Retail media has gone from a little experiment to one of the most powerful and fastest-growing advertising channels in today’s digital economy, which is focused on commerce. Amazon, Walmart, Target, and even smaller online stores are more than just places to buy things; they are full-fledged media empires with their DSPs, inventories, and brand studios. As people’s attention becomes more divided and they make judgements about what to buy in apps instead of search engines, retail media is where the actual buying happens. This is also where the most relevant ads need to be.
Retail media is doing great, but creative execution hasn’t kept up. When you’re launching hundreds of SKUs across dozens of marketplaces and audience groups, what does it truly mean to “personalise at scale”? Creative teams are getting too many requests. Every new campaign needs new images, messages that are relevant to each channel, and different A/B versions. What used to be a quarterly photo shoot and a marketing message now feels like an endless treadmill of assets.
The main creative conflict of our day is that we have to do things by hand in a market that moves at the speed of a machine. The old ways of doing things, such as campaign briefings, static designs, and layered approvals, are now in direct conflict with the always-on, changing needs of digital commerce. What happened? Hiccups. Missed chances. Creative that isn’t doing well. This isn’t a concern for the future. Right now, it’s occurring.
And the answer is more and more Martech, but not the Martech of the past. Not spreadsheets and dashboards. We’re talking about creative engines that leverage AI and act less like tools and more like independent partners. The magic of tomorrow’s ads isn’t in a design studio; it’s in a machine that knows your audience better than your agency does.
So, let’s discuss the future of retail media and why creative scale needs to be a Martech issue instead of a design one.
Retail Media’s Rise and the Creative Crisis No One Wants to Admit
Retail media is developing very quickly and is now one of the fastest-growing areas of digital advertising. But there is a growing creative dilemma beneath the glossy growth numbers. As businesses rush to satisfy the needs of personalised, fast-paced campaigns on retail platforms, traditional creative creation can’t keep up.
What happened? Generic assets, missed opportunities, and squandered money on media. It’s time to face the difference between what retail media promises and what it does.
Retail Media Is Eating the Digital Ad World Alive
Retail media isn’t just one thing anymore; it’s the whole playbook. eMarketer says that U.S. retail media ad spending will reach over $100 billion by 2026, making it the third-largest digital advertising channel behind search and social. Amazon Advertising alone makes more than $45 billion a year. It’s not only about size; it’s also about accuracy.
Retail media lets marketers show ads right at the point of sale, with real-time behavioural data and direct attribution. In short, this is the best thing that could happen for performance marketers.
But here’s the dirty little secret: most brands aren’t ready for this. They’ve put money into keeping track of performance. They’ve added to their Martech stacks. They have CDPs, CRMs, DMPs, and dashboards. But how do they come up with ideas? Still stuck in the 1960s. Sets of static banners. Brainstorming sessions once a week. Approval takes longer than a Christopher Nolan film.
The Bottleneck Everyone Is Ignoring: Creative Throughput
Let’s be honest: you can’t personalise something without a lot of creativity. One banner can’t reach 30 different customer groups. You can’t use one video to test five different versions of a product. But most creative teams are still working with ideas from 2015, like fixed asset counts, monthly cycles, and templated formats.
Retail media needs a lot of creative work that is always changing. But traditional creative pipelines are always slow, straight, and expensive. Every version is handled by a person. A person makes every A/B test. And what if a campaign doesn’t do well? You have a few weeks to try something new.
Why Martech Must Own the Creative Problem?
Martech is meant to make marketing easier, faster, and bigger. So why is creative work still seen as a small business? We have made sending emails automatic. We have made clever segmentation engines. We have even used AI to write subject lines. But we’re still making banner advertising by hand? Not only is it out of date, it’s also careless.
This gap is starting to narrow because of modern Martech platforms. Creative AI, dynamic content optimisation engines, and prompt-based graphic generators are now in charge of the first drafts, the A/B sets, and the changes that are customised to each audience. It’s not about getting rid of designers; it’s about making them bigger. Let people make the voice of the brand. Let the machine make the 150 different versions it needs to send them to the right people in general.
And let’s be honest: in a retail media setting, when timing, relevance, and iteration are what make or break a campaign, creative latency means missed sales. Not only are your competitors spending more than you, but they are also iterating more. And they’re doing it with Martech that knows how to make things.
Retail Media Without Creative Scale Is Just a Missed Opportunity
It’s time to call out the hypocrisy: brands are paying millions on retail media placements, but they’re using the same old product banners from last quarter. They’re using static materials while also using dynamic ad placements.
They are using big-picture creative techniques to get little conversions. It doesn’t work. And it’s not because the media isn’t strong. It’s because the message isn’t keeping up. And it won’t—unless brands start thinking of making creative content as a Martech job.
The Brands That Win Will Let AI Do the First Draft
The big change is that AI should make the first version of each component. Allow it to look at the SKU. Allow it to write the description of the product. Let it pick the best headline. Let it make the five image variations that are most likely to work. After that, let the person make the final adjustments.
The main part of Martech’s new job in retail media is to transfer strategy into creative speed. Making changes based on what you’ve learnt. Making choices based on data. Not just measuring performance, but making it happen.
The Creative Bottleneck Meets a Digital Tsunami
Traditional creative workflows just can’t keep up with the way retail media is growing and digital consumer journeys are getting longer and longer. Marketing teams are under a lot of stress to come up with hundreds of different types of content that are personalised, localised, and aware of the situation, all while working with less time and money. Creative excellence is still a must, but speed and scalability are now the most important things.
This is where Martech platforms are stepping in, not just to help with campaigns but also to come up with new ideas. What used to be a human, inspiration-based process is now turning into an automated, data-driven machine that combines science with storytelling.
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AI as Co-Creator: The New Creative Workflow
Today’s MarTech platforms are adding generative AI features right into the process of making content. These tools can look at client data, figure out what performance signals mean, and provide campaign-ready assets—like copy, images, and layout variations—almost right away.
The change is big. AI is no longer simply a back-end analyst or automated bot. It’s now in the brainstorming room, helping to write headlines, change visual layouts, and make persuasive content in all media. This addition changes marketing teams from being slow to produce to being able to quickly organise large amounts of material that has a big impact.
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Human Creativity, Supercharged by MarTech
This isn’t about getting rid of people; it’s about freeing them. MarTech takes care of repeated versioning, filling in dynamic information, and formatting for several channels, so creative teams can focus on strategy, storytelling, and making people feel something.
Copywriters take over as editors-in-chief. Designers choose, improve, and raise the quality of AI-generated images. Strategists put performance information back into the machine. The result is a virtuous loop in which AI takes care of the volume, and people focus on the value.
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More Content Isn’t Enough; It Needs To Be Smarter
People often think that AI only speeds up the creation of content. Martech platforms make content more intelligent. These systems don’t just produce content; they make it better.
AI engines change the tone, format, and message of a campaign in real time based on how well it did in the past, how the audience behaves, and how they interact with it in real time. The creative is continually changing to meet the needs of the audience, the platform, and the business. That’s a level of immediacy that traditional procedures could never even imagine.
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The Strategic Edge: From Ideas to Impact
This AI-powered creative change isn’t just a short-term plan; it’s a long-term one. Companies that use AI-powered Martech platforms say they can get to market faster, have greater conversion rates, and work better together across teams.
More significantly, they build a creative muscle that is always there, based on data, and ready for the future. Campaigns become live systems instead of short bursts. Testing goes on all the time. Iteration happens on its own. And every new asset makes the creative engine smarter and more responsive.
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Creative Control Isn’t Lost—It’s Elevated
People are worried that AI may ruin brand voice or make material that sounds bad. That’s only true if teams give up control. The best MarTech platforms make sure people are always involved by using ethical guardrails, following brand rules, and making sure the content is culturally relevant.
Marketers still get the final say on what looks nice. But now they have a creative partner that never stops working and can make that vision a reality on every retail media surface, as fast as digital commerce needs it.
MarTech Drives the New Creative Powerhouse
It’s time to stop making creative work by hand and in one place. The future belongs to teams that combine human creativity with machine intelligence. These teams build with data, make changes in real time, and talk to every customer all the time.
AI-powered Martech platforms are not only making workflows better; they are also changing what it means to be creative. For brands that work in the high-stakes realm of retail media, this isn’t an option. It is necessary for competition. People who accept it will not only keep up but also lead the way into a new age of smart innovation.
Marketing Technology News: MarTech Interview with Julian Highley, EVP, Global Data Science & Product @ MarketCast
How It Works: The Core Components of AI-Driven Creative
The idea of AI-powered innovation is no longer a distant dream; it’s here, and it’s changing how brands do large-scale marketing. Retail media and personalised advertising are becoming the places where people fight for attention. Martech platforms are becoming the brains behind AI-driven creative execution.
This change isn’t about AI taking over for people. It’s about seeing the creative process—from the brief to the output to the iteration—as a system that responds to data in real time. Let’s look at the four basic parts that make this feasible.
1. Data-Driven Creative Briefing: Accuracy Begins with the Input
The old way of giving creative briefs—long, unchanging paperwork based on guesswork and gut feelings—is being changed for the AI age. Modern Martech systems don’t use abstract personas or old market research. Instead, they get their information straight from live product feeds, real-time customer behaviour, and campaign performance histories.
AI analyzes:
- SKU-level features and availability
- Search trends and signs of behaviour
- Patterns in geography and demographics
- How well does historical content work
What happened? Smart, flexible, creative prompts that are tailored to the campaign’s goals, the product’s stage in its lifecycle, and the unique audience group. The AI doesn’t assume what could work; it figures it out, suggests it, and keeps learning from what works. This data-driven briefing step is the first important part of scalable, AI-powered content creation. It makes sure that every campaign starts with facts, not speculation.
2. Making Dynamic Content: The Alchemy Begins
This is where the magic, or “creative alchemy,” happens. With the information from data-fed briefings, Martech platforms with built-in AI engines start making different versions of content on their own. That means:
- Headlines that work best for diverse groups of people
- Image options that fit with the buyer personas
- Copy that is specific to different channels, including email, banner ads, social media, etc.
It’s not just about giving away generic templates, though. These AI engines combine natural language generation (NLG) and computer vision to provide content that fits with the brand, has been tested for performance, and is specific to the channel. The AI has learnt from thousands of successful campaigns, and it becomes smarter every time you use it. This kind of automated creative generation is the only way for brands with hundreds or even thousands of SKUs across many marketplaces to move forward.
This is possible because of Martech. It’s not a “external creative studio” that was added on; it’s part of the marketing stack. This means that marketers can create and deploy variations right in the platforms they already use to do their work.
3. Real-time optimization and iteration: Creative Intelligence that never stops
This is the point at which AI stops being a creator and starts becoming an unending optimizer. Martech systems start gathering real-time performance data, such as click-through rates, conversion rates, scroll depth, hover time, geographic differences, and more, as soon as content is up. These signals go back to the AI engine, which starts to change parts of the information on its own.
The algorithm can do the following if one image works better in a certain area or one headline variation gets more mobile users to convert:
- Change creatives in the middle of a campaign
- Stop investments that aren’t doing well
- Make fresh versions on the spot
This is one of the main benefits of integrating AI in the Martech ecosystem instead of separate technologies. The AI can directly access feedback loops on performance, which speeds up iteration and increases ROI. Campaigns don’t run on guessing anymore; they change all the time based on what happens in the actual world.
4. Contextual Relevance: Sending the Right Message at the Right Time
AI’s capability goes beyond making content; it also includes delivering it in a precise and relevant way. Modern Martech systems can assist AI in customising assets based on:
- Device (desktop, mobile, tablet)
- Channel (website, social media ad, email)
- The time of day or the season
- Behavioural intent (whether someone is a first-time visitor or a repeat visitor)
- Geography and even the weather
This contextual relevance makes basic advertising into experiences that get a lot of conversions. A customer in Mumbai looking at a product on their phone on a Monday morning sees a different ad than someone in London shopping on their computer on a Friday night. AI working inside the Martech stack made both of those versions on the fly and made them better.
It’s micro-targeting on a creative scale, which is only possible because of the combined intellect of AI and Martech.
The Creative Loop, New and Improved
When you put together data-driven briefings, automated content creation, real-time optimisation, and contextual delivery, you create a creative loop that lives and breathes. One that never sleeps, never waits for permission, and is always learning.
This isn’t the future. It’s going on right now. Brands that add this new creative engine to their Martech systems will get an edge that has never been seen before: flexibility, relevance, and huge ROI, all delivered at scale with fewer people and a faster time to market.
The message is obvious for those who are still caught in static workflows or outsourcing creative work for long periods of time: change or risk becoming irrelevant. In the age of AI, creativity is more than simply an art; it’s a system. And Martech is what makes that system work.
Implementation Considerations for Brands: Preparing the Ground for AI-Driven Creative at Scale
As AI-powered creative solutions become more popular in retail media, it’s less about flipping a switch and more about building the correct framework for them to work. Brands need to focus on four key areas of implementation to fully understand the benefits of AI-generated content.
This is especially true in retail settings where relevance, speed, and accuracy are essential. These include things like being ready for data, having people in charge, following ethical rules, and being able to easily fit into existing Martech ecosystems.
a) Data Foundation: Feed the AI Engine
A strong data foundation is the first and maybe most important thing that AI needs to be creative. To make good content, you need clean, organised product data, audience signals, and previous performance measurements. Even the smartest AI is just an idea generator in the dark without them.
Brands need to make sure that their Martech systems, such as product information management (PIM), customer data platforms (CDPs), and analytics suites, all work together and are correct.
For example, AI tools could send messages that are unclear or wrong if the descriptions of the products are missing, inaccurate, or out of current. Targeting will fail if consumer segmentation is unclear or not well defined. AI technologies can design, test, and optimise on a large scale when creative assets are tagged in a structured way, audience attributes are clearly defined, and campaign results are labelled in a consistent way.
This is not a one-time data dump, which is important. AI-driven platforms need a steady stream of data. That means using real-time signals from Martech stacks to make sure that insights are constantly up to date, whether they are about how shoppers behave, how much competitors charge, or how prices change with the seasons. Brands should think of data as a living asset, not a dead archive.
b) Human Oversight and Brand Voice: Creative Ideas with Limits
One of the biggest myths about AI in creative work is that technology takes the place of people. In actuality, it makes it better, but only if people are in charge of the process on purpose. AI could make 100 different banners in a lot less time than a designer could, but without guidelines, tone, and brand identity might easily get lost.
Marketers need to check AI outputs not only for factual correctness but also for emotional subtlety. Brand voice isn’t only about style; it’s also about the emotional imprint that develops trust and loyalty. No matter how smart they are, AI technologies can still get sarcasm, humour, or cultural differences wrong. That’s why it’s so important to have a human-in-the-loop validation process, especially in fields like fashion, beauty, and finance, where tone is crucial.
Brands should put creative rules right into their Martech frameworks to keep things consistent. After that, AI technologies can use the standards for tone, brand vocabulary, and visual identity that have been approved. Some Martech solutions also let you report material that doesn’t follow brand rules in real time, which helps keep quality high as the business grows.
c) Ethical AI in Creative: More Than Just Clicks and Conversions
As AI becomes more common in marketing, we need to use its potential wisely. One of the most important things to think about when putting something into action these days is making sure that the creative generation is done in an ethical way. Not only should you avoid offensive pictures and jokes, but you should also avoid using deceptive tactics, making stereotypes, and being culturally insensitive.
For instance, personalisation shouldn’t turn into hyper-targeted emotional manipulation. AI shouldn’t use psychological triggers like fear or shortage without first being checked by a person. Also, AI training data needs to be checked for bias to make sure that the creative work doesn’t unfairly favour specific age groups, genders, or ethnic groupings.
Some Martech companies are now adding explainability modules, which are AI tools that show the reasons behind creative choices. These not only aid with compliance, but they also help creative teams figure out why some headlines or images worked effectively. Transparency helps marketing teams gain trust from their employees, stakeholders, and customers, who are becoming more aware of how their data is used.
d) Integration with Existing Workflows: Martech at the Center
If an AI creative tool isn’t used every day by a brand, it won’t work as well as it could. To scale AI-generated content quickly and easily, it needs to work well with digital asset management (DAM) systems, ad servers, content calendars, and media buying platforms. This is where Martech shines—not just as a set of tools, but as the glue that holds modern marketing together.
Creative teams should be able to start AI-generated versions of their work from their DAMs, and performance teams should be able to see real-time results in their campaign dashboards. The finest Martech platforms now have APIs or built-in connections to generative AI tools. This lets people work together on projects where they can edit, approve, and distribute AI assets without having to switch between platforms.
Integration isn’t only about technology; it’s also about how things are set up. Teams need to be on the same page. This involves teaching marketers how to understand AI insights, giving designers the power to improve images made by machines, and giving performance marketers the tools they need to use AI creatives smartly.
The Martech Imperative
In the end, the success of AI in retail media isn’t based on how much content it can make, but on how well and ethically that content works. Implementation is the point at which the plan and action come together. Brands could turn a great chance into just another unsuccessful experiment if they don’t have clean data, human oversight, ethical guidelines, and smooth integration into Martech ecosystems.
But for those who do it right—who see Martech as the engine room of creative scale, strategy, and intelligence—the reward is clear: content that connects, converts, and gets better all the time. Brands that plan for this future now will not only keep up with the fast pace of retail media; they will set the standard.
Final Thoughts
Advertising has always been a mix of strategy, design, and storytelling. But this combination is changing in a big way in the age of retail media. AI and Martech are changing things that used to depend on manual work, gut instinct, and gradual iteration. The creative process, which used to be separate from data and performance, is now more flexible, smart, and measurable. This change signals the beginning of smart innovation.
In the past, marketers would spend weeks or even months coming up with creative ads. The process was linear and inflexible, from the briefing to the implementation, and it couldn’t keep up with how fast digital commerce changes. Retail media, which always needs new, personalised, and context-aware information, has shown that this method has its limits. It needs to be big without losing its subtlety, and fast without hurting the brand’s identity. Martech has come in here, not only as a support tool, but as a key player in changing how creativity is made, used, and improved.
With the addition of AI-powered creative tools to Martech platforms, it is now possible to make hundreds of different pieces of content in the same amount of time that it used to take to make one. These variations are not arbitrary; they are based on performance indications, audience insights, and contextual triggers that lead to real-world effects. In this new age, martech doesn’t merely automate; it also organises. It takes raw data and converts it into creative insight, into material that is both useful and meaningful.
There are big benefits for brands that are willing to use this concept. AI-generated creatives can make performance metrics like click-through rates (CTR), return on ad spend (ROAS), and conversion rates much better. They let advertisers test many headlines, images, and messages at once in real time. And because they are part of Martech ecosystems, the feedback loop is instant, and learning happens at the same speed as the market.
This change is not only technological; it is also cultural. Marketers need to stop trying to control every pixel and start curating and directing smart systems. They need to change their definition of creative brilliance from static perfection to constant change. And they need to set up internal systems that let people and machines work together without any problems.
People who don’t regard AI as a threat to creativity but as a way to make things happen more quickly will have a bright future. Martech will be the canvas, the paint, and the brush all at once. It will bring ideas into reality on a scale never seen before. In this paradigm, marketing departments become creative labs, where every piece of content is attractive, functional, emotive, and engineered.
As we look to the future, one thing becomes clear: in the age of retail media, creativity isn’t simply art; it’s algorithmically augmented al bullet. Brands that see this early, put money into the correct Martech infrastructure, and give their teams the capability to work with AI will be able to reach a level of efficiency, relevance, and profit that was formerly thought to be unattainable. The creative revolution is here, and smart technology is making it happen.
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