Hello everyone! Are you interested in developing an AI shopping assistant app? If you are, this is the best blog for your concern because you will get everything about the app in this guide.
The AI shopping assistant app is a very trending and helpful application for prospective users and businesses. If you are a business man who wants to generate money by making such an app then this is the best decision for you because this AI shopping assistant app will help you and your audience. With the help of this app, you can generate a good amount of money by using multiple revenue models.
In this blog, you will discover about AI shopping assistant apps like what it is, features, development process, cost estimation of this app, revenue models and what technologies are required to build AI shopping assistant app.
But before discussing all of these things, we cover some realistic market stats and facts which will help you make AI shopping assistant app development decision more confidently and practically.
So let’s start with some amazing market figures.
AI Shopping Assistant Market Forecast 2025
According to MarketResearchFuture, the market size of Intelligent Personal Assistants was valued at USD 9.5 Billion in 2024. The Intelligent Personal Assistant market industry is projected to grow from USD 88.6 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 32.10% during the forecast period (2024 – 2032). Increased adoption of smartphones and integration of advanced technologies in virtual systems are the key market drivers enhancing market growth.
AI shopping assistant apps will boom, as the market is expected to grow significantly from 2025 to 2030, based on advanced technology and higher customer demand in retail for personalized experiences.
Market Growth
The global retail AI market, including shopping assistant applications, is expected to increase at a compound annual growth rate (CAGR) of around 23% over 2025-2030, reaching approximately $40.74 billion by 2030. These facts and figures are supported by growing AI adoption in customer personalization, virtual shopping experiences, and retail operations automation.
Key Drivers
The main drivers are the growth of e-commerce, an increased penetration rate of smartphones, and the growing usage of digital assistants, such as chatbots and voice assistants. AI contributes to consumer behavior analysis and provides detailed product recommendations for streamlined shopping experiences.
Technological Trends
NLP would grow faster as AI systems could effectively understand and respond to customer inquiries. Machine learning remains the most dominant in predictive analytics and personalization.
Regional Insights
North America will spearhead market revenue due to high adoption rates of AI technologies in the U.S. and Canada. On the other hand, the Asia-Pacific region will likely experience the highest growth during the forecast period due to the extensive growth of the e-commerce market in China and India.
Read More: Video Shopping App Development
What is the AI Shopping Assistant App?
An AI Shopping Assistant App is a smart mobile or web application that is designed to enhance users’ shopping experience. Powered by Artificial Intelligence (AI), this functionality will help users find relevant and preferable products, compare prices, and get personalized recommendations based on users’ preferences and shopping history.
The app can also include some advanced features like voice search, chatbots, and augmented reality (AR) to make shopping more convenient and engaging from the user’s perspective. By understanding user behavior and preferences, the AI Shopping Assistant app acts like a personal shopper, helping users save time and make better purchasing decisions.
It’s one of the powerful tools for both consumers and businesses, bridging the gap between technology and seamless shopping.
Features to be Considered in AI Shopping Assistant App Development
AI shopping assistant apps have to be user-friendly and highly functional. Here, we cover all the features that are really important to consider during the development of the AI shopping assistant app. With the integration of these features, you can create a high-performing AI shopping assistant app.
Order Tracking
Order tracking is the finest feature of these apps because it offers live tracking of orders to keep users updated on their delivery status. With the help of this feature, users can track their orders efficiently and get regular updates on their order status.
Visual Search
The visual search feature is very helpful in these kinds of applications because it enables users to upload images and find similar products using AI-powered image recognition technology. This feature makes the searching part easier for users; they just have to scan and upload a similar product, and they find the related products within a minute.
Augmented Reality (AR)
Augmented reality (AR) is the most powerful AI feature, which is quite essential nowadays because, with the help of this feature, users are allowed to virtually try out products like clothes, accessories, or furniture to enhance and streamline their shopping experience.
Real-Time Notifications
Real-time notifications are one of the important features of such apps because, with the help of this feature, users get alerts about discounts, sales, or when a saved product is back in stock to keep users engaged. So, integrate this feature into your app first.
Personalized Recommendations
Personalized recommendations are the base feature of this AI shopping assistant app because it uses AI to suggest products based on user preferences, shopping history, and behavior for a customized experience. This feature is essential for these kinds of applications, as it helps users and businesses a lot.
Note: In addition to AI shopping assistant apps, businesses that explore many innovations in app development can also benefit from party planning app development insights, which similarly rely on AI for enhanced user experience, personalized recommendations, and seamless planning solutions.
Voice Search and Assistance
The voice search and assistance feature is important because it allows users to search for particular products or get shopping help using voice commands, making the app more accessible and convenient. Users can search for any product at any time via the voice search assistant feature.
Note: While cutting down the costs and features that the AI-based shopping assistant mobile apps offer, businesses interested in developing an online book-purchasing mobile app could take advantage of AI-driven facilities like personalized recommendations, voice search, and smart categorization for the convenience of customers.
Smart Chatbots
The smart chatbot feature is quite advanced and efficient because it integrates AI chatbots to provide instant answers, assist with product queries, and guide users through the shopping process. This feature helps users to answer their questions or queries and solve their problems.
Multilingual Support
Multilingual support is the most helpful feature for users and businesses from both perspectives. This feature includes multiple language support to make the app accessible to people of every language type. Users can set the language according to their preferences, and they can access the entire app in that particular language.
Price Comparison
Price comparison is also a quite recognized feature because it helps to compare prices of products across different platforms, helping users make informed decisions. This feature is easy to use; users just need to upload the image, and the app shows the exact prices of the product.
Wishlist and Favorites
Wishlist and favorites features allow users to save their favorite items and products or create wishlists for future purchases. Users can easily save their favorite products for future shopping, and they can also manage their wishlist by adding and removing the products.
Secure Payment Options
Secure payment options are also the best feature, which allows users to do multiple secure payment gateways for hassle-free transactions, ensuring user trust and convenience. This feature is useful for users to make their payment things more easily and secure.
Explore More: Grocery shopping delivery app Development
AI Shopping Assistant App Development Process
Let’s discuss the most important topic of the blog: the AI shopping assistant app development procedure. If you want to develop AI shopping assistant app, then these simple and easy steps will help you. You just need to follow these steps while developing the app. Here’s a simplified step-by-step development process for AI shopping assistant app:
Requirement Gathering
At the initial time, you have to gather all essential requirements and understand the app’s purpose, target audience, and must-have features like product search, recommendations, voice assistance, and many more.
Design & Prototyping
After gathering all the requirements, you have to design the app with the hired app development company. The designers will create a user-friendly design and develop prototypes to visualize the app’s look and feel before starting development.
AI Model Integration
After design and prototyping, AI developers will work on AI model integration. They build and integrate AI features like recommendation systems, NLP for chatbots, and image recognition for visual search.
Development & Testing
After completion of AI model integration, your hired professionals will develop the app’s backend and frontend, and after the entire AI shopping assistant app development, the testers will ensure everything that the app works smoothly through rigorous testing.
Launch & Maintenance
In the last step, the app is ready to launch, and your mobile app development company will deploy the app on app stores or web platforms. Then, with the time and current demand, they provide regular updates and support to enhance user experience.
AI Shopping Assistant App Costs: What to Expect?
The mobile app development cost will depend on multiple factors like the apps’ complexity, features, tech stack, and development team location and experience. All these factors affect the overall cost of AI shopping assistant app development.
- The basic app includes simple features like product search, basic recommendations, and user authentication, which cost relatively less.
- An advanced app includes personalized recommendations, voice assistance, and payment gateway integration, requiring a higher budget.
- Meanwhile, a complex app with more advanced features, such as real-time NLP-based chatbots, augmented reality (AR) shopping experiences, and multi-platform support, demands significant investment due to advanced technologies and specialized expertise.
Here, we make an estimated cost table for better understanding. The cost breakdown is based on developer roles and app complexity:
| Role | Basic App | Advanced App | Complex App |
| Project Manager | $3,000–$5,000 | $5,000–$8,000 | $8,000–$12,000 |
| UI/UX Designer | $2,000–$4,000 | $4,000–$6,000 | $6,000–$10,000 |
| Backend Developer | $5,000–$8,000 | $8,000–$15,000 | $15,000–$25,000 |
| Frontend Developer | $4,000–$7,000 | $7,000–$12,000 | $12,000–$20,000 |
| AI/ML Developer | $8,000–$12,000 | $15,000–$25,000 | $25,000–$40,000 |
| Mobile App Developer | $6,000–$10,000 | $10,000–$18,000 | $18,000–$30,000 |
| QA Engineer | $3,000–$5,000 | $5,000–$8,000 | $8,000–$12,000 |
| DevOps Engineer | $2,000–$4,000 | $4,000–$6,000 | $6,000–$10,000 |
| Total Cost | $33,000–$55,000 | $58,000–$98,000 | $98,000–$159,000 |
Note: When you are going to develop AI shopping assistant app, you have to discuss the cost estimation with your choosing one of the best app development companies or hire mobile app developers.
Revenue Strategies for Sustainable Growth
As there are many revenue models available in the market, you have to choose the best one or two or more according to your application and your requirements. These models help you generate money through the app, and with the help of these monetizing strategies, you earn a good amount of money.
Subscription Plans
The subscription plan is the best revenue model because, in this model, users have to pay a monthly or annual fee for premium features like personalized shopping recommendations, exclusive deals, priority customer support, and many more.
Affiliate Marketing
Affiliate marketing is also an ideal choice as a revenue model because, with the help of this strategy, app owners can earn a fixed commission by directing users to partner e-commerce platforms or brands when anyone purchases products through the AI shopping assistant app.
In-App Advertising
In-app advertising is also a better one because in this revenue model, app owners are allowed to display ads from third-party advertisers, such as product promotions or brand campaigns, and they can generate revenue through impressions or clicks.
Freemium Model
The freemium model is the effective revenue model because the app offers basic features for free, but if users want to access the entire app with advanced features, then they have to pay money for advanced functionalities like voice shopping or AR product previews.
Partnership with Brands
Partnerships with brands are the fastest revenue model because app owners have to collaborate with brands to promote their products directly on the AI shopping assistant app through exclusive partnerships or featured listings.
AR/VR Shopping Experiences
AR/VR shopping experiences are the catchy revenue model because they offer virtual shopping experiences as a paid service to retailers to showcase their products to users interactively. This is gonna be an attractive revenue model.
Technologies Use in AI Shopping Assistant App Development
These core technologies are used to develop secure, reliable, and user-centered AI shopping assistant apps. Here’s a table for your consideration which highlights essential technologies for AI Shopping Assistant App Development:
| Category | Technology/Tool |
| Programming Languages | Python, JavaScript, Kotlin, Swift |
| Frameworks | TensorFlow, PyTorch, Scikit-learn |
| React Native, Flutter | |
| Node.js | |
| AI & ML | OpenAI API, Hugging Face, Dialogflow |
| Google AI, Amazon SageMaker | |
| Cloud Services | AWS, Google Cloud, Microsoft Azure |
| Firebase | |
| Databases | MongoDB, PostgreSQL, MySQL |
| Elasticsearch | |
| APIs | Shopify API, WooCommerce API, Amazon MWS |
| Stripe API, PayPal API | |
| Front-end | HTML5, CSS3, JavaScript, React |
| Data Processing | Apache Kafka, Apache Spark |
| DevOps | Docker, Kubernetes |
| Jenkins, GitHub Actions | |
| Analytics | Google Analytics, Mixpanel, Amplitude |
| Security | OAuth 2.0, SSL/TLS |
| Cloudflare |
Note: This table highlights essential tech stacks with all different aspects of development, ensuring a robust and feature-rich AI Shopping Assistant App.
Nutshell
Well, well, well, this blog is at its end, and hopefully, you are satisfied with the guide, and you get answers to your questions or queries. By framing this blog, we just want to clear your confusion to create AI shopping assistant app. As we discussed in this guide, we cover all the things that are really important to know for businesses that want or are thinking of developing AI shopping assistant apps.
If you literally make up your mind to build AI shopping assistant app, then you have to choose the best IT app development company that can provide all app development services with quality work and development.
You can connect with our (Octal IT Solution) professionals for your AI shopping assistant app development requirements. Our expert developers will develop exactly what you demand at the most affordable price. Our experts are experienced in their work, and similar to these apps, they have already successfully delivered the applications.
So don’t wait. Connect now for further discussion.
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