Yahoo Lifestyle AI in Retail: The Questions Every Retailer Should Ask Before Investing
Artificial intelligence, and now generative AI, has rapidly transformed the business landscape, particularly for retailers navigating changing consumer expectations, supply chain complexities, and operational inefficiencies. The global AI in retail market was valued at $7.14 billion in 2023 and is projected to grow at a staggering 31.8 percent compound annual growth rate, reaching $85.07 billion by 2032. However, the key to leveraging AI effectively isn’t simply adopting the technology — it’s about asking the right questions.
As a partner at global professional services firm Forvis Mazars, I advise retailers to shift their focus from whether they should implement AI to how they can solve specific challenges using AI. With risks, investments, and ethical considerations to weigh, the right questions can determine the success of AI initiatives.
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Start With the Problem, Not the Technology
One of the biggest mistakes retailers make is rushing to implement AI without a clear understanding of the problem they’re trying to solve. While it’s tempting to follow competitors into AI adoption, blindly applying the technology can lead to wasted resources and missed opportunities.
Instead, retailers should ask themselves:
What specific challenge are we trying to address?
Can AI offer a solution that’s more efficient or effective than current methods?
For example, a retailer struggling with high product return rates might use generative AI to improve product descriptions or deploy virtual try-on tools to set better customer expectations. These targeted applications of AI can yield tangible results, but only when anchored in a well-defined problem.
Data Readiness: The Foundation for AI Success
The extent of AI’s effectiveness depends on the quality of data inputs. Yet many retailers face challenges with fragmented, siloed, or inaccurate data. Clean, well-structured data is essential for AI to provide meaningful insights.
Retailers must consider:
Do we have access to clean and accurate data?
Are our departments collaborating to share data effectively?
For instance, connecting demand data from sales teams with manufacturing operations can help retailers predict trends, reduce waste, and streamline inventory management. However, if the underlying data is flawed or disconnected, AI’s insights may lead to poor decisions and inefficiencies. Companies should look to establish data owners who have accountability for ensuring clean and accurate data. Data ownership along with an established and consistent data management process will help ensure quality reporting outputs.
Balancing Investment With ROI
AI requires a significant upfront investment, from implementation to ongoing maintenance. Measuring its ROI isn’t always straightforward, especially for newer applications like generative AI.
Retailers should shift their focus from short-term cost savings to long-term value creation. Instead of asking, “How much will this save us?” they should ask, “How will this improve our operations, customer experience, or competitive edge?”
Take AI-powered customer service chatbots, for example. While they reduce the need for large call centers, their true value lies in enhancing customer satisfaction and freeing up employees for higher-value tasks. Success depends on identifying measurable goals — such as improved conversion rates or reduced returns — and aligning AI investments with strategic priorities.
Navigating Risks and Ethical Considerations
AI adoption comes with risks, including data privacy concerns, content ownership issues, and potential biases in AI-driven decisions. These challenges make it critical for retailers to establish ethical guardrails and help ensure accountability for AI-generated outcomes.
Retailers need to ask:
How do we safeguard customer data used in AI models?
Who is accountable for decisions made based on AI insights?
For example, a retailer automating customer interactions with AI-powered recommendations must check that customer data is handled responsibly and that the AI doesn’t unintentionally reinforce biases or inaccuracies. Ultimately, businesses — not AI — must own the decisions and their outcomes.
Leadership and Vision Are Critical
The success of AI in retail isn’t just about technology — it’s about leadership. Strong leadership teams can guide AI adoption with a clear vision, helping to ensure it aligns with organizational goals and fosters a culture of innovation.
AI isn’t a onetime initiative; it’s an ongoing journey that requires adaptability and collaboration across departments. Leaders must champion this transformation by breaking down silos, encouraging cross-functional teamwork, and prioritizing initiatives that deliver real value.
Retailers are standing at a crossroads with AI. The technology offers unprecedented opportunities to enhance operations and customer experiences, and stay competitive in a rapidly evolving market. But its success hinges on asking the right questions: What problem are we solving? Is our data ready? What risks do we need to manage?
The goal of AI isn’t just to reduce costs — it’s to solve meaningful problems and create long-term value. Retailers that approach AI with this mindset will be well-positioned to thrive in the future.
Julie Petit is a partner at Forvis Mazars.
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