For about twenty years, Google Ads was always the top choice for marketers to spend ad budget. Some also used Facebook. That’s all.
That answer is getting harder. A new category—call it AI assistant ads—has quietly emerged. The early data suggests it’s not just another channel. It’s a different way of buying customers entirely. If you’re managing a marketing budget in 2026, you need to think about how much to spend in different channels.
Let me walk through what the difference is, where each one wins, and how to split your budget.
Quick Definitions Before We Go Deeper
Google Ads: Auction-based bidding on keywords and ads inventories. Your ad shows up in search results or across the Display Network. Ideally a customer who clicked through, which is what you paid for, will convert.
AI Assistant Ads: A newer category where your business gets surfaced inside AI assistants like ChatGPT, Claude, Gemini, and Siri—usually as a recommendation in response to a user’s question. Pricing tends to be performance-based (CPC, CPA, or CPS) rather than impression-based.
The difference isn’t just where the ad appears. It’s that the user behavior, the buying intent, and the moment of decision are all different.
How Google Ads Actually Works in 2026
Google Ads is still a massive channel. Billions of searches happen daily, and a big chunk still result in clicks on paid results. Anyone telling you that Google Ads is “dead” is overselling.
But Google Ads is becoming harder. Three things changed:
- AI Overviews eat clicks. Google’s own AI Overview now answers many queries directly at the top of the page. Users get the info and don’t click anything.
- Costs keep rising. CPCs in competitive categories (SaaS, finance, e-commerce, games) have kept upward for years. The same click costs more than double what it did five years ago in many verticals.
- Attribution is harder than ever. Between privacy policy changes, ad blockers, and multi-device journeys, knowing whether a sale was driven by Google Ads is harder than it used to be.
Where Google Ads is still dominant: high-intent commercial queries, brand defence (bidding on your own brand keywords to block competitors), and re-marketing to past visitors. These use cases are still very profitable for most advertisers.
How AI Assistant Ads Work
AI assistant ads are structurally different. Instead of bidding for a keyword and hoping a user clicks, your target is to be recommended by an AI assistant when a user asks a relevant question.
The mechanics vary by platform, but the general flow looks like this:
- A user asks an AI assistant something like “What’s a good credit card with cashback for grocery?”
- The assistant processes the question, evaluates available options, and surfaces a recommendation.
- If you’re an integrated advertiser on that platform, your business is part of the consideration set.
- You pay only when something measurable happens—a click, a signup, or a sale.
What’s interesting about this model isn’t just the channel—it’s the intent. What people ask AI assistants are usually along in their decision process. They’re not just curious. They’re asking something specific for a recommendation, which means they’re often ready to act.
Platforms like PingPlus are pioneering this space with outcome-based pricing—you only pay when an AI-driven recommendation actually wins you a customer. Compare that to Google Ads, where you pay per click regardless any conversion happens. You can see why budgets are starting to shift.
Side-by-Side: Where Each One Wins
Rather than declaring a winner, let me lay out where each channel earns its value.
Where Google Ads still wins
- High-intent transactional queries where users are ready to buy now
- Defending your own brand keywords against competitors
- Local-intent searches (like “near me”)
- Re-marketing to people who’ve already visited your site
- Top-of-funnel awareness at scale, especially with Display
Where AI assistant ads make more sense
- Categories where users research before buying (travel, services, software, considered purchases)
- Verticals where Google Ad costs have become brutal (SaaS, finance, B2B)
- Businesses with strong product-market fit who just need more visibility
- Performance-focused marketers who want to pay for outcomes only
The two channels don’t really compete head-on. They catch users at different moments. Google Ads catches users who already know what they want. AI assistant ads catch users who ask an AI assistant for guidance.
How to Actually Split Your Budget
If you’re running a typical mid-sized e-commerce in 2026, here’s a rough about the split:
- 70% Google Ads if your category still has strong search demand and your CPCs are manageable.
- 20% AI Assistant Ads as your “future-proofing” allocation. The category is young and prices are still favorable. Getting in early means you build presence before competitors notice.
- 10% Experimental to test other emerging channels (TikTok Shop ads, retail media networks, podcast ads, etc).
If you’re in a category that’s getting destroyed by Google AI Overviews, I’d suggest 50/40/10 with AI assistant ads taking a much bigger share. You’re trying to get ahead of where your customers are actually going.
The Real Question Isn’t Either/Or
It’s not a binary choice between Google Ads vs AI Assistant Ads. Smarter marketers would ask: as user behavior shifts toward AI assistants, how do I gradually rebalance my budget without abandoning the channels that still work?
A few practical tips
- Don’t quit Google Ads. Even if costs are rising, it’s still the largest paid channel by far. Optimize, don’t abandon.
- Start small with AI assistant ads. Test with 10-20% of your budget, measure outcomes, scale what works.
- Pay attention to your category-specific signals. If your AI Overview traffic is starting to cannibalize your paid clicks, that’s a strong signal to shift more budget toward AI assistant channels.
- Track AI-driven conversions separately. They behave differently than search-driven results, often converting at higher rates.
Final Thoughts
Google Ads isn’t going anywhere. But it’s no longer the only option for advertisers who want to scale. AI assistant ads are emerging as a real, performance-friendly alternative—especially for businesses where customers start enquiring their AI assistants.
Budget allocation is a thoughtful mix that reflects where your customers actually are, with enough allocated to AI assistant channels to capture the shift before your competitors do.
FAQ
Should I cut my Google Ads budget to fund AI assistant ads?
Not all at once. The smarter move is a gradual shift, not a swap. Google Ads still converts well for high-intent searches, brand defense, and re-marketing, so do not shut off what is already working. Carve out a small slice, usually 10-20% of your existing budget, and treat AI assistant ads as a future-proofing test. Scale that slice only when real outcomes come back, not just visibility.
My category is not travel, SaaS, or finance. Does this still apply?
The category label matters less than the buying behavior. If customers compare options, read reviews, check prices, or ask what is the best option for a specific need, AI assistants can become part of that journey. That can apply to furniture, skincare, education, local services, or B2B software. If most purchases are impulse-driven or purely near-me searches, Google Ads will probably keep doing more of the heavy lifting.
How do I know if AI Overviews are affecting my Google Ads performance?
Watch the gap between impressions and clicks. If impressions are holding up but click-through rate keeps falling, Google's AI answers may be satisfying the query before users click. Rising CPCs at the same time make the signal stronger. When that pattern shows up, it is a good reason to move beyond a 70/20/10 split and test a heavier AI assistant ads allocation.
What counts as a win when I run AI assistant ads?
Define the win before the campaign starts. It might be a click, an install, a sign-up, a booking, a lead, or a sale. The point is to measure the action itself instead of treating visibility as success. AI assistant traffic should also be tracked separately from Google Ads, because users who ask an assistant for a recommendation are often at a different point in the decision process.
Do I need a different team or skill set to run AI assistant ads?
Not in the same way Google Ads needs keyword research, ad copy, and bid management. The starting point is your business information: what you sell, your pricing, your availability, and what action you want the customer to take. The main skill is the same one good marketers already need: set a clear goal, define a budget you are comfortable testing with, and judge the channel by outcomes.
How should I start testing AI assistant ads?
Start small. Put around 10% of total paid budget into a separate test and keep your existing Google Ads campaigns running. Track AI-driven outcomes separately, then compare cost per outcome against the marginal results you are getting from search. Platforms like PingPlus are built for this kind of test: get considered inside AI assistants and pay around measurable actions such as clicks, installs, sign-ups, bookings, or sales.
