AI Shopping Assistant Market Size Is Set To Reach USD 24.90 Billion By 2032, Driven By Rising AI Adoption In Retail, Healthcare, And Multimodal Customer Engagement Report By SNS Insider

(MENAFN- GlobeNewsWire - Nasdaq) AI Shopping Assistant Market grows on rising AI adoption in retail, healthcare, and multimodal engagement, enhancing personalization and efficiency.

Austin, Sept. 02, 2025 (GLOBE NEWSWIRE) -- The AI Shopping Assistant Market size was valued at USD 3.65 billion in 2024 and is projected to reach USD 24.90 billion by 2032, registering a strong CAGR of 27.22% during 2025–2032.

Market growth is driven by retailers' increasing adoption of AI-powered solutions to enhance personalized shopping experiences, improve customer engagement, and boost sales conversion rates. Advanced AI technologies, including natural language processing, machine learning, and predictive analytics, enable intelligent product recommendations, virtual assistants, and real-time support. Rising e-commerce penetration, consumer preference for seamless online shopping, and demand for efficient, interactive, and data-driven retail experiences are further accelerating market expansion.

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The U.S. AI Shopping Assistant Market was valued at USD 1.00 billion in 2024 and is projected to grow at a CAGR of 27.00% over 2025-2032, reaching USD 6.73 billion. Growth is driven by retailers leveraging AI for personalized recommendations, enhanced customer engagement, efficient virtual assistance, and seamless online shopping experiences, fueled by rising e-commerce adoption and demand for intelligent and data-driven retail solutions.

Key Players:

• Alibaba Group Holding Limited
• Shopify Inc.
• Salesforce, Inc.
• eBay Inc.
• Google LLC
• Amazon.com, Inc.
• Meta Platforms, Inc.
• Microsoft Corporation
• Adobe Inc.
• IBM Corporation
• Perfect Corp.
• Sherpa.ai
• The Yes
• Outfittery
• Caper AI
• Uniphore
• Manifest AI
• Constructor
• Yalo
• SleekFlow

AI Shopping Assistant Market Report Scope:

Report Attributes	Details
Market Size in 2024	USD 3.65 Billion
Market Size by 2032	USD 24.90 Billion
CAGR	CAGR of 27.22% From 2025 to 2032
Base Year	2024
Forecast Period	2025-2032
Historical Data	2021-2023
Report Scope & Coverage	Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments	. By Offering (Solution, Services) . By Technology (Natural Language Processing (NLP), Machine Learning (ML), Computer Vision (CV), Others) . By Type (Voice, Text, Visual, Multimodal) . By End-use (BFSI, Retail & E-Commerce, Healthcare, Travel & Hospitality, Media & Entertainment, Others)
Customization Scope	Available upon request
Pricing	Available upon request

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By Offering, Solution Segment Leads AI Shopping Assistant Market in 2024 Driven by Enterprise Adoption of AI Tools for Personalization and Engagement

The solution segment dominated the AI Shopping Assistant Market in 2024, fueled by enterprises adopting proprietary AI tools for personalized product recommendations, virtual try-ons, and enhanced customer engagement. Retailers increasingly favor integrated platforms offering scalability, advanced analytics, and seamless omnichannel support. These standalone or embedded AI solutions improve operational efficiency, elevate user experiences, and deliver higher ROI, establishing the segment as the top revenue generator in the market.

By Technology, Natural Language Processing (NLP) Segment Dominates AI Shopping Assistant Market in 2024 with 39% Revenue Share Driven by Enhanced User Interaction

The NLP segment held the largest revenue share of 39% in 2024, owing to its capability to interpret user intent, support multilingual interactions, and improve query accuracy. NLP powers chatbots and voice assistants to provide human-like, contextual responses, and its widespread integration across platforms makes it a core technology underpinning most AI shopping assistant solutions.

By Type, Multimodal Segment Expected to Grow Fastest in AI Shopping Assistant Market with 30.53% CAGR During 2025–2032 Driven by Rich, Multi-Channel Customer Engagement

The multimodal segment is projected to record the fastest growth at a CAGR of 30.53% over 2025-2032, as brands adopt AI assistants capable of handling voice, text, images, and gestures. By processing multiple data types simultaneously, these assistants enhance personalization and create intuitive, natural interactions, meeting rising consumer demand for seamless, cross-modal shopping experiences.

By End-use, Healthcare Segment to Grow Fastest in AI Shopping Assistant Market with 29.80% CAGR During 2025–2032 Driven by Personalized Health Solutions

The healthcare segment is projected to record the fastest growth at a CAGR of 29.80% over 2025-2032, driven by adoption of AI shopping assistants for recommending supplements, wellness tools, insurance plans, and medication reminders. AI enhances patient self-service, reduces wait times, and optimizes retail pharmacy operations, while personalized product suggestions based on user data boost demand in digital healthcare commerce.

North America Dominates AI Shopping Assistant Market, Asia Pacific Expected to Grow Fastest

North America led the AI Shopping Assistant Market in 2024 with a 38% revenue share, supported by robust technological infrastructure, high digital adoption, and early investments from major retail and tech companies. The presence of leading AI developers, mature e-commerce ecosystems, and consumer readiness for personalized experiences strengthened the region's leadership in deploying AI-based retail and engagement solutions.

Asia Pacific is projected to record the fastest growth at a CAGR of 29.84% during 2025-2032, driven by rising smartphone penetration, expanding e-commerce platforms, and increasing digital literacy. Investments in AI-driven retail innovation across India, China, and Southeast Asia, along with adoption by local and global businesses, are enabling AI shopping assistants to reach a large, youthful, and digitally engaged consumer base.

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Exclusive Sections of the Report (The USPs)

• USP 1 – Consumer Behavior & Personalization Analytics

Helps clients understand shopper preferences, purchase triggers, and personalization strategies to increase conversion and engagement.

• USP 2 – Multi-Channel Integration Assessment (E-commerce, In-Store, and Mobile Apps)

Enables clients to optimize AI assistants across online and offline touchpoints for a seamless customer experience.

• USP 3 – Technology Innovation Tracker (NLP, Computer Vision, and Recommendation Engines)

Provides insights on the latest AI capabilities enhancing product discovery, virtual try-on, and personalized recommendations.

• USP 4 – Revenue & Monetization Models (Subscription, SaaS, and Transaction-Based)

Helps clients evaluate profitable business models for deploying AI shopping assistants at scale.

• USP 5 – Vendor & Platform Benchmarking

Assists clients in selecting best-in-class providers based on features, integration ease, AI sophistication, and support services.

• USP 6 – Compliance & Data Privacy Framework (GDPR and CCPA)

Reduces risk by ensuring AI assistants handle personal data responsibly and in compliance with regulations.

• USP 7 – Future Trends & Innovation Roadmap

Prepares clients for emerging trends, such as voice-based shopping, AR-enabled recommendations, and AI-driven loyalty programs.

About Us:

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