PYMNTS Intelligence: Retailers Must Upgrade Back-End Systems to Harness AI Power and Potential

With the rise of eCommerce and the need for convenience and flexibility, retailers have turned to artificial intelligence (AI) to enhance the customer experience, with AI-powered self-service options becoming popular.

According to data captured in a recent PYMNTS study, 84% of U.S. consumers use self-service kiosks, with 66% preferring them over staffed checkouts. And although some customers still have reservations about self-service, citing a decline in social skills and a lack of meaningful connections, this preference extends across different generations, including Gen Zs and millennials.

One of the main drivers behind the rise of self-checkout options is customers’ aversion to waiting in lines. In fact, Americans spend an estimated 37 billion hours waiting in line each year, with retail stores being the primary location.

It is no surprise then that 82% of consumers actively avoid businesses with any length of line and have turned to self-service kiosks offering a faster and more convenient checkout experience.

Autonomous retail technology company Standard AI is one of the firms looking to cash in on the trend, recently announcing the use of Google Cloud’s Vertex AI tools to improve checkout. The company is also getting access to Google Cloud’s generative AI, point-of-sale (PoS) capable assisted, and large language model (LLM) capabilities, which it will use it to support its autonomous checkout solution and Skip, its branded self-checkout solution.

“We’re on the cusp of an AI-powered revolution in retail, driven by the need to manage labor and inflation challenges while meeting the needs of new tech-enabled shoppers,” said Jordan Fisher, CEO of Standard AI.

Retailers Must Upgrade to Use AI

AI has emerged as a transformative technology in the retail sector, with the potential to generate efficiency gains and new revenue. The grocery industry, for example, could save $113 billion by deploying AI in both consumer-facing and back-end applications, PYMNTS has reported.

AI-powered predictive analytics, for example, can optimize inventory management and reduce the risk of overstocking or understocking. By analyzing consumer data and sales trends, predictive analytics algorithms can also forecast demand for specific products, allowing brands to adjust inventory levels accordingly.

However, retailers must upgrade their back-end systems to accommodate and harness the full potential of AI. A survey revealed that 83% of retailers can only benefit from AI after modernizing their infrastructure.

Additionally, retailers must undergo complete business transformations to fend off increasing competition from eCommerce giants.

Against this backdrop, merchants are outsourcing payments innovation to third parties as well as collaborating with FinTechs to implement new technologies efficiently and cost-effectively, especially for smaller retailers with limited resources. This collaboration allows retailers to offer a seamless omnichannel experience and personalized service.

Overall, AI holds immense potential, but retailers must upgrade their internal systems to accommodate it. Transforming in-store experiences and partnering with third-party providers can be crucial steps for merchants looking to meet customer demands and stay competitive.