Our Take on the Latest AI Features from Meta and Google Ads
TL;DR:
Meta and Google Ads are doubling down on AI. Expect more automation across ad copy, visuals, and targeting.
New features include AdLlama, AI chat-driven personalization, and Google’s AI Mode and AI Max.
The benefits: Faster creative testing, smarter targeting, and better efficiency.
The risks: Brand drift, generic creative, and overreliance on automation.
Our approach: Use AI for inspiration, not execution. Set guardrails, test with intention, and keep humans in the loop.
AI keeps evolving and ad platforms are moving with it. Meta and Google’s latest features make automation smarter and faster, but that doesn’t mean hands-off marketing works. Here’s how we’re making sense of it, and keeping human-driven strategy in the driver’s seat.
What’s New with Meta’s AI Tools
Meta has rolled out a new wave of AI-driven updates designed to automate ad creation from start to finish. These include everything from AI-generated ad copy and visuals to personalization powered by chat data. Some of the newest features include:
AdLlama, Meta’s experimental model that refines ad copy based on what’s performed best in the past.
AI-generated visuals and video, where still images can now be animated and enhanced automatically with transitions or background music.
AI chat integration, which uses topics people discuss with Meta’s AI to influence which ads they see (for example, someone chatting about home upgrades might later see energy-efficiency content).
It’s a big step toward fully automated advertising, and while the tools are impressive, they’re not flawless. We’ve seen examples of brand tone slipping or visuals veering way off-brand when AI gets too involved.
How we’re approaching it:
We’re continuing to develop and test ad variations ourselves, using AI only for inspiration, not execution.
What’s Happening with Google’s AI Features
Google’s own AI upgrades are rolling out just as quickly. The platform has been steadily building new automation layers into its existing campaign types, focusing on smarter intent matching and adaptive creative.
Here’s what’s new on the Google side:
AI Mode is Google’s conversational search layer (think ChatGPT inside Search). Ads are already being tested within these AI responses.
AI Max for Search enhances campaigns with automated creative variations, expanded keyword matching, and dynamic targeting.
Visual optimization in Demand Gen campaigns automatically resizes and stylizes assets to fit multiple placements.
Improved measurement tools use AI modeling to fill in attribution gaps and refine conversion insights.
While Meta’s AI updates lean more toward creative automation, Google’s changes are about smarter intent understanding and performance optimization.
How we’re approaching it: We test new features in parallel with existing setups, never replacing control completely. We provide clear creative inputs, strong copy, optimized landing pages, and brand guidelines, so Google’s AI has quality (and accurate) data to work with. Then we rely on the data to inform further decisions.
Where We See Opportunity (and Risk)
The Upside
Faster creative testing: AI can generate ad variations at a fast pace.
Smarter targeting: AI uncovers new audience intent and emerging keywords.
Incremental efficiency: Even small gains in CTR or relevance compound over time.
Personalized relevance: Ads may align more closely with what users care about.
The Risks
Brand Mis-Alignment: Auto-generated content can misrepresent a product service or tone.
Generic creative: If everyone uses the same tools, ads start to blend together.
Reduced transparency: AI may create copy or headlines pulled from content you didn’t intend to promote.
Over-reliance on automation: ‘Set it and forget it’ leads to inefficient ad spend and poor performance.
Our stance is simple: AI should make marketing smarter, not on auto-pilot. It’s a tool, but never a replacement for strategy or creativity.
How We’re Putting This Into Practice
When we use AI-powered ad features at Avenue, we take a structured, human-first approach:
Set guardrails before testing: Define brand voice, messaging rules, and creative do’s and don’ts before enabling any automation.
Test with intention:Run new features against a control group to measure whether they actually improve performance.
Keep a human in the loop:Review all AI-generated assets manually and monitor campaign results regularly to catch tone or targeting drift early.
Share learnings across campaigns:Feed results back into our creative and keyword strategies to guide future testing.
This keeps the benefits of AI ( speed, scale, efficiency ) while maintaining what matters most: Brand integrity, accuracy, and performance transparency.
What You Can Do Now
Even if you’re not testing new AI ad features yet, you can prepare your campaigns today.
Audit your creative library: AI performs best when it has strong inputs to learn from.
Document your brand voice and values: The clearer your boundaries, the safer your automation.
Keep content fresh and detailed.: Google’s AI sometimes pulls from site copy, so clear messaging helps.
Track first-party data: Strong signals make AI optimization smarter.
Stay updated: Meta often rolls out new AI tools to select advertisers first, so early awareness matters.
Final Thoughts
AI is becoming part of every ad platform’s DNA. That’s not a reason to panic, but a timely reason to plan. The marketers who will win in this next phase aren’t the ones who hand over control to algorithms, but the ones who collaborate with them and leverage this emerging technology strategically.
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