AI Can’t Replace Merchandisers, But It Can Supercharge Their Value
Zohar Gilad is cofounder and CEO of Fast Simon.
gettyI recently came across this McKinsey research from 2020: 52% of all retail activities can be automated. At first glance, that sounds like a justification to reduce headcount, especially given the improvements in automation technology since this research was published.
But dig a little deeper, and you’ll see more to the story, especially in merchandising.
Yes, AI is changing how merchandisers do their jobs. This is especially apparent at entry level, where junior merchandisers spend much of their time completing manual tasks like data entry.
But successful merchandising also involves a lot of judgment, which is where humans still outshine AI.
What agentic AI can do is act as a force multiplier for transferable skills. Instead of replacing merchandisers, AI removes bottlenecks and gives time and control back to brand teams.
The merchandiser still decides what matters, but AI handles the volume.
In merchandising, every operational task falls into one of two buckets: inspiration or execution.
Inspiration is the human domain. This includes what can’t (yet?) be calculated by an algorithm: taste, brand essence and qualitative judgment. How do you inspire a customer to click on a product? How do you manifest the essence of a brand? Indirect effects and inspiration are harder to measure.
These questions are where human judgment is valuable and where merchandisers are essential.
The other bucket, execution, is where automation makes a difference. AI can handle the millions of real-time micro-decisions, like product ranking and inventory adjustments, that human merchandisers can’t manage consistently at scale.
A human merchandiser couldn’t possibly create a personalized virtual storefront for every shopper that visits their brand’s website, but AI can do that quickly.
The teams that learn to use AI for execution will have more time to focus on inspiration.
Across my conversations with D2C retail teams, the same bottleneck comes up: Merchandisers know what they want to do, but they don’t have the bandwidth to execute every idea.
That’s where AI can make the biggest difference. My company, Fast Simon, builds AI merchandising tools for e-commerce brands. But AI can act as an extension of the merchandiser’s team regardless of the tool used.
Natural-language AI assistants make this easy. A merchandiser could prompt, “Prioritize waterproof outerwear for New England shoppers this weekend, especially green and black raincoats, but protect highly rated products from discounting,” and the AI assistant would set rules to follow during the promotion period.
The merchandiser can express a business objective in merchandising language without waiting for a technical team to translate it.
AI tools can also streamline workflows for campaign rollouts. From strategy to design, many steps lead up to a campaign launch, and merchandisers often need to rely on other teams for data or assets to ensure a successful rollout.
AI can reduce the number of steps and make workflows quicker. Instead of waiting three days for the design team to create a campaign image, the merchandiser could describe the image they need to an AI tool. The tool would generate an image, and the merchandiser would have the assets they need in seconds.
AI frees up a merchandiser’s time, so more meaningful work, like the ongoing merchandising of collections, special promotion planning and holiday sales preparation, can move off the back burner.
Turning complete control of merchandising over to an AI tool is a brand disaster waiting to happen. A human-in-the-loop approach ensures that merchandising decisions preserve the brand.
1. Protected “Islands”: Merchandisers can reserve dedicated, high-visibility areas on their site exclusively for human curation. They might manually curate a flagship product page, seasonal collection or holiday campaign, while AI optimizes the rest of the catalog.
2. Objectives: Merchandisers can guide AI’s underlying logic based on real-time business targets, directing it toward the outcome that matters most. That might mean it optimizes based on goals for top-line revenue during a major campaign launch or prioritizes inventory liquidation at the end of a season.
3. Guardrails: By setting parameters that AI must operate within, merchandisers can better ensure that AI doesn’t act against the brand without needing to review each of its decisions. They might direct the AI assistant to order a product page by color or prohibit it from discounting products with a 4.5-star rating or higher.
Each of these levers can be adjusted up or down, depending on how much control a merchandiser does or doesn’t want to allow their AI tools. The goal is to give merchandisers the freedom to determine where human judgment matters most.
Just because AI is handling more of the execution doesn’t mean the role of the merchandiser is obsolete. Their expertise is irreplaceable, but where they create value is changing.
AI can handle product ranking decisions, create personalized storefronts and adjust promotions according to inventory levels, so merchandisers spend less time on manual tasks. With those items off their plate, they can focus on the customer experience, which is the core of every retail brand.
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