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The retail marketing industry is awash with artificial intelligence (AI) hype \u2013 much of it vague, speculative or fear-driven.<\/p>\n
According to WARC, 59% of marketers now worry about disruption from AI, up from 27% in 2023.<\/p>\n
With pressures to balance brand and performance, manage campaigns across multiple channels and prove ROI, retail marketers are being challenged not just to understand AI, but to make it work within existing workflows without slowing operations.<\/p>\n
But what does implementation of the tech actually look like for retailers?<\/p>\n
From creative development and campaign testing to market research, stock management and decision support, we asked retail marketing leaders and experts to share concrete examples of how AI should be applied, and what measurable impact it has had on efficiency, costs and results.<\/p>\n
Workflows that have been automated and the measurable change they have delivered<\/strong><\/p>\n The biggest AI marketing gains for retailers have come from using the technology as a practical co-pilot.<\/p>\n This much is true for Giulio Beltramo, head of marketing at multinational retailer and brand owner One Retail Group, who trains models to understand what works for his marketing team, why it works and the context in which it works.<\/p>\n \u201cAI has become an extensive valuable companion to bounce ideas off, validate hypotheses against real-world data, research at scale in a cost-effective way and get back a whole lot of information that can prompt further questioning and discovery,\u201d he says.<\/p>\n One Retail Group\u2019s established AI workflows also feed into its creative development teams. While imagination is the limit with their AI stack, Beltramo notes that implementation comes with effort.<\/p>\n \u201cPrompting campaign-level assets or assets we feel comfortable listing on our product pages takes hours of iterations and extensive prompting,\u201d he adds. \u201cFurther to this, using two or three tools is often necessary when delivering a final asset.\u201d<\/p>\n The payoff, however, is substantial.<\/p>\n AI allows the team to experiment with lower risk, develop creative variants faster, and ultimately reduce costs. \u201cOver the past few months, we have been able to run variants on creative, try new looks and feels, and truly define the brand and visual direction we want to go in,\u201d Beltramo says.<\/p>\n \u201cThis was done at a lower risk, lower cost, and we were able to develop and test more variants quicker, resulting in better performing creatives, reduced cost per click (CPCs) and cost per action (CPAs), and clearer insight into brand direction through metrics like view-through rates and engagement.\u201d<\/p>\n For Fran Bridgewater, marketing director at Drinks Network, which works with a host of wine retailers, the clearest gains in AI implementation are in marketing and communications. AI is saving time, sharpening targeting and helping safeguard authenticity.<\/p>\n \u201cAI drafts product descriptions, social media captions, email copy, and regional campaign variants,\u201d Bridgewater says. \u201cFocused on speed and consistency rather than replacement, these tools cut repetitive work and free small teams for higher-value trade, brand and strategic activities.\u201d<\/p>\n With AI now in the fold, production and campaign turnaround is 30-40% faster for UK boutique wine producers associated with Drinks Network. \u201cIt\u2019s enabled more consistent output and emerging conversion gains from clearer messaging and better audience targeting,\u201d says Bridgewater.<\/p>\n According to Phil McMahon, retail and engagement strategist at Really Good Culture, the marketers most likely to benefit from AI are those using agentic tools to remove friction for shoppers navigating AI-powered search.<\/p>\n \u201cAt the end of the day, retail marketing is about driving conversion and improving availability and reducing friction are effective ways to do that,\u201d McMahon says.<\/p>\n \u201cThese automations also improve availability for shoppers, which is a key driver of satisfaction and loyalty. All of this is of growing importance in an increasingly omnichannel retail landscape,\u201d he says.<\/p>\n The guardrails that are essential for keeping brand risk low<\/strong><\/p>\n Using AI for research purposes is a must for retail marketers, but Beltramo cautions that generative AI often tells you exactly what you want to hear.<\/p>\n For him and One Retail Group, the research is only as good as the interrogation you do of it.<\/p>\n \u201cGet a tool that shares the sources of its research and actually check them,\u201d Beltramo adds.<\/p>\n \u201cAsk it \u2018why have you given me this answer\u2019 or \u2018rate this response out of 10 and iterate on your answer\u2019. You have to be vigilant and assume a bias.\u201d<\/p>\n With regards to using AI to aid creative, strong brand and visual guidelines are required to ensure that the vision of the brand does not get lost in the prompting phase.<\/p>\n \u201cWhen creating using AI you almost have three brains involved,\u201d Beltramo says.<\/p>\n \u201cThe brain of the campaign creator, the brain of the person executing or prompting, and then AI\u2019s brain. If you say, \u2018create a picture of a dog\u2019, each three of those brains are going to imagine a different dog.\u201d<\/p>\n Bridgewater echoes this sentiment, admitting that AI-assisted outputs must be rigorously reviewed.<\/p>\n \u201cRetailers have to protect brand voice, provenance, and technical accuracy, especially under strict appellation rules,\u201d she says.<\/p>\n \u201cWith regards to branding and copywriting, AI doesn\u2019t always deliver, fully automated tasting notes often lack personality and sense of place.\u201d<\/p>\n Human oversight is paramount, agrees McMahon, as AI systems do not guarantee 100% accuracy. Automation should be reserved for flagging issues as opposed to being responsible for judgment calls.<\/p>\n \u201cDespite the hype, it\u2019s still early days for AI in retail and new problems and failures will arise as the technologies scale,\u201d he adds.<\/p>\n \u201cAI is the hammer, not the blacksmith. Human oversight of AI automation will mitigate blind spots and help maximise its benefits, and this should ultimately be reflected in shopper feedback and the retailer\u2019s bottom line.<\/p>\n Lessons learnt along the way<\/strong><\/p>\n At One Retail Group, Beltramo is clear that his team is still learning how to work with AI and where it can add the most value. He likens AI to being the coach or assistant to a sprinter, not the sprinter itself.<\/p>\n \u201cThe marketer in this situation is the runner,\u201d Beltramo adds.<\/p>\n \u201cI would always recommend that you as a marketer still have to do the actual hard work in order to get AI to take your work to the next level. It will get you that much further, that much quicker, but you still need to put in the work.\u201d<\/p>\n Similarly, for Bridgewater the lesson is clear: AI works best as a trusted assistant.<\/p>\n \u201cStart with bottlenecks, prioritise small wins, keep humans in the loop, and track outcomes rigorously,\u201d she says.<\/p>\n \u201cThe retailers we work with that are embedding AI across content, data, decision-making and customer experience are already turning experimentation into a tangible competitive advantage.\u201d<\/p>\n