Global Artificial Intelligence in Retail Market Size, Trend & Opportunity Analysis Report, by Component (Solution, Services), Technology (Machine Learning, Natural Language Processing), Sales Channel (Omnichannel, Brick and Mortar, Pure-play Online Retail

Market Definition and Introduction

The global artificial intelligence in retail market was valued at USD 11.61 billion in 2024 and is anticipated to reach USD 113.18 billion by 2035, expanding at a CAGR of 23.0% during the forecast period (2024–2035). Artificial Intelligence (AI) has been rapidly evolving from an auxiliary experiment in retail to infusing sampling with the native propellant of value-enabled transformation basis in the sector. Retailers are restructuring their business models and infusing intelligent algorithms seamlessly into every part of the value chain, from forecasting demand and managing inventory to optimising pricing, all the way to personalising the services they offer. A real-time data analysis, cloud computing, and ubiquitous digital channel-powered ecosystem has turned data-driven dynamics more customer-centric than ever, utterly redefining the function of retail for intuitive consumers. AI is the backbone of predictive, prescriptive decision-making in retail, allowing retailers to understand their clientele better to anticipate needs, streamline logistics, and maximise revenues.

Now, AI's disruptive impact in retail spans beyond e-commerce players, as the feasibility for adoption seems in favour of best transforming the brick-and-mortar traditional in-store journeys with AI. In-store navigation, smart shelves, and AI-operated checkout systems are making the integration of physical and digital channels seamless to provide an omnichannel experience. Concurrently, virtual assistants and conversational AI interfaces are revolutionising interaction with customers, offering live product recommendations, handling questions, and building up brand loyalty. Cloud-based, cheap AI tools with open-source frameworks have democratised their access to mid- and small-sized retailers, thereby levelling the competitive playing field.

The emergence of revolutionary AI applications in the retail sector is spurred by the changing shape of stringent government laws on data protection and privacy, along with the values of see-through AI. Even if the exhaustiveness of such legislation brings about challenges, it also keeps businesses on their toes and pushes them to jump their forward position onto nothing less than transparent, explainable, and unbiased AI systems. The Asia-Pacific region and North Africa considerably mourn the death of face-to-face conversation between man and machine. Today, AI rears its scorching eyes on both in extinguishing them as retail players excel with AI or resign their potential selves too early.

Recent Developments in the Industry

They are based on strategic partnerships to have innovative development in AI-based business platforms for retail.

In April of 2024, Microsoft Corporation united with retailer giant Carrefour to co-develop cloud-based AI tools for personalising customer journeys. It is this partnership that will centre on incorporating real-time insights into predictive analytics, with in-store operations allowing the retailer to unite real-time data insights with dynamic merchandising strategies to ultimately drive sales efficiency with broader consumer loyalty.

Product launches boost AI frameworks for achieving omnichannel retail success.

June 2023 saw Oracle Corporation launch the entire Retail AI Cloud Services suite, designed to improve demand forecasting as well as customer engagement. The offering, powered by deep learning-modelled analytics, manages supply chain challenges and gives access to smarter pricing optimisation, while blurring the line between online and offline channels. The very attendance of this introduction points to the knitting up of already demonstrated industry appetite for solutions with equal measure to agility, at once accuracy.

Regulatory updates transform compliance measures for ethical AI adoption.

These new regulations will promote investment in explainable AI and compliance-ready platforms, ensuring that AI-enabled recommendations are bias-free in terms of the resulting behaviours in retail adopting the content use of customer data while promoting algorithmic transparency. However, one of the most confident points to contemplate is mid-2024, when the EU AI Act implementation is already taking effect in the areas of retail.

Investments Push Up AI Adoption in Retail in Emerging Economies.

In August 2024, Infosys Limited announced a USD 1.2 billion investment programme focusing on AI-powered retail transformation in the Asia-Pacific region. Investments also include setting up innovation hubs across Asia dedicated to advancing AI-enabled logistics and personalised shopping models to prepare the regional market for scalable, future-ready digital ecosystems.

Expansions Sharpen AI Footprint in Next Generation Retail Hubs.

By launching innovation labs in India and Brazil, Amazon Web Services expanded its AI-driven retail analytics in November 2023. The local setup is expected to help retailers cash in on these gains with AI applications in last-mile delivery optimisation and in cutting costs as well as establishing seamless shopping environments, thereby driving rapid adoption in high-growth regions.

Market Dynamics

AI deployment in the retail ecosystem is a result of rising consumer demand for customised shopping.

AI use in the retail market came into action to serve the increased demand for personalised shopping. In doing so, retailers use machine learning models for consumer behaviour, preferences, and expected purchases, hence, influencing more or new offers and recommendations in real-time. As the strategy increases customer loyalty, basket size, and slows down churn in both physical and digital commerce, it may also be seen as a game-changing approach. Additionally, in an omnichannel world, widespread AI adoption brings consistency and unifies customer touchpoints so customers can identify the brand with ease.

High costs and a lack of skill set hamper wider AI adoption.

Despite improved possibilities, AI faces hindrances in its spread due to high placement fees and the scarcity of professionals skilled in AI. The infrastructure for AI requires great IT infrastructure, data replication capabilities, and high analytics capabilities, all of which make it an uphill task for small and mid-sized retailers. Of even greater concern, scaling such feed is even more awkward with the shortage of AI-skilled professionals across multiple retail functions. While the advent of cloud-based AI-as-a-service models has to some extent mitigated these challenges, financial and human resistance is far from over, keeping down the growth among resource-starved retailers.

Privacy issues and tough regulations create challenges for AI-led retail growth.

Consumer data is the cornerstone of AI systems; thus, complying with privacy laws like GDPR plus CCPA is as difficult. To begin with, this means the retail store needs to inform, anonymise, and remain accountable for algorithmic operation in the handling of consumer data. Global regulations pose a greater threat, because compliance would be easier to do in a cross-border initiative; additional time will be spent adapting technologies region by region. Ignoring these ethical concerns and privacy issues can hamper brands' reputations or lead to regulatory fines; compliance is thus a major issue for the retail sector.

Who is not looking forward to predictive analytics and intelligent supply chains?

The future of AI in retail will be forecasted through predictive analytics and intelligent supply chain dynamics. While the AI revolution will transform the way that we predict demand, combine it with our warehouse space optimisation, and make sure the last mile is very efficient and may soon be a complete package, reducing all unnecessary costs. In a rapidly growing e-commerce environment, speed and accuracy make the difference. Equally impressive could be the endorsed future AI-powered dynamic pricing models and real-time payment analytics as telltale signs of the fast-emerging commercial possibilities in the next-generation retail ecosystem.

Emerging trends imply the future presence of AI-driven, interactive, and green retail ecosystems.

One of the most powerful trends in the retail market is the advent of these AI-driven interactive shopping environments where AR/VR and generative AI converge to bring dynamic experiences. At the same time, environmental sustainability has become the starting point for a situation in which retailers pump AI into curbing waste, saving energy, and ensuring more supply chain transparency. Both these together define an emerging new reality under which retail ecosystems have been transformed into models geared towards being customer-centric, digitally immersive, and environmentally responsible.

Attractive Opportunities in the Market

AI-Powered Personalisation – Hyper-customised recommendations fuel stronger loyalty and increase consumer spending.
Predictive Analytics Growth – Smarter forecasting reduces supply chain inefficiencies and enhances retailer responsiveness.
Immersive Retail Experiences – AR/VR and generative AI deliver interactive shopping simulations and product visualisations.
Green Retail Transformation – AI enhances sustainability by reducing waste and improving resource allocation.
Cloud-Based AI Expansion – Affordable AI-as-a-service widens adoption among small and mid-sized retailers globally.
Data Compliance Edge – Retailers deploying explainable AI gain regulatory approval and a customer trust advantage.
Intelligent Pricing Models – AI-driven real-time price optimisation maximises margins in competitive markets.
Retail Automation Surge – Robotics and AI improve checkout, restocking, and inventory tracking efficiency.
E-Commerce Boom – AI adoption accelerates in fast-growing online marketplaces, particularly in the Asia-Pacific region.
Collaborative Ecosystems – Strategic alliances between tech giants and retailers drive innovation in retail AI.

Report Segmentation

By Component:
Solution, Services

By Technology: Machine Learning, Natural Language Processing

By Sales Channel: Omnichannel, Brick and Mortar, Pure-play Online Retailers

By Application: Customer Relationship Management (CRM), Supply Chain and Logistics, Inventory Management, Product Optimisation, In-Store Navigation, Payment and Pricing Analytics, Virtual Assistant, Others

By Region: North America (U.S., Canada, Mexico), Europe (UK, Germany, France, Spain, Italy, Spain, Rest of Europe), Asia-Pacific (China, India, Japan, Australia, South Korea, Rest of Asia-Pacific), LAMEA (Brazil, Argentina, UAE, Saudi Arabia (KSA), Africa Rest of Latin America)

Key Market Players

Microsoft Corporation, IBM Corporation, Amazon Web Services, Google LLC, Oracle Corporation, Salesforce, Intel Corporation, SAP SE, NVIDIA Corporation, and Infosys Limited.

Report Aspects

Base Year: 2024
Historic Years: 2022, 2023, 2024
Forecast Period: 2024-2035
Report Pages: 293

Dominating Segments

End-to-end AI Solutions in Retail Drive Technology and Innovation

Solutions make up the backbone of retail AI programs and include software packages that work with CRM, supply chain alterations, and customer engagement. In AI technologies, predictive analytics are brought together with natural language processing and intelligent recommendation engines, which world retailers are hoping to reimagine the shopping experience. As such, a lean-to-mean system structure leaves ample additional room for the advancement of end-to-end solution systems within this context. AI software allows seamless processes for in-store and online insights, allowing the retail industry more informal adaptation. Large retailers are augmenting AI investment to develop scalable platforms, thus reinforcing the dominance of this segment in an AI strategy in retail's long-term future.

Machine learning technologies are ruling the roost in the retail AI market, allowing for predictive decisions with some consumer insight.

Machine learning lays the foundational groundwork for many of AI's appeals in retail, offering several useful applications, including demand prediction, precision marketing, fraud detection, and price optimisation. In retail, it allows retailers to scour through data and come up with patterns impossible for human filters to track. Machine learning also enjoys exquisite affordability for flexible usage throughout several retail functions, from logistics optimisation to consumer engagement. Reinforcement learning and neural networks have also come into play; it is little wonder that it is precisely through them that much development has affected the accuracy of machine learning models, thereby enhancing operational efficiency and profitability. The latter continues to hammer its dominance in driving the highest share of AI in the retail market.

The development of an omnichannel distribution channel has lent it some edge, thus aligning consumer journeys across digital and physical retail realms.

Omnichannel is a great transformational retail strategy. It is the opposite of the online-offline binary, as here retailers blend the two experiences to form a complete idea. Artificial Intelligence orchestrates these interactions, ensuring consistent customer engagement over e-commerce websites, mobile apps, and brick-and-mortar stores. Predictive analytics, AI chatbots, and intelligent recommendation engines then give an advantage in leading personalised omnichannel journeys, thereby improving conversion rates and customer loyalty. Hybrid behaviour of a new generation, where buyers research online and buy in-store, or vice versa, has come up, and these AI-powered omnichannel strategies have suddenly become indispensable. This particular dominance is most evident in the sophisticated retail markets, namely North America and Europe, where cutting-edge competition pushes retailers towards unified AI ecosystems.

AI/CRM Leads the Pack of AI Retail Applications, Followed By Customer Engagement and Retention

CRM remains the most fashionable in-use AI application area in retail, driven by retailers who want to achieve personalised engagements using more sophisticated tools. CRMs driven by AI focus on real-time segmentation, dynamic recommendations, and sentiment analysis, giving a lot of insight into consumer behaviour. CRM platforms are used by retailers for the manufacture of loyalty programs, as well as automation of customer service or promotion of targeted offers, resulting in tangible growth within retention. CRM solutions are a must as they direct complete interplay in the face of cost-cutting competition in customer loyalty. Heavy usage and high reliance on AI CRM keep this sector undoubtedly in the topmost front seat for AI usage in retail.

Key Takeaways

Solutions Drive Growth – Integrated AI platforms dominate retail transformation through end-to-end digital integration.
Machine Learning Core – Predictive models optimise decision-making and enhance consumer insights at scale.
Omnichannel Ascendancy – Unified retail ecosystems elevate customer journeys across physical and digital channels.
CRM Leadership – AI-driven CRM platforms spearhead customer loyalty and engagement in competitive markets.
Data Privacy Hurdles – Regulatory frameworks necessitate explainable, bias-free, and secure AI retail adoption.
Sustainability Push – AI enables retailers to align with global sustainability goals through waste reduction.
E-Commerce Catalyst – Online retail growth accelerates AI deployment in supply chain and logistics optimisation.
Innovation Surge – Generative AI and immersive technologies transform consumer engagement and shopping experiences.
SME Adoption Rising – Cloud-based AI-as-a-service expands retail AI access for small and mid-tier retailers.
Strategic Alliances Expand – Partnerships between retailers and tech giants accelerate AI adoption globally.

Regional Insights

North America tops the charts by far in its use of AI in retail, enabled by a solid foundation in technological infrastructure and advanced consumer ecosystems.

North America, particularly the United States, is leading the way in the adoption of AI in retail. Advantages in this region include advanced cloud infrastructure, mature e-commerce penetration, and consumer data ecosystems, creating a very rich environment for AI. Industry leaders such as Walmart and Amazon have invested a lot in AI-based logistics, pricing, and personalisation models, setting up global benchmarks. And to top it all, stringent data privacy regulations and consumer rights frameworks have driven retailers to develop transparent and ethical AI systems. All these conditions make North America a world-leading stage for retail AI, and continuous investment only reinforces the lead position.

Europe progresses AI retail with a focus on sustainability and an ethical compliance framework.

Europe continues to be a stronghold for retail AI, mainly because of its sustainability agenda and a strong emphasis on regulations surrounding the ethical use of AI. An AI Act plus GDPR is drawing up a zone of explainability, fairness, and consumer protection around AI deployments. A few retailers in Germany, France, and the UK are beginning to use AI in supply chain optimisation, improving transparency in stock holding while also maintaining sustainable practices. Further funding into circular economy initiatives encourages retailers to adopt AI into waste reduction and consumer engagement strategies that are environmentally friendly. The strong retail base of Europe, coupled with its commitment to regulatory innovation, sustains its leading role in driving growth in AI for retail.

Asia-Pacific continues to endorse the fastest growth of its commercial AI-in-retail market across continents by digitalisation and consumption.

Asia-Pacific has recorded the fastest growth in all of the continents in terms of adopting AI technology in commerce. The countries of China, India, and South Korea possibly have the largest retail markets and equally the best government-assisted technological initiatives. Alibaba and Flipkart, among other e-commerce platforms, are founding applications and beneficial projects that harness predictive analytics, logistics, and immersive retail experiences using AI. As consumption among rising middle-class individuals propels growth, it increases the appetite for mobile commerce, and in turn, AI-driven retail ecosystems sprout rapidly. The dynamic landscape that the Asia-Pacific region has ensured keeps it as the fastest-growing market for AI in retail.

LAMEA takes forward the AI-fuelled adoption in retail through modernising commerce, coupled with innovation initiatives within regions.

AI in retail is also gradually being adopted in Latin America, the Middle East, and Africa (LAMEA) because of the growth in digital commerce and modernisation initiatives. Brazil shows an increase in AI-driven innovation in e-commerce, while the Middle East spends on smart retail technologies in line with broader digital transformation agendas, such as Saudi Vision 2030. The retail environment in Africa is largely mobile-based, and AI is being used to promote financial inclusion as well as penetration of digital commerce use. While the challenges related to infrastructure gaps and regulatory fragmentation are evident, increasing investments in AI ecosystems point to the trajectory of continued growth and exceptional potential in the region.

Core Strategic Questions Answered in This Report

Q. What is the expected growth trajectory of artificial intelligence in the retail market from 2024 to 2035?

The global artificial intelligence in retail market is projected to grow from USD 11.61 billion in 2024 to USD 113.18 billion by 2035, registering a CAGR of 23.0%. This growth is driven by personalisation demands, omnichannel retail expansion, and technological innovation across applications such as CRM, supply chains, and immersive shopping.

Q. Which key factors are fuelling the growth of artificial intelligence in the retail market?

Several key factors are propelling market growth:

Rising demand for personalised and immersive shopping experiences
Increasing adoption of omnichannel retail strategies
Expansion of cloud-based AI services and affordable access for SMEs
Growth of predictive analytics in supply chains and logistics
Regulatory emphasis on ethical AI adoption and data transparency

Q. What are the primary challenges hindering the growth of artificial intelligence in the retail market?

Major challenges include:

High implementation and operational costs for AI systems
Shortage of skilled AI professionals in retail deployment
Complex regulatory compliance across global retail markets
Data privacy and ethical AI concerns are limiting consumer trust
Legacy infrastructure constraints for small and mid-sized retailers

Q. Which regions currently lead the artificial intelligence in the retail market in terms of market share?

North America currently leads the AI in retail market due to advanced infrastructure and mature consumer ecosystems, while Europe follows closely with a regulatory-led focus on ethical AI and sustainability.

Q. What emerging opportunities are anticipated in the artificial intelligence in retail market?

The market is ripe with new opportunities, including:

Expansion of immersive AI-powered shopping and virtual retail ecosystems
Growth in Asia-Pacific’s e-commerce and mobile retail markets
Rising adoption of AI-powered predictive supply chain systems
Strategic alliances between tech firms and retail giants
Development of sustainable and bias-free AI-driven retail solutions

Key Benefits for Stakeholders

The report offers a quantitative assessment of market segments, emerging trends, projections, and market dynamics for the period 2024 to 2035.
The report presents comprehensive market research, including insights into key growth drivers, challenges, and potential opportunities.
Porter's Five Forces analysis evaluates the influence of buyers and suppliers, helping stakeholders make strategic, profit-driven decisions and strengthen their supplier-buyer relationships.
A detailed examination of market segmentation helps identify existing and emerging opportunities.
Key countries within each region are analysed based on their revenue contributions to the overall market.
The positioning of market players enables effective benchmarking and provides clarity on their current standing within the industry.
The report covers regional and global market trends, major players, key segments, application areas, and strategies for market expansion. Show more