AI)-driven product recall prediction market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI)-driven product recall prediction industry. This artificial intelligence (AI)-driven product recall prediction 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 artificial intelligence (AI)-driven product recall prediction market consists of revenues earned by entities by providing services, such as defect detection, quality monitoring, risk prediction, recall forecasting, and supply chain analytics. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI)-driven product recall prediction market also includes sales of software platforms, analytics tools, data integration systems, and artificial intelligence (AI)-powered quality monitoring solutions. 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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