14 April 2026

Google’s AI creative tools explained: what to use, what’s changing, what’s being deprecated

In summary

• Google’s AI creative tools are expanding quickly, but overlap is driving confusion, not capability
• The real shift is from static creative assets to adaptive, system-driven creative
• Success depends less on tools, and more on how data, signals and creative connect

The real problem isn’t capability, it’s clarity

If you’ve opened Google Ads or Merchant Center recently and thought, “haven’t I seen this somewhere else?” you’re not alone.

Right now, the challenge isn’t a lack of capability. It’s that everything looks like it does the same thing.

New tools. Old tools renamed. Features appearing in multiple places. And very little clarity on what’s actually worth using.

So, rather than list every product (because that changes monthly), it’s more useful to step back and answer three questions:

• What should you actually be using today?
• What’s changing underneath the surface?
• And what’s effectively being phased out, even if it’s not labelled that way?

Much of the confusion comes from mixing two different categories, tools designed for asset creation, and systems designed for performance and optimisation.

What to use right now (and why it matters)

There are a few areas where tools are becoming more useful, particularly around asset creation and creative iteration.

Product Studio (Merchant Center)

For retail and eCommerce, this is where most of the momentum is.

Image generation, background expansion and lightweight video, all tied directly to product feeds.

It’s improving quickly and, importantly, it connects to performance.

AI image and asset creation tools (beyond Google)

There’s also been a rapid increase in standalone image and asset creation tools, both within and outside of Google.

Platforms like Canva have seen rapid growth here, increasingly embedding AI into design workflows and beginning to bridge the gap between asset creation and activation, including direct integrations into Google Ads.

These are less about performance optimisation and more about:

• speeding up production
• generating concepts
• reducing reliance on manual design workflows

They’re useful, but they sit slightly differently in the stack. They don’t replace strategy, they support it.

AI creative inside Google Ads

This is where most teams will interact with AI day-to-day.

Think:

• image generation
• copy variations
• asset suggestions

It’s less about producing a final ad and more about enabling faster iteration and variation where it makes sense.

Emerging creative hubs (Studio environments)

Google is clearly moving toward centralising creative tooling again.

We’ve already seen tools like Ads Creative Studio folded back into broader environments.
Expect continued consolidation here.

What’s actually changing (this is the real shift)

The tools are the surface layer. What’s really changing is how creative works.

From assets to systems, creative used to be: one campaign, one set of assets.

Now, it’s one system generating, testing and iterating continuously.

The question is no longer, “what ad do we build?” It’s “what inputs are we feeding the system?”.

Creative is now data-dependent

AI doesn’t create in isolation. It responds to what it’s given.

That includes:

• product feeds
• audience signals
• conversion data
• measurement frameworks

Which means creative performance is now directly tied to the quality and structure of those inputs.

If the inputs are inconsistent, incomplete or poorly structured, the outputs will be too. That’s where we see most issues. Not in the tools themselves, but in what’s feeding them.

That said, not all creative should be driven by performance alone. Brand still plays a critical role, particularly in how you show up consistently, build recognition and create differentiation.

AI-driven creative systems are powerful for iteration and scale, but they work best when they’re grounded in a clear brand foundation.

Overlap isn’t accidental

A lot of the confusion comes from the same capabilities appearing in multiple places. That’s not a mistake.

Google is:

• embedding AI into existing workflows
• testing where features get used
• gradually consolidating environments

So, while it feels fragmented now, it’s part of a longer shift toward fewer, more connected systems.

What’s being deprecated (even if it’s not called out)

You won’t always see formal deprecation notices. But you can see what’s becoming less relevant.

Manual creative at scale

Still important for brand, but not for iteration and performance.

Static campaign structures

Rigid setups limit how AI systems can optimise.

Creative disconnected from data and media

This is the biggest shift.

Creative can’t sit separately anymore, it’s now part of a connected system. Platforms like CM360 are increasingly acting as the system of record, connecting creative, media and measurement into a single framework.

What marketers should do now

This is where the focus needs to shift from tools to execution.

• Design for variation, not perfection (for performance outcomes): Build systems that test and learn, brand creative and strategy require a different approach.
• Simplify the stack: More tools often create more fragmentation, not better outcomes
• Connect creative to measurement early: If you can’t measure it properly, the system can’t optimise it

The bigger picture

It’s easy to focus on which tool does what.

But the more useful lens is this: Creative is no longer a fixed output. It’s an adaptive layer within your marketing system.

And the teams getting the most value aren’t using more tools. They’re connecting them better.

Louder’s recommendations

• Treat AI creative as part of a system, not a standalone capability
• Invest in clean, structured data to improve creative outputs
• Align creative, media and measurement early in the process
• Reduce tool sprawl and focus on integration over expansion
• Build workflows that support continuous testing and iteration

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