Revolutionizing Retail: How Generative AI Is Shaping The Future Of Shopping

AI styling is re-shaping the retail shopping experience in both B2B and B2C markets, one outfit combination at a time

The cross-industry integration of generative artificial intelligence is revolutionizing the way consumers shop. From personalized chatbots enhancing customer interactions to innovative idea generation for marketing campaigns, generative AI is transforming retail by disrupting it. The future of shopping is changing, not only through consumer experiences but also business practices.

AI styling is a newer retail use case for generative AI that offers both a business-to-business (B2B) and business-to-customer (B2C) application, transforming how retailers curate personalized fashion recommendations and engage with their customers. In essence, AI Styling refers to the use of AI algorithms to provide personalized fashion recommendations to customers in the retail industry.

While the prospect of venturing into the retail Gen AI space may seem daunting for entrepreneurs and businesses, data shows that the time to embrace generative artificial intelligence (AI) in retail strategy is now; According to a 2024 Nvidia study, AI adoption resulted in a boosted annual revenue for 69% of retailers surveyed while 72% saw a significant decrease in operating costs. Further, Fortune Business Insights predicts substantial growth for global AI in the retail market, forecasting a market size of $85.07 billion by 2032. These statistics underscore the impact AI can have on the retail landscape

To navigate ethical considerations surrounding AI use effectively, businesses must confront them directly

Integrating AI styling into one’s business operations can be simplified through a strategic approach. Here are 7 actionable steps to seamlessly incorporate AI styling into your business model.

Step 1 – Choose a Path: B2C, B2B, or Both

One might choose a B2C approach over B2B in order to directly engage with consumers, and offer personalized solutions, fostering strong brand loyalty. Conversely, B2B provides potential for larger contracts and scalable revenue opportunities, catering to industry-specific needs with specialized expertise. Brands like Aiuta AI Stylist offer both B2B and B2C services using AI solutions.

Step 2 – Maximize Market Impact: Leveraging Gen AI’s Competitive Advantage

If you are a retailer or brand with existing offerings, AI styling can complement your existing business. However, if you’re an entrepreneur looking to innovate in the Gen AI space, you may find success by developing AI styling as a standalone product. Companies such as Intelistyle and Fashmates offer businesses an opportunity to integrate generative AI into their existing models without building out their own AI styling systems, providing a competitive advantage.

Data shows that the time to embrace generative artificial intelligence (AI) in retail strategy is now

Step 3: Choosing Your Path: In-House AI or Third-Party Solutions

In contrast to third-party solutions like Intelistyle and Fashmates, proprietary AI models can also provide advantages depending on your business model. Stitch Fix’s Outfit Creation Model (OCM), trained on millions of curated outfits, is able to generate millions of new outfit combinations daily. If one’s goal is market differentiation, then Stitch Fix’s approach to AI integration, which has been in-house since its inception, might be more suitable. Developing proprietary AI styling creates the opportunity for full control and ownership over AI-generated data and seamless integration with existing systems.

Step 4: Balancing Input: Stylist Input, Customer Input, or Both

Businesses can decide to incorporate stylist input, customer input—or both—into their AI development process. For those aiming to create a sophisticated AI styling tool, leveraging both stylist expertise and customer insights, such as past purchases and trend preferences, may be advantageous. This balanced approach ensures comprehensive data integration and enhances the tech’s ability to deliver personalized styling recommendations tailored to individual preferences.

Step 5: Setting the Metrics: Key Performance Indicators (KPIs)

Once AI styling is integrated into a business model, monitoring key performance indicators (KPIs) is essential to ensure goal attainment. For customer engagement, one should consider conversion rates, subscription enrollments, and customer retention, while comparing AI-styled recommendations to non-AI interactions. In terms of tech performance, seek to test recommendation accuracy, gather customer satisfaction scores on the AI styling experience, and quantify time saved by customers compared to manual methods.

Step 6: Ensuring Excellence: Implementing Quality Assurance

To uphold quality standards in AI styling, it’s important to implement AI performance metrics. Additionally, continuous refinement of recommendation algorithms, enhancement of image recognition capabilities, and provision of user-friendly interfaces are essential practices.

For those aiming to create a sophisticated AI styling tool, leveraging both stylist expertise and customer insights may be advantageous

Step 7: Embracing Ethics

To navigate ethical considerations surrounding AI use effectively, businesses must confront them directly. Establishing internal policies early on to govern the ethical use of AI, mitigating bias, and proactively communicating with customers about AI usage and potential biases are essential steps toward fostering transparency and trust.

By implementing these 7 steps, entrepreneurs can take proactive steps towards revolutionizing retail AI integration. Artificial intelligence will remain a powerful force for transforming retail, shaping the future of shopping, and driving innovation in the industry, making it critical for entrepreneurs to harness its potential.

Saron Bizuayehu ’24 is an MBA Graduate of Columbia Business School. Before her MBA, Saron held a diverse set of roles at Fannie Mae, focusing on business analysis, project management, and ESG portfolio management. She also has experience as a shoe entrepreneur and in consulting for consumer products and retail.