AI in Retail Industry: Real-World Applications
By: Scott Hess – Vice President of Information Services, High Company LLC and Powell Arms – Senior Vice President & Managing Director – Retail Division, High Associates Ltd.
Artificial intelligence (AI), more specifically Generative AI (GenAI), has garnered substantial attention and excitement in the past 18 months due to the introduction of products like ChatGPT, Gemini, Copilot, and DALL-E, among others. For the first time, AI in retail and other industries is accessible and comprehensible to anyone with an internet connection and a web browser. Users can engage in text-based conversations, ask questions, stimulate creativity, and edit documents without the need for programming skills.
While AI might seem like a recent innovation, its roots trace back to 1956 when a small group of scientists conducted a summer research project at Dartmouth University on artificial intelligence. Today, AI is increasingly being integrated into businesses and demonstrating its impact across all industries. According to a recent PwC article titled 'Sizing the Prize,' the global Gross Domestic Product (GDP) could grow by 14%—equivalent to over $15 trillion—by 2030, driven by the rapid development and adoption of AI. Currently, the GDP of China is ~$18 trillion, and the United States is ~$27 trillion.
The challenge for many businesses is determining how best to leverage AI applications in retail.
Understanding Generative AI and its role in the retail industry
Generative AI operates by predicting the next letter or word in text based on models trained on vast amounts of data, including publicly available information from the internet and other sources.
What sets GenAI apart is its ability to generate responses to user queries in conversational language. It can assist with creative tasks (‘how should I launch a meeting with a fun fact about AI in the retail industry’), editing text (‘create an executive summary of 500 words based on the text below’), and image generation, showcasing just a few of its practical applications.
AI use cases in retail
A recent study by Gartner, a leading technology research and consulting firm, indicates that 40–50% of retailers are using AI today — a number expected to rise. This adoption spans large chains like Home Depot and Walmart to regional and local stores.
The use of AI in retail includes sentiment analysis, providing insights into consumer behavior, preferences, and emerging trends by analyzing unstructured data from social media or review platforms. These insights shape artificial intelligence retail solutions like customer service enhancements, product development, and pricing strategies.
AI can analyze existing in-store video systems to assist staff in real-time work, for example, opening more registers if lines grow or alerting employees when a customer has waited too long at a service counter. Additionally, AI tracks shopping paths to identify traffic bottlenecks caused by displays or layout design, offering ways to improve store flow and customer experience.
GenAI also enhances consumer interaction by enabling conversational, chatbot-driven product searches. Instead of using filters, shoppers ask questions directly and receive customized product suggestions — one of the growing AI use cases in retail.
Retailers also use GenAI to:
- Develop customized marketing campaigns tailored to specific consumer segments
- Create engaging social media content and ad creatives
- Generate product images and alternative product descriptions that resonate with niche audiences
These tools demonstrate how AI is changing the retail industry — reshaping how businesses connect with consumers.
Read more about AI in Real Estate Development.
Risks and considerations when using AI in the retail industry
Despite its transformative potential, it’s crucial to remember that AI in retail market settings is still evolving. Companies must evaluate risks and limitations before full implementation.
Generative AI operates on data, but data governance matters. Sensitive information (e.g., payroll data on shared drives) could be unintentionally accessed if safeguards are weak.
The use of public data can introduce bias or copyright issues. Demographic skewing may produce biased outcomes, and lack of attribution can lead to legal trouble.
Also, using AI in retail does not eliminate the need for human oversight. Generated content isn’t always accurate — humans must verify context, intent, and alignment with business objectives.
The future of AI in retail
The future of AI in retail holds transformative potential across all industry segments. As technology matures, understanding its implications on the workforce, consumer interaction, and operational efficiency becomes critical.
A balanced, informed approach allows leaders to evaluate the benefits of artificial intelligence in the retail industry, manage risks, and harness the power of innovation to maintain a competitive edge.
FAQs about AI in Retail
1. How is AI used in the retail industry?
AI is used in retail to analyze customer behavior, personalize shopping experiences, optimize inventory, enhance customer service with chatbots, and improve store layouts through video and data analysis.
2. What are the main benefits of AI in the retail industry?
Key benefits include better customer insights, increased operational efficiency, faster decision-making, and more targeted marketing campaigns. AI also enables retailers to automate routine tasks and reduce costs.
3. What are some real-world applications of artificial intelligence in retail?
Applications include sentiment analysis on social media, automated product recommendations, dynamic pricing, fraud detection, and virtual fitting rooms powered by computer vision.
4. Is AI in retail only for large companies?
Not at all. While large chains like Walmart lead adoption, small and mid-sized retailers are also embracing AI for tasks like inventory forecasting, chatbot support, and local customer targeting, especially through cloud-based tools.