Consumers are quick to sense when a message lacks intent. They look for cues that someone made a deliberate choice, that a brand understands context, tone, and timing. In retail, those cues often determine whether a shopper lingers or scrolls past. As generative AI accelerates content production across product pages, ads, and personalized recommendations, creative output scales dramatically. Volume increases, and with it the margin for sameness.

Retailers are operating in an environment where content production is no longer the bottleneck. As automation expands across creative and commerce workflows, the priority shifts to preserving distinction at scale. Brand voice, visual identity, and reputation have to remain consistent even as campaign cycles compress and decision-making moves closer to real time. Sustaining that consistency demands structured oversight, clear creative parameters, and governance built directly into the system rather than layered on after deployment.

For Anthony Nakache, Managing Director at Google MENA, the commercial opportunity lies in aligning scale with control. Provenance tracking, watermarking, likeness protections, and counterfeit detection are becoming operational standards inside AI-driven marketing stacks. When embedded early, these safeguards enable retailers to increase experimentation, improve measurable performance, and accelerate time-to-market while reinforcing long-term customer trust.

WHY AI MATTERS NOW 

The shift, Nakache suggests, extends beyond marketing into the entire retail business.

“Not only for retail marketing, but for retail business overall,” he says. Generative AI is helping retailers approach common challenges in new and creative ways. AI-powered tools such as virtual fitting rooms and 3D product images increase shopper confidence and engagement. Through AI agents, retailers generate content, offer tailored product recommendations, and provide real-time customer support. AI also enhances security, optimizes inventory, and streamlines operations.

Retail, he argues, is currently the best place to achieve quick, clear returns from AI adoption. Major companies are already moving decisively. 51 percent of retail and consumer goods executives have started using AI agents, and 59 percent say generative AI is already making a real difference in their marketing.

Marketing in particular stands out as one of the most proven ROI cases. “Marketers who integrate AI report 60 percent greater revenue growth than their peers,” Nakache notes. From Google’s perspective, AI-powered Search and YouTube are two major platforms driving AI marketing transformation.

“YouTube allows brands to show relevant and culturally relatable ads to people who search, scroll, stream and shop,” he says. Using AI tools and influencer marketing, it becomes easier for viewers to move from watching a video to buying a product. As a result, many retailers are seeing better returns on YouTube than on social media or traditional TV.

If AI is becoming infrastructure, its most immediate disruption is economic. The creative process itself is being restructured, compressed, and scaled.

“Generative AI is supercharging nearly every part of the creative process, from generating briefs and audience insights to ideation and creating entirely new ads, including video,” Nakache says. What once required multiple production cycles can now be executed in a single day. Within Google Ads, teams can create campaign visual assets quickly and ship ideas the same day, improving relevance across audience segments while accelerating time to market.

Adoption is already widespread. More than 80 percent of advertisers are using at least one AI-powered Search Ads product. As usage expands, the competitive gap between adopters and non-adopters is expected to widen.

“Competition will intensify between AI adopters,” he notes. The strongest teams will produce more in less time, reduce cost per campaign, and redirect savings into broader media buys, influencer partnerships, or other growth priorities.

Nakache also anticipates a structural shift in how creativity is positioned within marketing organisations. He draws a comparison to the fashion industry, where ready-to-wear and haute couture coexist.

In this scenario, AI-enabled teams become the masters of a high-speed, infinitely scalable creative model similar to ready-to-wear. Traditional creative teams evolve toward a digital version of haute couture, focused on bespoke, artisanal and human-centric work. In that environment, shopping becomes more intentional and elevated rather than purely frictionless.

Looking ahead, Nakache is clear that inaction is not a neutral position.

“I do not think that avoiding AI is a viable competitive strategy,” he says. Over the next three years, he expects the gap between AI leaders and laggards to widen significantly, particularly as Agentic AI becomes more widespread across commerce ecosystems.

To accelerate adoption, Google developed an open standard called Universal Commerce Protocol. The framework is designed to handle every step of a customer’s purchase journey, from first look to secure checkout, making Agentic AI more accessible to retailers at scale.

“Retailers that deploy AI agents organization-wide will successfully differentiate themselves,” Nakache explains. Creative capability will continue to matter, but it will represent only one component of a much broader value chain increasingly shaped by intelligent systems.

THE RISE OF CONTINUOUS ITERATION

Compressed production cycles are already changing how retail campaigns move from concept to launch.

“In e-commerce, shorter production times mean the end of waiting weeks for creative work,” Nakache says. Retailers can now move from a simple idea to a live, professional campaign in just a few hours.

He points to Kraft Heinz as a clear example. The company’s TasteMaker AI platform reduced content creation timelines from eight weeks to eight hours. By integrating brand assets, consumer insights and foundational culinary data, Kraft Heinz accelerated time-to-value and saved tens of thousands of hours across research and development and marketing. The system also enables rapid iteration on product innovations, including line extensions and new market opportunities.

That compression of time is also reshaping culture.

“We’ve reached a point where AI doesn’t just assist creativity, but scales it to drive business impact,” Nakache explains. The shift, he says, is from generative to agentic AI, where tools not only suggest but execute. In 2025, there was a threefold increase in assets created by advertisers using Gemini, allowing studio-quality work to be produced in minutes rather than weeks.

He stresses that this evolution is already visible in the market. During the last holiday season, Google Shopping and AI innovation studio Addition tested whether AI could operate at the pace of a live city environment in New York. The team deployed a hyperlocal system that generated hundreds of unique, location-specific ads tailored to the exact block where they appeared.

Using the Imagen 3 model, they built a fully AI-powered video pipeline. From hundreds of creatives, images aligned with brand safety criteria were selected, top performers were identified, and updates were pushed instantly to LinkNYC displays. Messaging shifted in response to live trends, demonstrating a true test-and-iterate culture where systems learn and react as fast as consumers.

“For retailers today, this level of agentic maturity is the new competitive frontier,” Nakache says.

As AI becomes embedded in marketing workflows, the balance between in-house teams and external agencies is evolving rather than disappearing.

“Agencies lead AI adoption, outpacing advertisers by 35 percent in AI maturity across marketing functions, from insights to creative,” Nakache says. As brands seek more specialized AI expertise, agencies are increasingly offering proprietary workflows, complex cross-platform integrations, and high-level creative campaigns that many standard in-house models cannot sustain.

At the same time, internal teams are not stepping back. They are using AI to automate routine tasks so they can focus more deeply on strategic and data-driven decision-making, as well as on protecting what Nakache describes as the brand’s core “soul.”

He does not see a zero-sum shift. “It would still be a mix of in-house and agency work,” he explains. The advantage will go to teams that maintain the shortest distance between a creative spark and a deployed, measured campaign.

While AI lowers the barrier to entry, he adds, the ceiling for excellence continues to rise.

THE GOVERNANCE IMPERATIVE

Nakache sees the acceleration of AI adoption across MENA as structural rather than cyclical.

“The surging AI adoption we’re seeing isn’t just a marketing trend in the region; it’s a reflection of the local unique DNA,” he says. The region’s demographic profile is heavily skewed toward a tech native youth population, with more than half of its 421 million people under the age of 30. This is a generation that does not simply consume trends but actively creates them.

Recent research reinforces that momentum. The ‘Our Life with AI’ report conducted with Ipsos shows that the UAE is operating on a different curve, with 71 percent of the public expressing excitement about the possibilities of AI. To translate that optimism into action, Google launched the ‘AI for All’ initiative in partnership with the UAE’s AI Office, institutionalizing AI literacy among government leaders, entrepreneurs, and SMEs.

Brands themselves are also driving adoption. Regional “love marks” are experimenting aggressively with AI-powered creativity. Together with Google, Qatar Airways hosted the “Sky Studio Challenge,” where filmmakers used Gen AI tools alongside high-speed in-flight connectivity to brief, generate, render and publish full commercial films during a single transatlantic flight. The exercise demonstrated how traditional constraints around location and production timelines are rapidly dissolving.

As scale increases, governance becomes equally important.

“From a governance perspective, particularly as retailers scale AI-generated visual assets, the focus is less on brand protection from AI and more on bold but responsible use of it,” Nakache explains. Brand integrity in the generative era, he says, rests on transparency and accountability.

Tools such as SynthID watermark AI-generated content to ensure traceability and help brands distinguish their authentic DNA from synthetic replicas. AI systems are also being deployed to identify high-fidelity counterfeits by detecting discrepancies invisible to the human eye.

“People, particularly creators, can be brands too,” he adds. Through YouTube Likeness Detection, individuals are given safeguards to protect their identity, ensuring that both creators and viewers remain protected as AI-generated content scales.