For decades, advertising production followed a familiar path. A brand developed a campaign brief, agencies built concepts, production houses shot content, post-production teams edited assets, and media teams distributed them across channels. The process was often expensive, time-consuming, and dependent on multiple external partners.
Artificial intelligence is beginning to alter that model.
The biggest impact of AI in advertising may not be the creation of flashy AI-generated commercials or viral campaign experiments. Instead, it is quietly changing where advertising gets produced. Across industries, brands are increasingly moving parts of ad production in-house, using AI-powered tools to create, adapt, localize, and optimize marketing assets at scale.
What started as an experiment in content generation is now becoming an operational strategy.
The shift is being driven by a combination of rising content demands, pressure on marketing budgets, and the need for faster turnaround times. As marketers produce thousands of assets across social media, retail platforms, connected television, marketplaces, and performance channels, AI is helping internal teams handle work that previously required agencies, production houses, or external creative vendors.
The result is not the disappearance of agencies. Rather, it is a redistribution of production responsibilities across the advertising ecosystem.
Recent industry data suggests the trend is accelerating.
According to the Interactive Advertising Bureau’s 2025 Digital Video Ad Spend and Strategy Report, 50% of advertisers are already using generative AI to create video advertisements, while 86% are either using or planning to use the technology. The same study found that buyers expect AI-generated creative to account for nearly 40% of all advertising content by 2026.
Another study conducted by the World Federation of Advertisers and media consultancy mediasense found that 71% of in-house marketing teams are implementing generative AI in specific production functions, while 65% are actively experimenting with AI tools. However, only 12% say AI has been fully integrated into their workflows, suggesting the industry remains in an early stage of transformation.
Taken together, these figures indicate that AI is no longer being treated as a creative novelty. It is becoming part of the infrastructure of modern marketing operations.
A volume problem is driving the change
The movement toward in-house production is closely tied to a challenge marketers have faced for years: content volume.
A single campaign today may require dozens or even hundreds of creative variations. Brands need short-form videos for social media, marketplace images for e-commerce listings, localized creatives for regional audiences, retail media assets, influencer content, display banners, and personalized versions for different customer segments.
Producing this volume through traditional workflows can be costly and slow.
AI changes that equation.
Instead of creating every asset from scratch, marketers can generate multiple versions of visuals, headlines, scripts, and video edits from a core creative framework. Localization, language adaptation, background changes, product variations, and resizing can be completed in hours rather than days.
The IAB report found that advertisers are increasingly using AI for audience-specific creative versions, contextual adaptation, and visual style modifications. These use cases are less about replacing creativity and more about handling scale.
David Cohen, Chief Executive Officer of the Interactive Advertising Bureau, captured the shift succinctly when he noted that “the economics of advertising are being transformed.”
The economics matter because marketing budgets have not expanded at the same pace as content requirements.
Gartner’s 2026 CMO Spend Survey found that marketing budgets account for 7.8% of company revenue, only slightly higher than the previous year. More than half of surveyed CMOs said they lacked sufficient budget and resources to fully execute their marketing strategies.
Under those conditions, AI increasingly looks like a productivity tool rather than a creative experiment.
Gartner’s research also shows that marketing leaders expect AI-driven automation to rise from 16% of marketing activities in 2026 to 36% by 2028. While that does not imply full automation, it suggests routine production tasks will increasingly be handled through AI-enabled workflows.
What brands are actually moving in-house
Despite concerns about AI replacing agencies, most brands are not bringing entire campaigns inside their organizations.
Instead, they are targeting specific production activities where AI delivers measurable efficiency gains.
These include social media edits, product photography, video cutdowns, language localization, e-commerce content, banner production, marketplace imagery, subtitles, voiceovers, and performance marketing assets.
The common characteristic across these categories is repetition.
When marketers need hundreds of creative versions rather than one flagship campaign, AI offers a clear advantage.
Reuters recently reported that several multinational companies are using India-based capability centers to handle growing volumes of AI-enabled marketing production.
Kimberly-Clark, for example, said its internal AI platform reduced content creation timelines from nearly a month to just a few hours while also helping localize campaigns for multiple markets.
“Our content creation process that once took weeks can now be completed within hours,” Deena Dayalan, Kimberly-Clark’s India leader, said while discussing the company’s AI-powered production approach.
Retail businesses are also finding practical applications.
Catalyst Brands has been experimenting with AI-generated product imagery and videos for e-commerce listings, reducing the need to transport physical products for traditional photo shoots.
Similarly, marketing teams within Target’s retail media operations are using AI tools to generate advertising copy and creative variations more quickly, allowing campaigns to respond faster to changing consumer trends.
These examples illustrate an important distinction.
AI is not primarily replacing large-scale creative campaigns. It is replacing manual production processes that sit between strategy and execution.
The rise of marketing production hubs
One reason this shift is gaining momentum is that many brands have already built internal marketing operations over the past decade.
Global capability centers, particularly in India, have become important hubs for analytics, content operations, technology development, customer experience management, and marketing support.
AI is increasing the strategic value of those centers.
Because production can now happen digitally rather than through traditional studio infrastructure, marketers can manage creative workflows closer to data, technology, and customer insights.
This creates tighter integration between production and performance.
Instead of waiting for multiple partners to execute creative requests, internal teams can generate, test, modify, and deploy assets from a single operational environment.
Industry data suggests marketers are embracing this model.
Canva’s 2026 State of Marketing and AI study found that 97% of marketing leaders now use AI in their everyday creative work.
The survey also revealed that 89% of marketers save at least four hours per week through AI-assisted workflows, while one in four report saving an entire working day every week.
Emma Robinson, Head of B2B Growth Marketing at Canva, summarized the trend by stating that “AI has changed how marketing gets made, but not what makes it effective.”
That distinction is important.
The conversation is increasingly shifting away from whether AI can create content and toward how organizations structure teams around AI-assisted production.
Ad production is becoming part of the martech stack
Perhaps the most significant change is that creative production is becoming increasingly connected to marketing technology systems.
Historically, content creation and campaign measurement operated as separate functions.
Creative teams developed assets. Performance teams measured results.
AI is blurring that separation.
According to Nielsen’s 2025 Annual Marketing Report, 47% of companies use AI for content creation, 43% for creative evaluation, 50% for quality assurance, 44% for customer segmentation, and 42% for personalization.
This means the same systems that help generate content can also evaluate effectiveness and recommend improvements.
A social media creative that performs well can be adapted automatically for another audience segment. Product imagery can be optimized based on conversion data. Messaging can be localized using performance insights rather than intuition.
The feedback loop between production and measurement is becoming significantly shorter.
As a result, many brands are viewing content production less as a standalone creative function and more as an extension of their broader marketing technology infrastructure.
Agencies are adapting too
The rise of in-house AI production does not necessarily signal a decline for agencies.
In fact, agencies are among the most active adopters of generative AI.
According to Basis Technologies’ 2025 Advertising Agency Report, nearly 98% of agencies now use generative AI in some capacity. More than one-third of agency professionals use AI daily, while over 90% use it at least weekly.
The report also found that 61% of agency professionals use AI for content development and creative ideation, while nearly half use it for image and video production.
This suggests agencies and brands are often adopting similar technologies.
The difference lies in where value is created.
As AI reduces the cost of routine production work, agencies may find greater differentiation in strategic planning, creative development, brand positioning, cultural insights, and campaign concepts.
Executional scale alone is becoming less of a competitive advantage when software can generate thousands of asset variations.
The industry’s future may therefore involve a clearer division between strategic creativity and production execution rather than a winner-takes-all outcome.
The human question remains unresolved
Even as brands bring more production capabilities in-house, marketers continue to face questions about quality, trust, and consumer perception.
Research suggests audiences remain cautious about AI-generated advertising.
Kantar’s 2026 analysis of generative AI in advertising found that only 48% of consumers enjoy seeing AI-generated imagery in ads, while 57% express concerns about misleading or fake content.
The same research showed that AI-generated advertisements generally score lower on overall impact compared to traditionally produced advertising.
Consumer sentiment studies from Canva tell a similar story.
Nearly 70% of consumers believe AI-generated advertising lacks emotional depth, while 87% say effective advertising still requires human involvement.
Gartner’s 2026 consumer research adds another layer of complexity, finding that half of surveyed consumers would prefer to engage with brands that avoid using generative AI in customer-facing content.
These findings explain why marketers continue to rely on human oversight even as AI adoption accelerates.
While AI can improve speed, scale, and efficiency, brand leaders remain cautious about handing over emotionally sensitive storytelling or high-profile campaigns entirely to machines.
The challenge is no longer technological capability.
It is determining where automation adds value and where human judgment remains essential.
That balance is likely to define the next phase of advertising production.
The evidence increasingly suggests that AI is pulling significant portions of ad production closer to the brand. High-volume creative work, localization, performance assets, and retail content are moving in-house because the economics favor speed, control, and scalability.
At the same time, strategic creativity, brand storytelling, and cultural relevance continue to depend heavily on human expertise.
The shift, therefore, is not about brands replacing agencies or AI replacing creativity. It is about advertising organizations redesigning production workflows around new capabilities.
For marketers, the question is no longer whether AI belongs in the production process.
It is how much of that process they want to own themselves.