AI reshaping retail execution, cut merchandiser time by 56%: Report

New Delhi [India], August 12 (ANI): Artificial intelligence (AI) agents are beginning to change how consumer goods companies manage retail operations, with one reported implementation cutting the time spent by merchandisers on each store visit by 56 per cent, according to a report by Effie.ai.
The report said AI is moving beyond systems that simply identify problems or recommend actions to tools that can execute parts of the retail process. These systems can help plan store visits, analyse shelves, prioritise tasks, update systems and verify whether actions have been completed.
"The shift cuts merchandiser time per visit by 56 per cent and supervisor time by 55 per cent with zero days of training needed for field staff to adopt new tasks, as the AI agent, rather than a manual, guides work in the moment," the report said.
It also claims a 2-4 per cent sales uplift linked to its platform.
The report said the shift is particularly significant for consumer goods companies because a major part of retail still takes place in physical stores. Physical stores account for approximately 79 per cent to 81 per cent of total worldwide spending, making the ability to understand and respond to what happens inside stores important for brands.
According to the report, consumer goods companies have traditionally faced limited visibility into whether products are actually available on shelves, correctly priced and displayed according to the arrangements agreed with retailers.
The report added that AI agents could help address this problem by taking over the digital part of a store visit while keeping humans involved in physical work and retailer relationships.
Ruslan Okhrimovych, CEO, Effie AI, said, "Retail Execution is moving through a fundamental architectural shift. Mobile applications digitized the visit. Image recognition digitized the shelf. Predictive AI began recommending where teams should focus. AI agents now create the possibility of executing the digital portion of the visit--planning, analyzing, prioritizing, updating systems and validating outcomes--while people handle physical work and retailer relationships".
The report said an AI agent can use information such as planograms, customer agreements, promotional calendars, store assignments, product priorities and historical execution data to make decisions within defined objectives and approval limits.
The report, however, said the market for AI agents in retail is still at an early stage. While AI-based perception and recommendations have become relatively mature, autonomous closed-loop execution remains a differentiator.
It said the key measure of value is increasingly how quickly an AI-generated insight can be converted into verified action.
The report also cautioned that companies should begin with clearly defined and measurable workflows before expanding the level of AI autonomy.
It recommended establishing a baseline, connecting the agent to relevant systems, validating actions and gradually moving towards coordination between specialised AI agents. (ANI)