AI is no longer a futuristic add-on in marketing. It has become the engine behind some of the strongest advertising performance gains seen in years.
Marketers are asking the same questions:
- Which AI applications actually move the needle, and what separates hype from real business impact?
Emerging data helps shape the answer. More than 34.1% of marketers now report that AI has already delivered major improvements to their campaigns, and the marketing and advertising sector leads all industries in generative AI adoption, with 37% actively using it to enhance creative and media workflows.
Across the case studies that follow, a clear pattern emerges. Brands are using AI to scale creative production that once felt impossible, uncover high-intent audiences that manual targeting misses, and optimize campaigns with a level of precision humans can’t replicate in real time.
- 1. Monks.
- AI-Powered Performance Creative for Hatch
- 2. Bria
- How Marcel Turned Lidl’s Brand Into a Viral Gen-AI Playground
- 3. Realtime Agency
- The Power of Automation: How Realtime Drove a 67% Lift in Sales for Liforme
- 4. PPC Live
- How Karaca Optimised Performance Max Campaigns with AI
- 5. Omneky
- How AI Drives Advertising Success
- The Future of Advertising Belongs to AI-Powered Creativity
- Frequently Asked Questions
These aren’t experiments. They’re proof points that AI in advertising delivers measurable, repeatable performance lift.
1. Monks.
AI-Powered Performance Creative for Hatch
Monks partnered with Hatch, the sleep wellness company behind the Restore 2 device, at a moment when you needed to introduce an unfamiliar product to entirely new audiences.
Restore 2 sits in a category that demands education before conversion, but education is expensive when every persona requires its own creative. Multiple photoshoots, dozens of variations, and persona-specific visuals usually drain both budget and time.
Hatch came to the agency with a clear problem: how do you scale personalized, lifestyle-driven creative without ballooning costs or production hours?
Strategic Approach
To break that bottleneck, Monks built an end-to-end AI pipeline that touched every stage of the campaign. You begin with audience research, powered by Google’s Gemini.
Instead of relying on static demographic decks, Gemini helped the team generate three fully fleshed-out AI personas. By “talking” to these personas, the team could extract real-world lifestyle cues, aesthetic preferences, sleep routines, and even details like bedroom décor.
Those insights fed directly into the creative platform. AI surfaced what “better sleep” meant to each persona, which inspired the overarching concept of positioning Restore 2 as “the everything machine” that fuels daily performance.
From there, generative AI helped design visual environments tailored to each persona’s tastes, all while staying aligned with Hatch’s brand guidelines.
The production layer was powered by Monks.Flow, the agency’s proprietary AI workflow. This system generated dozens of high-quality images and video variations in hours, instead of weeks, ready for Google Performance Max.
AI also produced custom soundscapes and multiple text variations to give the PMax algorithm an expansive menu of creative assets to mix, match, and personalize for each user.
Results
By building AI into every step, the agency delivered three personas, three videos, and sixty ad variants while cutting production hours by 50% and costs by 97%.
Performance surged, too. You see a 31% improvement in cost per purchase, an 80% jump in CTR, and a 46% lift in on-site engagement. For Hatch, this wasn’t just faster creative — it was more relevant, more efficient, and dramatically more effective.
2. Bria
How Marcel Turned Lidl’s Brand Into a Viral Gen-AI Playground
Publicis’ creative agency Marcel partnered with Bria to help Lidl France do something retail brands rarely pull off at scale: let customers co-create branded visuals without losing control of the brand.
Marcel needed a system that could instantly transform everyday objects into Lidl-style designs using the brand’s red, blue, and yellow palette. But doing this safely and consistently, across millions of generations, in multiple languages, and with zero tolerance for distorted objects or off-brand imagery, was the real hurdle.
On top of that, Lidl required copyright-safe data, airtight moderation, and compliance with EU AI Act standards.
In other words, the challenge was simple to describe but brutally hard to execute: deliver high-fidelity, on-brand AI visuals at massive scale, with minimal latency, and no risk to brand integrity.
Strategic Approach
Marcel built a streamlined web app powered by Bria’s tailored Text2Image models and Visual Gen-AI stack. This wasn’t generic image generation. Bria trained custom models on fully licensed, commercial-grade datasets, which allowed every output to stay legally compliant and visually consistent with Lidl’s identity.
Using Bria as the engine, Marcel enabled users to type prompts in English or French and instantly see Lidl-themed versions of scooters, mugs, helmets, umbrellas, or anything they imagined. The infrastructure lived on AWS, giving you low-latency performance even when traffic spiked to thousands of generations per minute.
Safety was handled through Bria’s multi-layered moderation systems, which filtered out inappropriate prompts, ensured ethical compliance, and maintained the playful tone Lidl is known for. Attribution technology also embedded transparent origin markers in every asset, aligning with Lidl’s commitment to ethical AI and compensating data partners fairly.
To fuel reach, Marcel activated influencers across social platforms, turning the web app into a viral toy that encouraged millions of people to generate and share their own Lidlized creations.
Results
The campaign exploded: over 1.7 million AI-generated visuals in just three weeks, with users organically spreading their creations across social feeds. The system stayed fast, stable, and error-free even under heavy load, proving that high-fidelity, on-brand AI generation is finally viable at retail scale.
For Lidl, the payoff was huge. The client got deeper brand engagement, cultural relevance, and a flood of user-generated content, all without compromising safety, compliance, or visual identity.
This wasn’t just a fun experiment. It showed how a grocery brand can become a pop-culture moment by giving customers an ethical, scalable, and creatively empowering AI tool.
3. Realtime Agency
The Power of Automation: How Realtime Drove a 67% Lift in Sales for Liforme
Realtime partnered with Liforme, the yoga brand known for its eco-friendly, high-performance mats, with one goal: figure out whether Meta’s Advantage+ Shopping Campaigns (ASC) could outperform an already healthy mid-funnel setup.
They weren’t trying to fix a failing account. They were testing whether AI-driven automation could push an already strong program even further, especially when it came to finding new customers.
But ASC requires a mental shift. They lost targeting controls, segmented ad sets, and handed the creative-mix decisions to Meta’s algorithm. For most advertisers, that feels uncomfortable.
To answer the question definitively, Realtime needed a clean experiment with no noise; no creative changes, no seasonal fluctuations, no audience shifts, no random marketplace interference.
Strategic Approach
To isolate the impact of AI, Realtime designed a statistically rigorous test using Meta’s holdout technology. Instead of adjusting creatives or audiences, they split the campaign by region.
One region saw the AI-driven Advantage+ campaign; the other saw the standard mid-funnel campaign. Same creative, same messaging, same budget structure.
ASC’s power lies in handing over those mid-level levers. With no ad sets, Meta’s AI takes full control of targeting and delivery. It also uses dynamic creative, testing combinations automatically across placements, audiences, and contexts you could never manually manage at speed.
Instead of doing the traditional “segment and tweak” routine, they let the algorithm learn who is most likely to buy — not just who engages — and deliver ads at the best possible moment. Realtime’s goal wasn’t only performance.
They wanted proof. Clear, statistically significant proof that ASC’s AI could both reduce cost per purchase and expand Liforme’s pool of net-new buyers.
Results
Within just five days, the data was conclusive at 95%+ significance. Advantage+ outperformed the standard structure by 67%, delivering dramatically lower cost per purchase.
But the real headline was who converted: 99% of purchases came from new customers, proving that AI targeting didn’t just optimize efficiency but unlocked entirely new pockets of demand.
For Liforme, the test showed exactly what ASC can do when you trust the algorithm: faster learning, lower costs, and an influx of high-intent customers you might never have reached manually.
4. PPC Live
How Karaca Optimised Performance Max Campaigns with AI
Karaca, one of the region’s leading kitchenware and cookware brands, manages more than 2,000 SKUs across its e-commerce catalogue. The digital team needed a way to increase revenue while gaining tighter control over Performance Max campaigns, particularly for high-value products.
The existing campaign structure was segmented by category, which provided basic organization but made it difficult to dynamically shift budget toward products with the strongest ROAS.
Manual bi-weekly reviews helped, but the process was slow, inconsistent, and impossible to scale across such a large product set. To solve this, the team turned to SMEC, an AI-driven optimisation platform, marking its first major step into automated PPC management.
Strategic Approach
The shift began by integrating Karaca’s Google Ads account with SMEC and restructuring Performance Max around performance tiers instead of categories. Three campaigns were created: High Score, Mid Score, and Low Score.
SMEC’s dynamic scoring engine continuously evaluated real-time ROAS and sales signals, automatically reassigning products across campaigns. A high performer could quickly move up into the High Score campaign, while a declining SKU could be shifted down within days.
To maintain creative relevance, asset groups within each campaign still mirrored product categories. SMEC’s automation capabilities were expanded further through seasonal push strategies during moments like Black Friday, enabling more aggressive bids on discounted SKUs.
The platform also supported an exclusion framework that removed underperformers from active rotation, a critical efficiency boost for a 2,000+ product catalogue.
The rollout required close, ongoing collaboration with the SMEC team to fine-tune labels, manage feeds, and ensure seamless integration with Google Merchant Center. Once in place, SMEC handled decisions that previously required hours of manual oversight, freeing the team to focus on strategy rather than maintenance.
Results
Across May 2024 to February 2025, the AI-driven structure delivered a 44% ROAS increase and 31% revenue growth. Automated product prioritisation and budget allocation eliminated wasted spend, strengthened performance across top SKUs, and modernised how Karaca approached Performance Max at scale.
The transition from category-based segmentation to AI-powered scoring became a transformational shift, proving how automation can meaningfully elevate e-commerce growth.
5. Omneky
New Sapience: AI-Driven Crowdfunding Powered by Omneky
New Sapience, a company building “sapiens” — knowledge-based thinking machines designed as an alternative to conventional neural networks — needed a way to communicate its complex vision to potential investors.
The goal was twofold: raise awareness for a groundbreaking approach to artificial intelligence and drive real investment during a RegCF crowdfunding round. To succeed, the brand required a partner capable of blending performance marketing, creative experimentation, and highly targeted acquisition at scale.
That partner was Omneky, known for its AI-first approach to ad creative and campaign optimisation.
Strategic Approach
Omneky deployed a three-part AI-driven workflow tailored specifically for crowdfunding. The process began with the platform’s AI image generator, which rapidly produced creative concepts shaped around themes that perform well in tech-forward funding campaigns.
Using predictive scoring and pattern recognition, Omneky’s system identified that robot-centric visuals consistently resonated with audiences interested in AI and emerging technology. These insights shaped the visual direction, influencing everything from thumbnail designs to ad-level creative.
Next, Omneky’s AI insights engine analyzed historical crowdfunding patterns, audience behaviors, and early campaign performance to guide messaging and placement decisions. Targeting strategies were built around individuals predisposed to tech investing, crowdfunding interest, and emerging AI innovation.
Finally, continuous data-driven optimization played a central role. Omneky used its dashboard to monitor ROAS, cost per investment, creative fatigue, and cross-platform engagement.
This allowed ongoing refinement of both creative variants and audience mixes, ensuring that spend was consistently routed toward the highest-intent segments. Across the entire campaign, AI served as the backbone of both creative production and tactical decision-making.
Results
The campaign exceeded expectations. Omneky’s ads directly generated over $460,000 in contributions, contributing to a total raise of over $1.18 million.
Performance metrics were equally strong: a 6x ROAS, 470+ investments, an efficient $160 cost per investment, and 52,000+ link clicks driving sustained traffic to the funding page. The combination of AI-generated creative, predictive insights, and precise targeting turned a complex product narrative into a successful, high-performing digital raise.
How AI Drives Advertising Success
Artificial intelligence has become one of the most powerful accelerators in modern advertising. It strengthens creative production, expands audience reach, automates optimization, and safeguards brand integrity in ways that were nearly impossible just a few years ago.
The following sections break down the core ways AI is driving measurable advertising success.
AI-Accelerated Creative Production
AI enables brands to produce large volumes of high-quality creative assets at unmatched speed. Instead of relying solely on photoshoots, manual design, or slow iteration cycles, teams can generate images, videos, and variations in hours.
This doesn’t replace human creativity; it amplifies it. AI assists in early concept development, offering insights into themes, messaging angles, color palettes, and visual styles that resonate with specific audiences.
By tapping into synthetic personas or predictive models, creative teams can shape concepts around lifestyle preferences, emotional triggers, and visual cues that increase relevance. The result is faster testing, lower production costs, and campaigns built on deeper insight rather than guesswork.
AI-Driven Targeting and Audience Expansion
Modern advertising platforms increasingly rely on machine learning to handle targeting and delivery. AI systems continuously evaluate user behavior, context, and intent signals that would be impossible for a human buyer to process at scale.
This unlocks entirely new pockets of high-intent users, helping brands expand beyond their typical audience segments. Structures like Performance Max or Advantage+ Shopping show how AI reallocates budget automatically toward audiences with the highest probability of converting, even when demographic details are unknown.
The outcome is greater efficiency, lower costs, and more accurate reach without the complexity of manual segmentation.
Automated Optimization and Budget Allocation
AI brings real-time intelligence to optimisation. Instead of adjusting bids, reallocating budgets, or reorganizing product groups manually, automation engines evaluate performance continuously.
Thousands of signals, ROAS shifts, creative fatigue, category trends, and inventory levels feed into models that adjust product placement or creative delivery on the fly.
This ensures strong performers receive increased investment, while underperforming products or ad sets are quickly suppressed. During high-volume retail periods, AI can also deploy more aggressive bidding strategies automatically, maximizing visibility when competition spikes.
Predictive Insights and Creative Intelligence
AI-powered analytics tools identify which creative elements drive performance before spend is wasted. Predictive scoring models evaluate headlines, imagery, objects, colors, characters, or motion cues and forecast how well those combinations will perform.
These insights help shape creative direction, guide iteration, and reduce costly testing cycles. Brands gain visibility into what works — and why — allowing more confident decision-making.
Safe, Compliant, and On-Brand AI Deployment
AI also strengthens brand governance. Modern systems ensure generated visuals remain on-brand by protecting color palettes, logos, and design conventions. Content moderation layers prevent unsafe or inappropriate outputs, while licensed datasets support copyright-safe generation.
This balance of creativity and control allows brands to scale experimentation without risking legal, reputational, or compliance issues.
AI’s impact is clear: when applied across creative, media, and optimization layers, it becomes a compounding advantage. Brands that integrate AI now are not just keeping up — they are setting the pace for the next era of advertising performance.
The Future of Advertising Belongs to AI-Powered Creativity
AI is no longer an experimental bolt-on to advertising; it is becoming the engine behind the industry’s biggest performance gains.
From Lidl’s viral Gen-AI activation to Hatch’s persona-driven creative production, Liforme’s automated audience expansion, and Karaca’s product-level optimization, the case studies make one truth clear: brands that embrace AI outperform those that rely solely on manual processes.
The real advantage lies in combining human insight with machine-scale execution. AI accelerates creative thinking, discovers new customers, reallocates spend with precision, and safeguards brand identity at levels traditional workflows can’t match.
For marketers and brands, the takeaway is simple: AI is not replacing the craft of advertising. It’s elevating it — making every idea sharper, every campaign smarter, and every dollar more impactful.
Frequently Asked Questions
How can AI improve creative testing without increasing production costs?
AI can quickly generate variations that help teams validate concepts before scaling spend, similar to how advertisers streamline early creative decisions when using AI optimization tools.
Does AI help advertisers discover new high-intent audiences?
Yes — machine learning models surface emerging interest groups and behavioral patterns, an approach also used by modern programmatic ad platforms to expand reach efficiently.
Can AI support more efficient paid media management for smaller teams?
AI reduces manual workload by automating bidding, pacing, and delivery, making lean teams more effective in the same way many brands rely on AI marketing platforms to handle repetitive optimisation tasks.
Where does AI make the biggest impact in performance marketing?
The strongest gains often come from smarter measurement and more accurate audience selection, which mirrors how brands improve outcomes with AI affiliate for performance marketing.
Is AI valuable for brands running multi-channel campaigns?
Absolutely — AI helps unify insights and predict performance across channels, a benefit also seen among businesses that work with specialist AI marketing agencies.
Can AI assist with scaling ad personalisation?
AI personalises messaging at speed by analysing context, sentiment, and user behavior, a capability reflected in tools built for AI influencer marketing platforms.
How is AI changing ecommerce-focused advertising?
Retail brands increasingly lean on AI for dynamic product prioritisation and creative automation, similar to how ecommerce advertisers optimise campaigns through advances in Amazon AI advertising.
What foundation should marketers understand before adopting AI for ads?
A solid grasp of machine learning basics and automation workflows helps teams deploy AI more effectively.
