Artificial intelligence dominated the stage at Cannes Lions 2025. From generative tools that pump out hundreds of ad variations in seconds to smart systems that personalize content delivery, AI-driven marketing was showcased as the future of advertising. But before we rush to declare AI the new creative director, let’s take a data-driven look at what is really happening in the industry and whether this is a foundational shift or another hype cycle.

The Cannes context: signal or noise?

Cannes has always served as a barometer for advertising innovation. This year, AI-generated campaigns received significant attention from both judges and journalists. Large brands unveiled tools that create ads, write copy, and even animate visuals with minimal human intervention.

However, the core question remains: are these technologies producing better results, or are they just producing faster results?

Early case studies from brands like Meta and Dove suggest measurable improvements. Meta’s Advantage+ AI suite reportedly delivered an average of 22 percent higher return on ad spend, while backend models improved ad conversions by up to 5 percent. These are not game-changing figures on their own, but they point to efficiency gains that compound over time.

AI in advertising: three practical uses with measurable ROI

To understand AI’s impact, it is important to separate marketing headlines from operational facts. Below are three clear ways AI is delivering returns for advertisers today.

1. Automated ad generation and testing
   AI tools can generate dozens of ad variants using a single piece of content. These variants can be A/B tested across different demographics, platforms, and devices with minimal manual input. This saves time, but more importantly, it speeds up learning cycles and optimizes spend. For small businesses that cannot afford to run large-scale campaigns, the ability to quickly test and pivot offers a strategic advantage.
   
2. Personalized customer experiences
   AI-powered systems can analyze user data in real time to serve personalized messages, offers, and content. While personalization has been a marketing goal for years, AI makes it scalable. Platforms like Adobe Sensei and Salesforce Einstein are now accessible to mid-sized businesses, offering analytics and automated decision-making at scale.
   
3. Efficiency in content production
   AI-based video generators, image enhancers, and text tools are reducing the resources required to create high-quality content. Qualcomm’s internal AI reportedly saves over 2,400 hours per month on content production. When implemented properly, these tools can decrease production costs by up to 30 percent.
   

The strategic question for SMBs: adopt or wait?

For small and medium businesses, the question is not whether AI works. It is whether AI investment fits their current strategy and resources.

Here are three questions business leaders should ask before adopting AI tools:

• What marketing bottlenecks could AI realistically address?
  
• Do we have the data and content assets necessary to train or feed AI tools?
  
• How will we evaluate the performance of AI-generated campaigns versus traditional ones?
  

Businesses that lack a structured marketing workflow may not benefit from AI automation immediately. However, those with repeatable tasks, growing content needs, or expanding digital reach can benefit from selective AI integration.

Risks and limitations: not all automation is good automation

While AI can support advertising efficiency, it is not a plug-and-play solution. Poorly implemented tools can lead to brand inconsistencies, tone mismatches, and compliance issues. This is especially critical in regulated industries like healthcare or finance.

Moreover, AI-generated content often lacks cultural nuance, emotional depth, and contextual relevance. The campaigns that performed best at Cannes did not rely solely on AI. They used AI as a tool, not a replacement for strategy or creativity.

What the data shows: adoption is accelerating, but uneven

Recent surveys from Deloitte and eMarketer show that over 70 percent of large enterprises have adopted at least one AI tool in their marketing stack. In contrast, only 28 percent of small businesses report using AI in any marketing capacity. The gap is closing, but slowly.

This disparity is not just about budget. It reflects uncertainty around implementation, training, and long-term ROI. For small businesses to adopt AI successfully, vendor transparency, user education, and clear case studies will be critical.

A practical framework for evaluating AI in advertising

If your business is considering AI adoption, use the following framework to make a grounded decision:

• Identify the problem first: What are you trying to solve, content backlog, low engagement, slow testing?
  
• Start with low-risk tools: Consider starting with free or low-cost AI copy generators, automated video templates, or image editors.
  
• Measure everything: Implement KPIs for both manual and AI-driven processes. Focus on metrics like cost per acquisition, engagement rate, and time-to-publish.
  
• Iterate with feedback: Involve your team in testing and refinement. Ensure the brand voice and customer experience are preserved.
  

Looking ahead: AI as infrastructure, not novelty

As more advertising functions become automated, AI is shifting from a trend to a foundational layer in marketing operations. Like the shift to digital or mobile-first strategies in the past decade, this transition is not optional, it is structural.

However, its success depends on how intelligently it is integrated. Businesses that treat AI as a tool to enhance human creativity and decision-making will benefit. Those that pursue automation for automation’s sake may end up with generic, ineffective campaigns.

Conclusion: strategic adoption is key

AI in advertising is neither a gimmick nor a silver bullet. It is a suite of evolving tools with real potential for impact, if applied strategically.

For small businesses, now is the time to observe, learn, and test. Ignore the hype, focus on use cases, and build the internal muscle to integrate new technologies wisely.

AI may not replace marketers, but it will certainly change what marketing looks like. The future belongs to businesses that know the difference.