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The Retailer's Guide to 2024 - AI: From endless possibilities to tangible use cases

Right now, generative AI is one of the most dominant retail trends providing seemingly endless opportunities for retailers seeking to enhance customer experience and optimize their businesses. From chatbots for customer service, best-fit apparel technology, and personalization to supply chain optimization, enhanced upselling, and search, along with subscription services. The use cases are many. This chapter will give the insights you need to identify yours.

Despite the opportunities generative AI brings, statistics from a 2023 Gartner survey revealed that only 54 percent of AI models successfully progress from pilot stages to production. In 2024, we believe industry leaders will transition from conceptualizing the potential of AI to implementing concrete use cases. Have you found the right ones for your business?

Throughout the expo at NRF Retail’s Big Show 2024, artificial intelligence was a dominant theme, featuring over a dozen AI-specific exhibitors in the Innovation Lab and several others spread across the event. Dedicated AI sessions and statements from 
executives emphasized its pervasive presence. Attendees observed that AI had transcended beyond the hype, presenting tangible use cases and opportunities in personalization, shopper behavior, sales and service, training and talent development, as well as 
operations, and more.

"Only 54 percent of AI models move from pilot to production" - Gartner

5 things to consider before implementing AI 

As retailers increasingly embrace AI and machine learning, it’s crucial to ensure your organization is well-prepared before the implementation. Take the following factors into account:

1. Assess the necessity of AI: Determine if AI is essential for meeting your objectives, or if there are alternative approaches that could be equally effective. Don’t implement AI for the sake of it.

2. Evaluate team skills: Consider whether your team possesses the necessary expertise to effectively implement and support AI and machine learning initiatives.

3. Understand operational impacts: Analyze how integrating AI into your operations will affect your current workflows and processes.

4. Plan for integration: Develop strategies for seamlessly integrating AI capabilities with your existing systems and technologies.

5. Address data, security, and infrastructure needs: Consider the data, security, and infrastructure requirements associated with AI and machine learning implementations, and ensure you have the necessary resources in place to support them effectively.

"Don’t implement AI for the sake of it"

How to find the right AI use case

To find the right AI solution for your retail business, it’s fundamental to align the technology with your unique needs and objectives. Here’s a summarized approach to defining AI use cases tailored to your organization: 

  • Align with business goals: Start by examining your company’s overarching goals and strategic initiatives. Identify specific objectives that, when achieved, will contribute to these goals. By utilizing AI, retailers can enhance the accuracy of their demand forecasts, improving production, supply chain management, and inventory optimization. This results in reduced instances of unsold inventory, better utilization of working capital, and minimized out-ofstocks.

  • Address pain points: Directly engage with your staff to uncover the challenges they face in their daily tasks. Conduct workshops or surveys to solicit feedback and identify pain points within your organization. These insights can guide the identification of AI use cases that address these specific challenges.

  •  Keep up with market trends: Keep an eye on industry trends and developments to identify opportunities where AI can provide a competitive advantage. Analyze market dynamics, customer behavior patterns, and potential risks to pinpoint areas where AI-driven solutions can accelerate your response to industry trends.

  • Analyze competitors: Conduct a thorough competitor analysis to understand their strengths and weaknesses, particularly in areas such as revenue generation and operational efficiency. Identify opportunities where AI implementations can help your business gain a competitive edge or address gaps highlighted by competitor analysis.

  •  Utilize existing data: Explore the data your organization gathers and generates to uncover insights and opportunities for AI implementation. Analyze historical data to identify patterns, correlations, and untapped opportunities. Collaborate with data experts to build connected dashboards across business functions, enabling comprehensive analysis and gap identification. For example, the multi-national fast-fashion company Zara utilizes AI to analyze sales data and customer 
    feedback. This analysis enables the brand to identify new trends and tailor their collections to resonate with its customer base.

"I don’t think anything can replace a mom. It’s the same thing with store workers" - Anshu Bhardwaj, Senior Vice President and Chief Operating Officer of Walmart Global Technology and Walmart Commerce Technologies

Do you want to read the whole guide? It's only one click away.

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