The HFS GenAI decision matrix for retailers: Moving beyond POCs

Despite the immense potential for generative AI (GenAI) to unlock new value in retail, many retailers should work on turning that promise into reality and avoid the ‘death by 1,000 pilots’ that plagues two-thirds of major enterprises today.

Retailers are eager to harness GenAI, but they’re trapped in a ‘paralysis of analysis’— overwhelmed by the sheer number of potential use cases and unsure where to invest for the most significant impact. In our recent GenAI study, 61 retail executives across the globe stated that the ‘lack of a structured plan for GenAI use cases and investments’ is the second most significant barrier to GenAI adoption.

So, we are cutting through the noise with a no-nonsense approach—offering a clear, actionable framework to help retailers prioritize GenAI investments that deliver both short-term wins and long-term strategic advantages. Retailers need a straightforward, structured approach to assess potential opportunities. The following table highlights the top 15 leading GenAI use cases in retail, evaluated on key dimensions such as return on investment (ROI), time-to-value, spend required, IT maturity dependency, integration with complementary technologies, and governance requirements.

Exhibit 1: HFS’ decision matrix for retailers based on analysis of leading GenAI use cases

Source: HFS Research, 2024

Some quick wins to develop confidence

• Conversational chat interface: Implementing chatbots or virtual assistants can quickly enhance customer service, delivering near-immediate value. The integration with conversational AI is straightforward, with low dependency on existing IT infrastructure, making it an ideal short-term investment.
• Automated text and image creation: GenAI can streamline the creation of marketing material such as product descriptions, ad copy, and imagery, providing a high return with minimal costs. It’s a quick, low-risk win for retailers with digital channels.
• Best-fit apparel technology: Leveraging AI for accurate sizing and fit recommendations can reduce return rates, directly impacting profitability. This is especially beneficial in apparel, where returns significantly affect margins.

Strategic bets for maximum impact

• Supply chain optimization: Investing in GenAI for supply chain management will be a long-term strategic move. The return is significant but requires mature IT infrastructure. Integrated with IoT and blockchain, AI can optimize logistics, sourcing, and procurement.
• Customer-centric merchandising: AI-driven customer insights can revolutionize how products are curated for consumers. This will lead to better inventory management and enhanced customer satisfaction. Though it requires a robust infrastructure, the value derived is transformative.
• Customer behavior modeling: Understanding customer behavior through advanced AI can enable personalized shopping experiences, improve loyalty, and increase sales. This requires significant data management and governance investment but can provide a major competitive advantage.

Avoid getting into convoluted territory

• Immersive retail experiences: While the metaverse and virtual shopping environments are trendy, they are still being prepared for prime time in most retail sectors. High costs, low feasibility, and uncertain consumer adoption make this a risky short-term investment.
• Real-time dynamic pricing: While personalized pricing across channels is appealing, real-time changes in physical stores cause operational difficulties. Most retailers are not equipped to manage this yet, and the ROI is unclear.

Think along these lines while investing

• Short-term (next 12 months): Invest in conversational AI, automated content creation, and customer personalization tools. These areas offer the fastest ROI with minimal technical debt.
• Long-term (next 2–5 years): Focus on larger AI implementations such as supply chain optimization and customer behavior modeling. These initiatives will take time but provide the most significant competitive edge and value creation.
• Spend: Align spending with the complexity of the use case. Keep costs low for quick wins such as automated text creation. Strategic bets such as gas supply chain AI optimization will require more significant, sustained investments.

The Bottom Line: The GenAI decision matrix for retailers focuses on achieving early, visible, and measurable success while laying the foundation for long-term transformation with a more significant business impact.

By focusing on high-impact use cases and aligning them with business goals and technological readiness, retailers can move beyond the ‘paralysis of analysis’ to tangible, measurable outcomes. The key is prioritizing initiatives that drive immediate value and lay the groundwork for a long-term competitive advantage. GenAI can be a game-changer with suitable investments, but success depends on decisive action and smart execution.