Amazon’s AI Ad Strategy Emerges in a Market Where 74% of SMBs Use AI Tools

Amazon’s new AI tools for advertisers arrive as marketers look for ways to work faster without sacrificing strategy.

In a recent Amazon Ads study, 87% of SMB marketing leaders said AI will support future growth by freeing up time for priorities like targeting and audience planning.

This optimism follows industry patterns in generative advertising adoption, where platforms from Google to Meta report growing AI-tool uptake. 

The same Amazon study found that 74% of SMBs are already using or actively testing AI tools for advertising, but many still feel overwhelmed by the number of tools available. 

These findings raise questions about whether faster content generation actually moves business outcomes.

That tension is at the heart of Amazon’s rollout of its upgraded Creative Assistant inside Amazon Ads’ Creative Studio.

It’s also one agency like Bobo Digital, a leading performance marketing firm, is watching closely, as more brands adopt automation without clear creative direction.

“We’re seeing a lot of brands rush into AI tools without mapping out the basics: audience, funnel stage, or message intent,” says Ben Debono, founder and director at Bobo Digital.

“Without that foundation, automation just creates more noise.”

That’s the risk, even as Amazon’s chatbot-style Creative Assistant promises to generate full multimedia campaigns, including scripts, images, edited videos, and voiceovers, in seconds.

The service is designed to simplify creative production for advertisers who lack in-house creative teams or big agency support.

Jay Richman, VP of product and technology at Amazon Ads, has described the tool as a way to help smaller advertisers grow their business by automating creative tasks that once required dedicated teams. 

“We see a huge opportunity to expand the creative horizons for brands of all sizes,” he shared in an Amazon blog post, describing the Creative Studio. 

But observers caution that the ease of producing ads should not replace thoughtful campaign strategy.

Why Speed Alone Won’t Win, and Strategy Still Matters

Despite the hype around automation, data shows that Amazon’s ad business is still very much performance-driven. 

In 2025’s second quarter, Amazon Ads revenue climbed 23% year-over-year to about $15.7 billion, marking one of its strongest growth spurts yet. 

In the third quarter, ad sales rose another 24% to $17.7 billion,  bolstered by Prime Video and expanded formats. 

These figures illustrate that advertisers continue to invest heavily in measurable placements that drive commerce outcomes.

For many brands, the recognition that automation speeds up creation is already clear.

Nonetheless, results still hinge on thoughtful audience targeting and optimization.

According to WARC Media’s Platform Insights report, Amazon’s retail media revenue is projected to exceed $60 billion in 2025, up from about $56 billion in 2024. 

These revenue numbers show Amazon’s growing dominance in digital ad spend.

Yet this growth masks the broader industry reality that automation does not guarantee a competitive advantage if campaigns are not backed by data-driven planning and iterative testing.

Another signal of the challenge is how SMBs that are still using AI tools report saving, on average, about 5.6 hours of work per week, according to Amazon.

That’s roughly 30 working days annually, which proves the strong efficiency gain. 

But saving time does not automatically translate to better outcomes without a clear plan for where and how ads should drive business metrics like sales or customer acquisition.

How Brands Should Rethink AI-Driven Advertising

1. Build Strategy Before You Scale Creative Output

AI tools can now generate ads in minutes, but brands still need to define objectives, audiences, and success metrics before hitting that “generate” button.

Amazon’s Creative Assistant can quickly produce scripts, images, and videos, yet without strategic direction, brands risk flooding campaigns with interchangeable creative.

Winning advertisers treat AI as a production layer, not a decision-maker. 

They map funnel stages and audience intent first, then use AI to create variations aligned to those goals.

“Automation helps brands move faster, but speed only works when direction is clear,” said Debono.

“Strategy determines whether AI output drives results or just adds noise.”

2. Test Formats and Targeting With Discipline

Creative automation makes variation easy, but testing still determines what performs. 

A recent industry study found that 70% of performance marketers actively test new ad formats due to diminishing returns without experimentation.

“AI gives brands more options, but testing tells them which ones actually work,” xx added. 

Structured A/B testing remains essential to avoid creative fatigue and uncover meaningful performance differences.

3. Align AI Use With Performance Goals

AI can improve results when applied intentionally. 

Data shows AI-generated ads deliver a 22% higher click-through rate than non-AI ads, on average.

“Performance improves when AI supports optimization, not when it replaces judgment,” explained Debono.

Brands that connect AI output to clear KPIs see measurable gains rather than surface-level efficiency.

What This Means for Modern Marketers

AI is lowering creative barriers, but it is also raising the bar for relevance and effectiveness. 

As access to automation expands, differentiation will come from strategy, testing discipline, and performance insight. 

Let’s face it, the world of ads is changing, and anyone can generate a social post straight from their desktop. 

But this is exactly why the real competitive advantage now lies in strategy.