Disrupting Retail: The Role of AI in Shaping the Industry
By Rachel Wells ’25 Associate
Retail stands as one of the largest and most dynamic industries today. Amidst the many challenges of the COVID-19 pandemic, total revenue between 2020 and 2021 surged from $6.5B to $7.3B, highlighting an impressive 12% increase. Projections indicate that by 2029, this number will soar even higher to $9.2B. This remarkable growth is propelled by several factors, including heightened consumer demand, economic expansion, pervasive social trends, and shifting demographics. However, among these fundamental drivers, another transformative force has recently emerged: that being artificial intelligence (AI). AI has significantly reshaped how retail enterprises approach their business operations and customer interactions. Indeed, for many retailers, AI serves as the driving force behind groundbreaking innovation. In this article, we’ll explore how retailers are leveraging AI to refine customer service, combat fraud, optimize inventory management, and redefine traditional commerce paradigms.
To understand the essence of this role, let’s start by defining the concept of AI. Artificial Intelligence (AI) encompasses technologies capable of problem-solving, prediction and mimicking various human processes. While many definitions exist, it’s easiest to recognize AI primarily as technology enabling data-driven decision-making, often rooted in machine learning algorithms. In the realm of retail, AI predominantly manifests through machine learning applications. This technology empowers organizations to streamline operations, enhance customer experiences, and optimize internal processes. By leveraging algorithms and data analytics, companies can allocate resources more efficiently, thereby prioritizing critical tasks and fostering productivity. A great example of AI’s transformative potential emerges from Lee’s Famous Recipe Chicken, a Midwest-based restaurant franchise. Like many in the fast-food industry, Lee’s faced challenges due to staffing shortages, impacting customer service quality. Partnering with Intel, they adopted High Auto, a conversational ordering system designed to automate drive-through interactions and boost labor efficiency. This innovative solution seamlessly engages customers, processes orders, offers recommendations, and addresses customer questions. In the pilot phase, High Auto achieved outstanding results, boasting a 95% order accuracy rate and completing 94% of orders without human intervention. The average order accuracy rate for humans? 84.4%. Moreover, the system significantly increased upselling, from 4% to 21%, by adeptly suggesting complementary items to customers. Another noteworthy application of AI in retail is Lowe’s collaboration with Fellow Robots’ NAVii android for inventory management. NAVii roams store aisles, promptly identifying low-stock items, mispriced products, and inventory discrepancies. This partnership exemplifies how personalized AI solutions enhance operational efficiency and customer satisfaction. In essence, personalized AI solutions offer multifaceted benefits, driving profitability, service excellence, and customer value across various industries.
With AI’s surging popularity and the shared challenges confronting retailers, it’s no surprise that 69% have reported increased annual revenue post-AI adoption, according to NVIDIA. Moreover, 72% of retailers have witnessed reductions in operating costs attributed to AI implementation. Broadly speaking, retailers pursue similar objectives through AI integration: enhancing store analytics and insights, delivering personalized customer experiences and recommendations, optimizing advertising, promotions and pricing strategies, managing stockouts and inventory, and implementing conversational AI solutions. However, companies also aim to leverage AI to address concerns related to data privacy and technological shortcomings. In line with trends across industries, new hurdles consistently emerge, prompting companies to eagerly embrace emerging technologies to navigate them effectively.
Despite its many benefits, AI remains relatively novel in the retail sector, making it challenging to distinguish best practices, ethical considerations, and potential pitfalls. Prior to AI implementation, retailers face a crucial decision: whether to deploy it in customer-facing or non-customer-facing capacities, such as in-store management or inventory control. As the adage goes, it’s a balancing act of risk vs reward, and this holds true here. Retailers adopting customer-facing AI must prioritize customer comfort, while those employing non-customer-facing applications must stay vigilant regarding data privacy and bias concerns. Customers are sensitive to how their information is handled, particularly regarding sensitive topics like purchasing habits or personal health products. For example, while a customer might not mind Target tracking their shopping preferences, they may feel differently about more intimate purchases like birth control. Similarly, instances of gender-based pricing disparities, such as the case involving Apple, can erode trust and deter customers from engaging with a brand. Such blind spots underscore the importance of cautious AI usage, despite its proven benefits for companies. Retailers must also acknowledge the potential effects of implementing AI on routine retail roles. Many employees are concerned about the possibility of layoffs. However, AI integration does not necessarily equate to job cuts; rather, it requires adaption to the restructuring of employee roles. It’s employees at companies lacking AI that should be more concerned. Such companies are likely to experience significant profit loss and place their workers at higher risk of layoffs. But by prioritizing careful consideration of AI implementation and its potential impacts on both employees and customers, retailers can navigate the evolving landscape of technology while maintaining trust and profitability.
With all this said, the integration of AI in retail has led to significant benefits such as operational efficiency, enhanced customer experiences, and cost savings. However, its adoption comes with challenges including ethical considerations and privacy concerns. Retailers must navigate these complexities while leveraging Ai’s potential to drive innovation and consumer trust. As the industry continues to evolve, a balanced approach to AI implementation, focusing on ethics, transparency and innovation, will be key to realizing its transformative impact on retail.
Rachel is a junior from Bow, NH pursuing a degree in Business Administration with a focus in management. Outside of the Fund, she spends her time working alongside fellow faculty, students and staff in Paul’s DEI Working Committee. She also works part-time as the Creative Director and Manager of Data Analytics for the Phinney Team at Keller Williams Realty. Additionally, she is a member of several UNH wide organizations, including UNH CHAARG, NH Youth Movement, and the CatPack Captains. She is very much looking forward to her third consecutive semester in the Fund and is excited to collaborate with her latest colleagues!
