Price Anomaly Detection Artificial Intelligence Global Market Report 2025

The price anomaly detection artificial intelligence market size has grown exponentially in recent years. It will grow from $1.55 billion in 2024 to $1.96 billion in 2025 at a compound annual growth rate (CAGR) of 27%. The growth in the historic period can be attributed to increasing adoption of artificial intelligence and machine learning technologies, rising demand for real-time data monitoring, growth in cybersecurity threats and fraud detection needs, increasing use of predictive analytics across various industries, and rising investments in cloud computing and big data analytics.

The price anomaly detection artificial intelligence market size is expected to see exponential growth in the next few years. It will grow to $5.06 billion in 2029 at a compound annual growth rate (CAGR) of 26.7%. The growth in the forecast period can be attributed to advancement in Internet of Things (IoT) device adoption, rising demand for real-time data monitoring, innovation in cybersecurity threat detection, advancement in cloud computing integration, and development of artificial intelligence and machine learning technologies. Key trends in the forecast period include advancement in real-time anomaly detection capabilities, development of explainable artificial intelligence and machine learning techniques, innovation in unsupervised and semi-supervised learning models, advancement in automated anomaly detection for cybersecurity, and development of scalable AI solutions for big data analytics.

The increasing exponential rise in digital transactions is expected to drive the growth of the price anomaly detection artificial intelligence market going forward. The rise in digital transactions refers to a rapid, accelerating growth in the volume and value of electronic (non-cash) payments. Digital transactions are increasing, driven primarily by a major shift among consumers toward card, contactless, and online payment methods. Price anomaly detection artificial intelligence identifies and flags irregular or erroneous prices in real time across millions of digital transactions, allowing merchants to correct pricing, protect margins, and maintain buyer trust. By reducing pricing errors and enabling reliable dynamic pricing, the technology enhances platform credibility and encourages further adoption of digital payments. For instance, in October 2025, according to UK Finance, a UK-based trade association, about half of mobile payment users paid monthly, and 44% did so weekly or more often, with the highest use among 16-24-year-olds (88%) and a rise among those 65+ from 14% in 2023 to 25% in 2024. Therefore, the increasing exponential rise in digital transactions is expected to drive the growth of the price anomaly detection artificial intelligence market.

Key companies operating in the price anomaly detection artificial intelligence market are focusing on incorporating machine learning to enhance real-time anomaly detection. Machine learning is a field of artificial intelligence where systems automatically learn from data and improve their accuracy or performance over time without explicit programming. For instance, in August 2025, Wellgistics Health, a US-based pharmaceutical technology company, introduced HubRx AI. This platform integrates machine learning to automate prescription routing, optimize inventory management, and detect anomalies in real time. By leveraging historical data and predictive analytics, HubRx AI enhances operational efficiency and reduces the risk of pricing discrepancies. Such innovations highlight the growing reliance on machine learning to address the complexities of price anomaly detection, providing businesses a proactive approach to maintain pricing integrity and customer trust.

In August 2023, IFS, a Sweden-based cloud enterprise software provider, acquired Falkonry for an undisclosed amount. Through this acquisition, IFS aims to strengthen its AI-powered industrial asset performance and anomaly detection capabilities, enabling scalable and cost-efficient AI solutions for predictive maintenance and process optimization. Falkonry is a US-based company specializing in price anomaly detection artificial intelligence.

Major players in the price anomaly detection artificial intelligence market are Google LLC, Microsoft Corporation, Amazon Web Services Inc., IBM Corporation, Oracle Corporation, Infosys Limited, Wipro Limited, SAS Institute Inc., Fair Isaac Corporation, DataRobot Inc., Pricefx AG, Pricemoov, H2O.ai Inc., Revionics Inc., Zilliant Inc., Wiser Solutions Inc., Anodot Ltd., Competera Ltd., Prisync, BlackCurve Solutions Ltd., and NetRivals.

North America was the largest region in the price anomaly detection artificial intelligence market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in price anomaly detection artificial intelligence report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the price anomaly detection artificial intelligence 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.

The price anomaly detection artificial intelligence market research report is one of a series of new reports that provides price anomaly detection artificial intelligence market statistics, including price anomaly detection artificial intelligence industry global market size, regional shares, competitors with a price anomaly detection artificial intelligence market share, detailed price anomaly detection artificial intelligence market segments, market trends and opportunities, and any further data you may need to thrive in the price anomaly detection artificial intelligence industry. This price anomaly detection artificial intelligence 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.

Price anomaly detection artificial intelligence (AI) is the practice and technology for monitoring, tracing, and analyzing pricing data patterns in real time to identify irregular behavior or anomalies in pricing transactions. The primary purpose of this system is to provide real-time visibility into pricing deviations, detect unexpected changes, and alert businesses to potential errors, fraud, or market shifts.

The key components of price anomaly detection artificial intelligence include software, hardware, and services. Software comprises AI algorithms, analytics engines, and dashboards that detect irregular price changes and deliver actionable insights. Deployment modes include cloud and on-premises, and it is used by enterprises of different sizes, including small and medium enterprises and large enterprises. It is applied across sectors such as retail, e-commerce, banking, financial services, insurance, manufacturing, healthcare, transportation and logistics, and others.

The price anomaly detection artificial intelligence market consists of revenues earned by entities by providing services such as real-time anomaly detection and alerting, root cause analysis, and automated pattern recognition. The market value includes the value of related goods sold by the service provider or included within the service offering. The price anomaly detection artificial intelligence market also includes sales of inference appliances, network appliances, secure hardware enclaves, barcode scanners, and edge telemetry devices. 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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