“Those who embrace technology will win,” said Richard Taylor, senior manager, strategy & consulting (energy, mobility retail) at Accenture during his “Fueling the Future: AI-Powered Value for Fuels & Convenience” session at the 2025 Conexxus Annual Conference, held this week in Tucson, Arizona.

“The narrative here is not that AI will be replacing humans, but that with AI, humans will become more powerful,” he said.

Taylor presented three practical use cases for generative AI that convenience retailers can get started with.

1. Gauging call center customer sentiment: Retailers can use AI to enhance the customer experience while speaking to customer service agents and increase customer satisfaction from the call. One of Accenture’s clients with 1,000 sites receives about 4,000 calls per month. “In order to get a sentiment analysis, you normally have to go through a good portion of those calls to understand if the customer is happy, and if not, why. It’s about 500-man hours per month. But by running them through AI, we have been able to process them and get a sentiment analysis in 15 minutes,” Taylor said. “You can see top issues people called in with, how the agent handled it and how the customer is feeling at the end of the interaction. The rich data provided allows retailers to take these insights and drive better results.”
2. Personalizing offers to customers: In Argentina, Accenture is testing AI analysis that will help retailers learn more about their consumers so they can give them better experiences. “We're able to leverage video and camera footage to understand a whole host of different information and data points about a customer profile. When a car pulls into the forecourt, does the customer have children? What's the mood of the person when they turn into the site? How much will they want to spend based on the look and feel of their car? What’s the weather outside? All of these data points come together in a matter of seconds as a car approaches the pump,” Taylor said. That information can then be used to present the best product offer or promotion to that customer at the pump to convert them into the store.
3. Forecasting fuel demand: Many factors contribute to how much fuel a retailer needs to order, and AI can make those calculations more precise, said Taylor. Beyond customer data and location data related to your site, Taylor said AI can also add macroeconomic and geopolitical data and generate an analysis for more accurate fuel pricing. “In particular Microsoft Copilot is constantly monitoring all this data and can say for example ‘Your brand has lost 2% market share in southern Florida, amounting to a lost margin of $80,000,’ and will make recommendations for what to do next. It can tell you to take an aggressive pricing strategy or adjust an average of three cents across all the locations to capture increased volumes and recommend how to best manage your fuel supply,” Taylor said.

Taylor noted that while AI is quickly growing, there are still privacy concerns and education that needs to occur as retailers implement it into their business.

“There's not a one size fits all approach. Consider who your employees are, what the culture in your organization is like, how you want to tackle these new technologies and what kinds of training and skill development your employees will need,” Taylor said.