AI 가격결정 툴 시장 보고서 : 동향, 예측 및 경쟁 분석(-2035년)

AI Pricing Tool Market

The future of the global ai pricing tool market looks promising with opportunities in the SMEs and large organization markets. The global ai pricing tool market is expected to reach an estimated $15.2 billion by 2035 from $5.4 billion in 2027 with a CAGR of 10.2% from 2027 to 2035. The major drivers for this market are increasing demand for dynamic pricing strategies, growing demand for real-time pricing insights, and expansion of subscription-based business models.

• Lucintel forecasts that, within the type category, cloud-based is expected to witness higher growth over the forecast period due to lower upfront costs and easier scalability for growing businesses.
• Within the application category, SMEs is expected to witness the highest growth over the forecast period due to the need accelerates for automation of pricing for small and medium-sized businesses.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period due to exponential growth of e-commerce and the rapid digitization of the region.

Emerging Trends in AI Pricing Tool Market

The AI pricing tools market is shifting from rule-based AI to demand, competition, customer willingness to pay, and margin target AI technologies. By 2027, the beyond airline and retail segments will include manufacturing, software, and distribution. Investment will depend on measurable revenue impact, governed data, and integration in enterprise pricing workflows.

• Generative Pricing Intelligence: By 2025, a combination of transaction data and large language models will allow answers to queries about price waterfalls and justification for recommendations. In November 2024, according to McKinsey, 78 percent of organizations use AI in at least one function. Faster decisions without human approval will drive adoption of this technology.
• Real-time Dynamic Pricing: Retail and digital businesses are moving from monthly repricing to event-based pricing based on competitor, demand, and inventory levels. Reporting from Amazon for 2025 continues to show a business built on fast price changes for millions of products. In the next 3-5 years, volatile categories will be dominated by real-time dynamic pricing.
• Governed and Explainable AI: The EU AI Act began its phased application in February 2025, and is driving the requirement for model explanations, documented data, and controlled outputs. Pricing vendors will add approval rules, audit trails, bias checks, and scenario testing for regulated B2B pricing, contracts, and customer-specific offers.
• Embedded Pricing Workflows: Including pricing suggestions inline in CRM, ERP, CPQ, and revenue management systems is how enterprise software solutions are offering pricing functionality. Salesforce reported $37.9 billion projected revenue in fiscal year 2025, providing perspective on the scale of the platforms that can offer AI capabilities. It is estimated that embedded tools will win the market because users would rather have suggestions integrated inline with their workflow compared to using a different analytical tool.
• Margin-led Optimization: As input costs are more volatile, companies tend to shift their focus from measuring volume to measuring contribution margin; PROS reported $274.7 million in subscription revenue in 2024, further illustrating the demand for revenue management solutions. During 2025-2027, pricing tools will combine costs, rebates, freight, and churn to ensure pricing tools protect vendor profitability.

The market is beginning to favor tools that deliver measurable margin improvements over tools that offer flexible integrations. We expect the earliest integrations to occur in high price churn environments. Emerging compliance related procurement frameworks will dominate how enterprise software is deployed over the next few years.

Recent Developments in the AI Pricing Tool Market

AI pricing tools for 2025-2027 show activity moving from pilot budgets to operating budgets. Users want margin control, explainability, and ERP connectivity, while vendors provide generative AI features. Lucintel looks at this as a shift to pricing software as revenue infrastructure rather than an analytics purchase.

• Generative AI Pricing Copilots: AI-augmented pricing and quoting by PROS in February 2025 helps give thousands of pricing recommendations much faster. The corporate effect is substantial: the delegation of pricing work to sales staff will be much broader.
• Cloud Ecosystem Partnerships: Pricefx has reinforced its cloud alliance strategy with major hyperscaler integrations in May 2025, providing much broader, global customer deployments. The relevance here is that the performance of pricing algorithms becomes less important than ERP, CRM, and data platform integrations.
• Margin-Centric Transformations: In 2025, corporate buyers significantly increased the need for measurable profit outcomes. Widely, double-digit growth in software renewals for pricing and revenue management was reported. In the next three to five years, this finance-led procurement preference will continue for tools that have a clear impact on gross margin and price achievement.
• Embedded Pricing Intelligence: Microsoft, SAP and Salesforce offered pricing recommendations within their integrated software suites in 2025. This opens their integrated software suites to pricing decisions and may become the biggest competitive threat for vendors who offer stand-alone pricing offerings.
• Governance and Explainability Requirements: Given the European Union AI Act's requirements with a February 2025 effective date, vendors are forced to begin documenting model behavior and human oversight. Ultimately, all purchasers of regulated products will make buying decisions based on a vendor's ability to explain model behavior and provide controls to approve system recommendations and justify pricing.

From 2025 through 2027, the market for ai pricing tools moves from disorganized analytics to governed revenue infrastructure, and buyers will shift from rewarding tools with the most novel functionality to tools that improve margin with depth and automation. Vendors who offer reliable workflow automation and integrate proprietary datasets should gain market share. Complex B2B pricing, where generative ai copilots fail to meet enterprise needs, remains a large and underserved market opportunity for these specialists.

Strategic Growth Opportunities in the AI Pricing Tool Market

As inflation and pressure on margins caused by digital channels and unbundled product catalogs push the ai pricing tool market to grow more rapidly, pricing automation tools powered by the cloud and better transaction data should become more widely available by 2024-2026. Lucintel has observed the market has potential to grow beyond basic recommendations.

• Vertical Pricing Applications: Pricing models tailored to inventory management, customer demand, and reluctance to pay differ by industry and are required by retail, airlines, hospitality, and online marketplaces. Booking Holdings reported 1.1 billion room nights in 2024 in February, showing the scale that exists. Vertical tools should dominate over broad tools that struggle to comply with industry-specific rules.
• Industrial B2B Pricing: Use of AI to address contract pricing, rebates, freight terms, and regional offers vs. using spreadsheets should be a key focus for manufacturers. PROS reported $301.8 million revenue in 2024 in February. This opportunity will continue to grow as sales organizations are forced to make guided, auditable price decisions to protect margins.
• Embedded Pricing Software: The ability to price AI within the commerce and order management tools/systems currently offered by commerce platforms and ERP vendors should lead to adoption of pricing software by a greater number of mid-market organizations that do not have dedicated pricing teams. Shopify reported $8.9 billion revenue for 2024 in February.
• Geographic Expansion: Vendors can utilize emerging payment systems to develop pricing models to address currency, tax, and payment behaviors across fragmented distribution in APAC, LATAM, and the Middle East. India had 270 million active digital payment users in 2025 per the government. During the next 3-5 years, regional dominance should be defensible.
• Pricing Governance Services: Competition and consumer protection issues arise with AI-generated pricing, leading to a need for monitoring, approvals, and documentation. The first provisions of the EU AI Act come into effect in February 2025. Governance features and managed services will likely become a major source of recurring revenue for regulated enterprises.

Demand for pricing engines integrated with transactional data and capable of decision rationalization will be the primary focuses for vendors. Commercial teams will favor pricing engines Enabled with industry specific models over generic models. In emerging markets, local regulations for tax rules, currency, and data governance will drive a vendor's ability to serve a market over an extensive feature set. Buyers will prioritize vendors that provide a quick return on investment.

AI Pricing Tool Market Drivers and Challenges

The ai pricing tool market is impacted by several factors, including technological advancements, customer expectations, the economy, and court decisions. AI is used to determine the perfect price, predict demand, and maximize profit margin in various businesses. Some technologies like cloud, data, and automation tools are rapidly increasing the deployment of AI, while customer privacy issues, bias in introduced algorithms, and high integration costs are limiting factors. Lucintel has displayed a positive outlook on the market due to the rapid nature of price changes that competing firms may need. The speed of market adoption is not limited to pricing tools and frameworks. About potential technological threats (cyber), and the uncertainty of the legal framework for AI, the speed at which adoption spreads to additional geographical regions and business activities is limited.

The factors responsible for driving this market include:

• Customer Demand: Many businesses have an increasing demand to use more tailored, flexible, and data-driven pricing to address the challenges posed by competitive actions and the customers' willingness to pay. Automated real-time pricing capabilities across online channels remained in high demand by retailers and digital commerce firms in January 2025. Over the next 3-5 years, the rapid market demand for optimizing margins will drive the adoption of AI pricing tools in retail, manufacturing, travel and services sectors. In addition to calculating prices, AI pricing tools have the potential of being used for customer segmentation, evaluating promotions, and managing customer lifetime value. Due to the need for consistent prices, businesses will invest in integrated AI pricing platforms across their multi-channel operations.
• Technology Development: The advancements of machine learning, generative AIs, and cloud computing, coupled with the rise of application programming interfaces, have a positive impact on efficiency and accuracy of pricing. By June 2025, most enterprise software platforms created natural language interfaces. As a result, commercial teams had the ability to test pricing scenarios without heavy programming knowledge. In coming years, the use of stronger predictive models, fast computing, and improved explainability of pricing systems will allow companies to reach more customers. Enhanced automation also will reduce the time needed to implement a system allowing more mid-sized companies to have the pricing tools that previously were restricted to larger companies with large analytics teams.
• Regulatory Support: Government support for artificial intelligence and responsible digital transformation will create demand for compliant pricing solutions. In February 2025, several government agencies and industry associations continued to create oversight to AI risk management and automated decision-making solutions. The creation of clear regulations in the next three to five years will move companies from informal pricing systems based on spreadsheets and black box algorithms towards pricing solutions which can provide documentation and oversight. Regulations will increase compliance costs; however, the improved trust of a prospective buyer towards a solution will create increased standardization of procurement which will favor established and technology advanced vendors.
• Artificial Intelligence (AI) Pricing: AI tools allow companies to adjust prices to meet available inventory and avoid waste. For example, in September 2025, businesses in the food, fashion, and consumer goods industries were more actively testing markdown optimization to limit unsold inventory and its associated greenhouse gas emissions. It is expected that within the next three to five years, companies will begin to link pricing decisions to their waste reduction, energy consumption, and circular economy goals. Several tools can aid in achieving these goals. For example, a tool utilizing dynamic markdowns can aid in selling perishable goods, while a tool based on demand forecasting can mitigate the risk of overproduction. In addition, as organizations grapple with consumer demands for goods produced in a more sustainable and responsible manner, as well as an increasing pressure to report on their carbon footprints, vendors that measure environmental impact alongside commercial success are likely to gain more business.
• Design Optimization for Manufacturing: The technology associated with pricing automation improves the integrated coordination of the procurement process with inventory, production, and sales, allowing manufacturers to respond optimally to fluctuations in price and the capacity constraints of inputs. Examples of these systems include connected pricing systems that, in contrast to the usual days-based quotes, respond to changing input costs in less than a minute . The following three to five years will see manufacturers using these systems to protect margins and avoid costly errors, as well as to maximize the usage of their scarce productive capacity. The integration of pricing systems with production management systems and supply chain will lead to more flexible prices in consideration of the duration of the orders and their complexity . This will help companies in the customized products and services with complex supply chains.

The challenges facing this market include:

• Data Quality and Availability: Misaligned, incomplete, or inaccurate data will result in poor overall data infrastructure and tool integration. Many organizations still operate with legacy systems, and most of them remain fragmented. Surveys on enterprise technology conducted in March 2025 indicated that the remaining barriers to the use of AI remain within data integration and governance, with nearly 40 percent of the respondents indicating major limitations to the readiness of data. Poor data quality will result in forecasting confidence and accuracy decreasing over the next 3 to 5 years. Companies will need to invest in data, cleansing, master data management, and standardized metrics. The use of connectors, validation controls, and proper data lineage will position companies and vendors to overcome this challenge.
• Regulatory and Ethical Concerns: Algorithmic pricing raises a variety of ethical and regulatory concerns, including unfair pricing, privacy, and discrimination. In October 2025, organizations continued to construct artificial intelligence governance and oversight with stronger documentation. In the next 3 to 5 years, pricing scandals, review delays, or litigation will increase legal costs and slow deployment. Audit trails, models, and reviews will be required by businesses to ensure accountability. Vendors will need to create systems that evaluate fair pricing to ensure there is no discrimination. Not addressing these risks may lead to reputation loss, a reduction in client trust, increased ethical concerns, fines, and customer attrition.
• Implementation Costs and Skills Shortage: One challenge with adopting a solution from the ai pricing tool market is that it requires software integrations, process redesigns, talent training, and redesigns. In July 2026, companies continued to report difficulties in filling positions for professionals with skills in pricing strategy, ML, data engineering, and change management. Over the next 3 to 5 years, these issues will be more dominant and will disproportionately affect smaller and medium sized enterprises. Long implementation cycles will contribute to companies using spreadsheets or keeping simple rule-based systems. Potential vendors should consider subscription pricing, pre-built models, interfaces with a low or no-code approach, and managed services and Measurable pilots as ways to address some of these issues.

The ai pricing tool market will have high demand driven by the focus on margin improvement, the use of advanced technologies, the emphasis on faster and better decision-making, sustainability, and continued efforts to improve operational efficiencies. Some of the barriers that will limit this growth over the next 3 to 5 years will be the shortages of skills and talent, high implementation costs, data constraints, uncertainty in the regulatory environment, ethical concerns, and uncertainty in the way the market will grow. In the next 3 to 5 years infrastructure with cloud based services will improve while concerns for good governance will decrease. Vendors of flexible products that integrate well with the users systems will be successful in the market.

List of AI Pricing Tool Market Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies ai pricing tool market companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the ai pricing tool market companies profiled in this report include-

• Dynamicpricing
• Sniffie
• Pros
• Bcg
• Accenture
• Yieldigo
• Reactev

AI Pricing Tool Market by Segment

The study includes a forecast for the global ai pricing tool market by type, application, and region.

AI Pricing Tool Market by Type [Value ($B) from 2019 to 2035]:

• Cloud-based
• On-Premise

AI Pricing Tool Market by Application [Value ($B) from 2019 to 2035]:

• SMEs
• Large Organization
• Others

AI Pricing Tool Market by Region [Value ($B) from 2019 to 2035]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the AI Pricing Tool Market

During the 2025-2027 timeframe, the ai pricing tool market is developing due to the deployment of AI, compute programs, sovereign procurement and cloud-based automation. Cloud based vendors are adding automated quotation and pricing recommendations to business software. Lucintel has stated that, more than model performance, the market will be defined by the execution of these AI deployments.

• United States: U.S. government investments and product rollouts are increasing: Salesforce rolled out Agentforce across more regions in January 2025, while Stargate announced $500 billion of U.S. AI funding (January 2025). These deployments will give pricing software larger budgets for data access, software integration and compute for procurement in the next 3 to 5 years.
• China: Automation pricing tool usage across manufacturers, distributors and online marketplaces will likely increase due to local model deployments. DeepSeek released R1 in January 2025, and Alibaba introduced Qwen2.5-Max in January 2025.
• Germany: SAP released Business Data Cloud in February 2025 combined enterprise data with AI and service offerings under the strategy Joule. SAP's market presence has the potential to embed pricing recommendations across its core business software.
• India: The IndiaAI AI Mission is underway with the goal of greater access (over 18,000 GPUs) to a national compute facility (January 2025). This funding should create a favorable pricing environment for vendor tool developers in India and improved pricing for Indian businesses.
• Japan: With the announcement of collaborating to introduce OpenAI technology across the Group Companies, and for the development of enterprise applications (February 2025), SoftBank and OpenAI will utilize OpenAI's technology for enterprise application offerings. SoftBank sells insurance and provides financial services. An extended presence through SoftBank's distribution network and enterprise customer base will make pricing, contracting and revenue management AI tools more accessible in Japan.

Features of the Global AI Pricing Tool Market

• Market Size Estimates: ai pricing tool market size estimation in terms of value ($B).
• Trend and Forecast Analysis: Market trends (2019 to 2026) and forecast (2027 to 2035) by various segments and regions.
• Segmentation Analysis: ai pricing tool market size by type, application, and region in terms of value ($B).
• Regional Analysis: ai pricing tool market breakdown by North America, Europe, Asia Pacific, and Rest of the World.
• Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the ai pricing tool market.
• Strategic Analysis: This includes M&A, new product development, and competitive landscape of the ai pricing tool market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the ai pricing tool market by type (cloud-based and on-premise), application (smes, large organization, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 8 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Market Overview

• 2.1 Background and Classifications
• 2.2 Supply Chain

3. Market Trends & Forecast Analysis

• 3.2 Industry Drivers and Challenges
• 3.3 PESTLE Analysis
• 3.4 Patent Analysis
• 3.5 Regulatory Environment

4. Global AI Pricing Tool Market by Type

• 4.1 Overview
• 4.2 Attractiveness Analysis by Type
• 4.3 Cloud-based: Trends and Forecast (2019-2035)
• 4.4 On-Premise: Trends and Forecast (2019-2035)

5. Global AI Pricing Tool Market by Application

• 5.1 Overview
• 5.2 Attractiveness Analysis by Application
• 5.3 SMEs: Trends and Forecast (2019-2035)
• 5.4 Large Organization: Trends and Forecast (2019-2035)
• 5.5 Others: Trends and Forecast (2019-2035)

6. Regional Analysis

• 6.1 Overview
• 6.2 Global AI Pricing Tool Market by Region

7. North American AI Pricing Tool Market

• 7.1 Overview
• 7.2 North American AI Pricing Tool Market by Type
• 7.3 North American AI Pricing Tool Market by Application
• 7.4 United States AI Pricing Tool Market
• 7.5 Mexican AI Pricing Tool Market
• 7.6 Canadian AI Pricing Tool Market

8. European AI Pricing Tool Market

• 8.1 Overview
• 8.2 European AI Pricing Tool Market by Type
• 8.3 European AI Pricing Tool Market by Application
• 8.4 German AI Pricing Tool Market
• 8.5 French AI Pricing Tool Market
• 8.6 Spanish AI Pricing Tool Market
• 8.7 Italian AI Pricing Tool Market
• 8.8 United Kingdom AI Pricing Tool Market

9. APAC AI Pricing Tool Market

• 9.1 Overview
• 9.2 APAC AI Pricing Tool Market by Type
• 9.3 APAC AI Pricing Tool Market by Application
• 9.4 Japanese AI Pricing Tool Market
• 9.5 Indian AI Pricing Tool Market
• 9.6 Chinese AI Pricing Tool Market
• 9.7 South Korean AI Pricing Tool Market
• 9.8 Indonesian AI Pricing Tool Market

10. ROW AI Pricing Tool Market

• 10.1 Overview
• 10.2 ROW AI Pricing Tool Market by Type
• 10.3 ROW AI Pricing Tool Market by Application
• 10.4 Middle Eastern AI Pricing Tool Market
• 10.5 South American AI Pricing Tool Market
• 10.6 African AI Pricing Tool Market

11. Competitor Analysis

• 11.1 Product Portfolio Analysis
• 11.2 Operational Integration
• 11.3 Porter's Five Forces Analysis
  • Competitive Rivalry
  • Bargaining Power of Buyers
  • Bargaining Power of Suppliers
  • Threat of Substitutes
  • Threat of New Entrants
• 11.4 Market Share Analysis

12. Opportunities & Strategic Analysis

• 12.1 Value Chain Analysis
• 12.2 Growth Opportunity Analysis
  • 12.2.1 Growth Opportunities by Type
  • 12.2.2 Growth Opportunities by Application
• 12.3 Emerging Trends in the Global AI Pricing Tool Market
• 12.4 Strategic Analysis
  • 12.4.1 New Product Development
  • 12.4.2 Certification and Licensing
  • 12.4.3 Mergers, Acquisitions, Agreements, Collaborations, and Joint Ventures

13. Company Profiles of the Leading Players Across the Value Chain

• 13.1 Competitive Analysis
• 13.2 Dynamicpricing
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing
• 13.3 Sniffie
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing
• 13.4 Pros
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing
• 13.5 Bcg
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing
• 13.6 Accenture
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing
• 13.7 Yieldigo
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing
• 13.8 Reactev
  • Company Overview
  • AI Pricing Tool Business Overview
  • New Product Development
  • Merger, Acquisition, and Collaboration
  • Certification and Licensing

14. Appendix

• 14.1 List of Figures
• 14.2 List of Tables
• 14.3 Research Methodology
• 14.4 Disclaimer
• 14.5 Copyright
• 14.6 Abbreviations and Technical Units
• 14.7 About Us
• 14.8 Contact Us