AI in Retail Market Size & Share 2023 to 2032
Market Size by Component (Solution [Chatbot, Customer Behavior Tracking, CRM, Inventory Management, Price Optimization, Recommendation Engine, Supply Chain Management, Visual Search], Service), by Technology, Application & Forecast.
Report ID: GMI2568
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Published Date: January 2023
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Report Format: PDF
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Authors:
Preeti Wadhwani, Aishvarya Ambekar
AI in Retail Market Size
AI in Retail Market size valued at USD 6 billion in 2022 and is slated to witness over 30% CAGR from 2023 to 2032. Driven by the extensive use of product identification and computer vision technologies in retail warehouses.
AI in Retail Market Key Takeaways
Market Size & Growth
Key Market Drivers
Challenges
Artificial intelligence (AI) has wide-ranging applications and has become a future tool for advancement. Healthcare, automotive, manufacturing, and several other booming industries are increasingly integrating AI technologies for everyday tasks. The increased inclination of Gen Z toward online shopping trends in the new era of advanced businesses is accelerating the use of AI in the retail market. The expanding Gen Z population has created the most technology-savvy and mobile-friendly consumer base. Their strong preference to shop online is set to encourage traditional retailers to adopt AI solutions and services.
Furthermore, cashier-less checkouts are another major benefit of integrating AI in the retail sector that is fueling the industry growth. Using computer vision and big data analytics, retailers are transforming routine shopping into intelligent shopping. For instance, in February 2022, Amazon rolled out its Just Walk Out cashier-less technology at its new Amazon Fresh grocery store in Ventura County, California, to offer customers a fully autonomous checkout option.
Complex organizational structures may restrain industry progression
The organizational framework of retailers is a major factor restraining the AI in retail market growth. Administrative culture can hinder the adoption of AI in businesses, especially in companies with underdeveloped analytical decision-making and digital transformation processes that create suspicion in algorithmic decision-making, fueled by the perception that studies and recommendations are unclear. As per KPMG’s Living in an AI World 2020 report, 62 percent of retail participants were not supportive of AI adoption due to a loss of job security. Nevertheless, artificial intelligence offers the potential to help individuals with tedious, time-consuming tasks, which is speculated to prompt retailers to adopt AI services.
AI in Retail Market Analysis
According to the report, the computer vision technology segment held more than a 15% share of the AI in retail market in 2022. The prevalent utilization of computer vision technology by merchants for several in-store applications to compete with their online rivals is driving the market demand. For instance, in September 2022, Kroger Co., an American retailer, rolled out its visual AI-based self-checkout solution that uses Nvidia’s computer vision and AI capabilities with Evergreen’s Visual AI.
With respect to components, the solution segment is expected to grow at 30% CAGR through 2032. The widespread adoption of analytics solutions by online retailers to widen their client base and offer better customer experience is set to facilitate the industry expansion. For instance, in October 2022, Wayfair, a store-commerce firm, completed a full digital transformation by migrating its data center applications and services to Google Cloud Foundation.
In terms of application, the programmatic advertising segment is projected to cross USD 25 billion by 2032. Today's omnichannel consumers can be more effectively reached through programmatic advertising that delivers continually tailored messaging at a massive scale, which is foreseen to propel segment development. According to the Journal of Service Management, consumer preference for programmatic advertising is directly related to their attitude toward the retailer and perceived ad relevance, which generates real-time ads that match their interests.
Under solution, the AI in retail market size from the price optimization segment is poised to amass substantial gains by 2032, as firms are becoming increasingly competitive to extend their customer reach due to declining product differentiation resulting from the rising use of e-commerce platforms. Moreover, with the e-commerce boom, firms are leveraging AI to determine optimal prices in order to bolster their sales, which is foreseen to drive price optimization solutions uptake.
Regionally, the Europe Artificial Intelligence in retail market is estimated to hold more than 15% revenue share by 2032, attributed to rapid digitalization, shifting customer preferences, and product innovation efforts by industry participants operating in the region. For instance, French retail behemoth Carrefour unveiled its first AI-powered store in Paris – the Flash 10/10 (10 seconds to shop & 10 seconds to pay).
AI in Retail Market Share
Some of the leading companies involved in the AI in retail market include
These companies majorly engage in product innovation and collaborate with retail firms to remain ahead in the competitive landscape.
For instance, in May 2022, Symbotic, a robotics warehouse automation company, announced the deployment of its automation technology at Walmart’s 42 Regional Distribution Centers to improve the accuracy of the retail giant’s inventory and expand the capacity of its warehouses.
Impact of COVID-19 pandemic
The COVID-19 pandemic had a favorable impact on the growth of artificial intelligence in the retail sector. According to IBM, a technology corporation, the emergence of the COVID-19 pandemic pushed many in-store retailers to adopt e-commerce solutions, such as the Salesforce commerce cloud solution, which aids merchants in achieving unified customer experience, omnichannel strategies, and automated market analytics. This enables no-contact pickup services, reservation systems in online stores, delivery of meals, and the development of autonomous online businesses, which has positively influenced the market revenue.
This Artificial Intelligence (AI) in Retail Market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue in USD from 2018 to 2032 for the following segments:
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Market, By Component
Market, By Technology
Market, By Application
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
1. Research design & analyst oversight
At GMI, our research methodology is built on a foundation of human expertise, rigorous validation, and complete transparency. Every insight, trend analysis, and forecast in our reports is developed by experienced analysts who understand the nuances of your market.
Our approach integrates extensive primary research through direct engagement with industry participants and experts, complemented by comprehensive secondary research from verified global sources. We apply quantified impact analysis to deliver dependable forecasts, while maintaining complete traceability from original data sources to final insights.
2. Primary research
Primary research forms the backbone of our methodology, contributing nearly 80% to overall insights. It involves direct engagement with industry participants to ensure accuracy and depth in analysis. Our structured interview program covers regional and global markets, with inputs from C-suite executives, directors, and subject matter experts. These interactions provide strategic, operational, and technical perspectives, enabling well-rounded insights and reliable market forecasts.
3. Data mining & market analysis
Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.
4. Market sizing
Our market sizing is built on a bottom-up approach, starting with company revenue data gathered directly through primary interviews, alongside production volume figures from manufacturers and installation or deployment statistics. These inputs are then pieced together across regional markets to arrive at a global estimate that stays grounded in actual industry activity.
5. Forecast model & key assumptions
Every forecast includes explicit documentation of:
✓ Key growth drivers and their assumed impact
✓ Restraining factors and mitigation scenarios
✓ Regulatory assumptions and policy change risk
✓ Technology adoption curve parameter
✓ Macroeconomic assumptions (GDP growth, inflation, currency)
✓ Competitive dynamics and market entry/exit expectations
6. Validation & quality assurance
The final stages involve human validation, where domain experts manually review filtered data to identify nuances and contextual errors that automated systems might miss. This expert review adds a critical layer of quality assurance, ensuring data aligns with research objectives and domain-specific standards.
Our triple-layer validation process ensures maximum data reliability:
✓ Statistical Validation
✓ Expert Validation
✓ Market Reality Check
Trust & credibility
Verified data sources
Trade publications
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Industry databases
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Regulatory filings
Government procurement records and policy documents
Academic research
University studies and specialist institution reports
Company reports
Annual reports, investor presentations, and filings
Expert interviews
C-suite, procurement leads, and technical specialists
GMI archive
13,000+ published studies across 30+ industry verticals
Trade data
Import/export volumes, HS codes, and customs records
Parameters studied & evaluated
Every data point in this report is validated through primary interviews, true bottom-up modelling, and rigorous cross-checks. Read about our research process →