- Customer service and marketing are AI’s biggest use cases in retail
- Inventory management and supply chain are a big focus looking ahead
- AI maturity is actually very low – this is a largely untapped and poised for big growth
More than two in three (70%) retailers are piloting or have partially implemented agentic AI with as many (71%) expecting the tech to help improve operational efficiency as soon as next year, according to a new Fluent Commerce report.
However, although 12% have already seen a strong impact, only 8% have fully deployed AI across their operations.
Presenting a further challenge, only 5% consider their AI systems mature and optimized, but plenty of other hurdles stand between retailers and successful AI deployments.
Retailers are optimistic about agentic AI
The figures show that 88% of retailers acknowledge agentic AI’s role in keeping them competitive against rivals, but ethical/regulatory concerns (43%), customer trust and transparency (43%), data quality and integration issues (39%) and skills shortages (36%) are holding them back from going all-in.
“Retailers are clearly investing in AI, but the journey from pilot to full-scale deployment is proving more complex than expected,” Chief Strategy Officer Nicola Kinsella comments.
At the moment, most of the AI in retail has been centered around customer service and chatbots (56%) and personalized marketing (46%) – but we could be on the cusp of major change as retailers begin to explore AI’s use across their operations.
Kinsella credited agentic AI for being able to “see the full operational picture,” for example order exceptions, processing speeds and fulfilment locations, delivery delays and more.
Nearly one-third plan to deploy agentic AI across inventory management (30%) and supply chain optimization (32%).
Not only do these new AI opportunities for retail businesses present further areas for productivity boosts, but looking ahead, retailers are clearly expecting to see more value from AI-enhanced administration rather than AI-enhanced creativity.
Leaving human workers to come up with the best strategies, AI can be left to generate useful insights and actions from existing data: “With the right data and a thoughtful rollout, retailers can capture real, measurable benefits from AI.”
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