Artificial intelligence (AI) matters for convenience-store category managers because they face faster cycles, more SKUs and tighter margins.
This insight comes from Sid Kulkarni, vice president of data and AI at Temple, Texas-based McLane Co., who spoke Feb. 25 at CSP’s Convenience Retailing University in Austin, Texas.
He added that AI is now embedded in everyday enterprise tools. Kulkarni said the challenge is separating hype from tools that deliver daily impact.
“AI augments category managers,” he added. “It does not replace them.” In addition, AI accelerates insight, but judgment stays human—and success depends on trust, governance and data quality, he said.
With category managers having to make increasingly complex decisions in today’s ultra-fast-paced marketplace, relying on strategies and technology from the 1990s and early 2000s will not work, he said.
“Decision-making processes require a balance of historical sales data, years of personal expertise and an instinctive grasp of consumer purchasing behaviors,” Kulkarni said. “We are witnessing a major shift as artificial intelligence becomes an integral partner to category management teams, giving them new tools to enhance their proven capabilities and talents.”
AI isn’t just using online chatbots, it’s used to create tools that actively inform complex decisions and evaluate scenarios based on massive amounts of data, giving category managers access to differentiated insights at-scale, he said.
The goal is increased revenue, a bump in profitability, better end-to-end outcome for retailers and their customers and increased customer loyalty, he said.
AI excels at analyzing consumer trends and market changes at a previously unattainable scale, Kulkarni said.
“It can identify patterns and make connections we may otherwise miss,” he said.
With AI as a powerful analytical engine, category managers can now combine more up-to-date insights with their intuition and expertise, he said.
For example, leading consumer-packaged goods companies are using AI to refine their consumer decision trees, enabling more targeted marketing and increased sales.
Kulkarni mapped out a day in the life with AI:
- Morning: AI flags underperforming SKUs and margin risk
- Midday: Scenario testing for promotion or price changes
- Afternoon: Supplier conversations backed by data
- End of day: Fewer reports, clearer decisions
“Better segmentation provides a clearer understanding of consumer needs and shopping patterns,” he said.
AI helps ensure that data sets are consistently updated with the latest schemas and taxonomies, he said. In addition, as new products emerge, they can be effortlessly integrated into existing frameworks.
“Modern category management requires a fundamental shift in how retailers approach their space and inventory decisions,” he said. “This acceleration ensures category strategies reach stores while opportunities are still relevant, driving better sales performance and customer satisfaction.”
Members help make our journalism possible. Become a CSP member today and unlock exclusive benefits, including unlimited access to all of our content. Sign up here.