Ever since Mango started to use Smartly, an AI-driven performance marketing tool, for social media ads, its revenue generated by these ads has quadrupled. <\/p>\n
Using the platform, Mango\u2019s design team is able create brand templates that can be easily toggled between different versions of a photo of a dress, for example. Whereas before, creating different images required taking photos of different outfits in multiple settings.<\/p>\n
The womenswear brand is far from the only fashion player to have figured out how to use artificial intelligence to optimise and boost the efficiency of advertising. Companies including sneaker retailer Foot Locker and German e-commerce giant Zalando are using AI for everything from product image backgrounds to quick-turnaround campaigns that align with social media microtrends.<\/p>\n
Consumers go through content \u2014 and trends \u2014 so quickly today that advertisers struggle to keep up with analog creative production alone. AI\u2019s rapid generation capabilities help marketers produce more varied ads so viewers are less likely to tire of them as they scroll social media\u2019s endless feeds. <\/p>\n
But figuring out the right formula to use AI is no small feat. New tools seem to pop up weekly and while some platforms excel at automatically generating images, they may lack the editing tools marketers need to ensure visuals stay on-brand. Brands must consider their unique needs \u2014 which can range from visualising creative ideas for a campaign and enhancing their product imagery with dynamic backgrounds to automatically targeting different audiences with different versions of the same ad \u2014 in order to determine the ways in which AI could amplify their creative production.<\/p>\n
The most accessible AI tools are ChatGPT and Adobe\u2019s Firefly, which many agencies already use for easy image generation. Others favour more advanced platforms like Midjourney and Leonardo AI for greater creative control and experimentation. Meanwhile, AI agency Maison Meta and Zalando aggregate multiple AI technologies into their own platforms, curating the best tools for specific tasks like background generation and editing under one interface \u2014 Maison Meta also hosts workshops for clients like Mango to teach them how to use its toolkit.<\/p>\n
More advanced tools are able to connect the dots between image generation and ad optimisation on social media. Meta, for instance, has its own suite of AI tools called Advantage+, which includes creative enhancements that allow brands to customise their ads by animating imagery, adding music or enhancing copy. Platforms like Smartly and Pixis are also dedicated to optimising the creative content in ads, allowing marketers to create visual templates that can be automatically updated to cater to different customers across platforms like Meta, TikTok, Amazon and more. Footwear retailer JustFab, for example, was able to create a template for its broad product catalog by removing the backgrounds across all images and generating new seasonal scenes across using Smartly.<\/p>\n
\u201cIt\u2019s the consumption happening now through social media that requires a volume that the marketing industry wasn\u2019t prepared for,\u201d said PJ Pereira, creative chairman of advertising agency Pereira O\u2019Dell.<\/p>\n
Lead With Human Creativity<\/p>\n
Regardless of the AI tools, human creativity and artistic direction must come first. \u201cThis is not the end of the creative director or the creative teams,\u201d said Jason Widup, senior vice president of marketing at AI advertising company Pixis. \u201cWhat we\u2019re seeing is the creative teams want to create new, interesting, fun concepts. They want to be pushing the envelope. And AI still doesn\u2019t have human taste.\u201d<\/p>\n
What this looks like in practice is using traditional brainpower to come up with core campaign concepts, and then using AI to see how far the idea can be pushed \u2014 testing out how an image would look on Mars, for instance, or with a giraffe alongside a model, said Pereira. \u201cYou can think and see in real time,\u201d he said.<\/p>\n
While in the past, campaign generation could be costly, AI enables marketers to test multiple ideas at one time and see what works best.<\/p>\n
\u201cThe biggest leap currently as a creative industry is the fact that the risk of trying something is infinitely smaller,\u201d said Pereira.<\/p>\n
Turn One Asset into Countless Variations<\/p>\n
Proponents of the technology still don\u2019t trust AI to fully take over ad production, said Pixis\u2019s Widup.<\/p>\n
Instead, many feed product assets and brand guidelines into tools like Smartly and Pixis, and then use the platforms to iterate on existing ideas and imagery to change backgrounds, colours or placement to create different versions of an ad that can be personalised and targeted across audiences.<\/p>\n
For Zalando, using its own AI tools to showcase products in a relevant context \u2014 like a hiking boot on a mountain, or even to turn static imagery into video \u2014 makes all the difference in driving customer engagement. This, in turn, helps them better understand what their customers want to see, which leads to fewer returns and triple the conversions. \u201cWe do not have endless hands, and we do not have endless time and endless budget,\u201d said Matthias Haase, vice president of content solutions at Zalando.<\/p>\n
Localise in Real Time<\/p>\n
Beyond creative content, AI can be leveraged to reach the right users at the right time. Whereas in the analog days of digital acquisition, consumers were repeatedly served the same ads, brands can now automate when viewers are served a piece of content \u2014 whether for a complementary product to one they already own or a specific handbag colour they\u2019ve been searching for. <\/p>\n
Most of Zalando\u2019s AI-generated content is market-specific to cater to local moments like Oktoberfest in Germany or regional running events, for example. These quick-turnaround, targeted campaigns typically take four days to produce, compared to six to eight weeks for traditional ad campaigns, and made up 40 percent of Zalando\u2019s campaigns in 2025. <\/p>\n
Its product description pages will eventually be customised to each geographical market using AI, showing different outfit combinations for French versus Polish shoppers, for example, and swapping out models that are recognised in different regions using digital twins<\/a>.<\/p>\n Build Content that Responds to Context<\/p>\n For platforms that connect AI image generation with targeting such as Smartly, brands can reach customers even more dynamically by making each element of an image changeable depending on the customer who is interfacing with it.<\/p>\n \u201cEvery element can effectively change based on the time of day, [and the] specific audience that is being targeted,\u201d said Oliver Marlow-Thomas, chief innovation officer at Smartly.<\/p>\n \u201cWe can dynamically map specific audiences to show specific variants \u2026 The dress the model is wearing, the shoe that\u2019s in the image, the colour of the background, or the colour of the hat, all of that is mapped and changeable.\u201d <\/p>\n Pixis, on its end, draws on data sources from Shopify to Google to macroeconomic data and weather channels to inform its decisions around which ad imagery is shown to who and when, said Widup. The platform has tested these dynamic ads for fashion brands on Meta, tailoring visuals and messaging to current weather patterns to make them feel relevant \u2014 showing rain jackets during storms or breezy outfits during heatwaves, for example \u2014 and boosting engagement and conversion rates.<\/p>\n Optimise Targeting with Platform Data<\/p>\n