Google to retire Dynamic Search Ads: Will AI Max rewrite funnel?

When Google catches a cold, the advertising industry does not merely sneeze. It books an emergency consultation, checks dashboards, rewrites media plans and, more often than not, searches for answers on Google itself.

That reflex may be returning as the company moves to retire Dynamic Search Ads (DSA) and steer advertisers toward AI Max, a newer automation layer for Search campaigns that promises more reach, more conversions and, depending on who you ask, less visibility into how the sausage is made.

AI ad models

The move may sound like a routine product update. It is not. In India, where Google held 97.14% of the search engine market in March 2026, according to StatCounter, any redesign of how search demand is captured carries outsized consequences. There are platform changes, and then there are ecosystem changes. This looks closer to the latter.

The commercial context matters too. Google India’s gross advertising revenue rose 11.3% year-on-year to Rs 34,742 crore in FY25, up from Rs 31,221 crore a year earlier. Revenue from operations stood at Rs 5,340 crore, while net advertising revenue was reported at Rs 2,694 crore. Profit after tax was roughly Rs 1,437 crore. Put simply, India is not a side quest for Google. It is a serious business.

Google first introduced AI Max for Search campaigns in 2025 as a beta product built around broader query matching, automated creative customisation and landing page expansion. Earlier this month, it said Dynamic Search Ads, automatically created assets and campaign-level broad match would be upgraded into AI Max, while creation of new DSA campaigns would end in September 2026.

Translation: the optional future is becoming the default future.

That distinction matters in India, where search budgets are often ruthlessly performance-led. Many advertisers are less interested in abstract brand love and more interested in leads by Friday. For them, visibility into which query triggered spend, which page converted traffic and which segment wasted budget is not academic. It is survival.

Chirag Jagwani, Head of eCommerce and Modern Trade at beauty and skincare brand Fixderma, puts it plainly: “AI Max shifts DSA from page-led expansion to intent-led prediction, unlocking more long-tail scale. But you lose control on query visibility, URL targeting, and query-to-landing page mapping. For us at Fixderma, it’s more traffic, but less precision in who we’re actually reaching.”

For years, DSA occupied a useful corner of the search stack. It allowed advertisers to use website content to automatically match relevant searches, dynamically generate headlines and harvest long-tail demand that keyword lists often missed.

“This is less a product sunset and more a structural shift in who controls Search demand capture,” says Vibhor Mehrotra of VIVA Consulting, an independent domain expert. “From page-led matching to signal-led matching, Google will infer intent from multiple signals. That increases reach, especially in messy multilingual, conversational Indian search behaviour.”

Search in India

It was not glamorous, but it was legible. Marketers broadly understood what it was doing, where traffic was going and how to tighten the screws when needed.

AI Max changes that equation. Instead of relying primarily on page-led matching, it uses a wider pool of signals to infer user intent, decide relevance, customise messaging and choose landing destinations. Google says the product can drive 14% more conversions or conversion value at similar CPA or ROAS, with campaigns heavily reliant on exact and phrase match seeing up to 27% uplift. For performance marketers, those are not small numbers. They are catnip.

But as ever in adtech, free efficiency usually comes with terms and conditions.

Nikhil Khatri, Vice President, Biddable Performance and E-Market at LS Digital, frames the shift as one from deterministic targeting to probabilistic targeting. “With DSA, advertisers had visibility into search terms and could actively shape long-tail traffic using negatives, page targeting, and query-level insights,” he says.

“With AI Max, that control shifts into a more automated, AI-led system,” he says, and adds that “control hasn’t disappeared, it has moved from manual optimisation to influencing how the system learns.”

That may sound reasonable, and in many ways it is. Search behaviour in India is fragmented, multilingual and often gloriously messy. Consumers jump between English, Hindi, Hinglish and regional languages. Queries are conversational, misspelled, shorthand-heavy and shaped by local context. A human-built keyword map can struggle to keep up. A strong AI model may genuinely do better.

Yet this is where marketers may experience a sense of déjà vu. The industry has spent years living through the third-party cookie soap opera, where every change to Google’s roadmap triggered waves of panic, planning decks and strategic repositioning. Search may now be entering its own version of that cycle. When Google redefines the rails, everyone else must explain how to ride the train.

Jacob Joseph, VP of Data Science at CleverTap, sees the deeper shift clearly. “This move signals a shift from keyword coverage to intent interpretation,” he says. “AI Max changes that by abstracting those mechanics into a model that decides what intent means, and how to act on it.” He adds that advertisers will now be “working with a system that is constantly interpreting and recalibrating intent.”

Which brings us to a more uncomfortable question: if AI Max performs, will anyone care?

Revenue rivalries: https://www.exchange4media.com/digital-news/why-meta-is-finally-overtaking-google-in-ad-revenues-153800.html

History suggests many will not. Performance teams are pragmatic tribes. If cost per acquisition falls and volumes rise, philosophical objections about transparency tend to become much quieter. A black box that prints profitable conversions is still, in boardroom terms, a friend.

That is why Google’s own numbers matter. If AI Max consistently delivers stronger returns, adoption in India could accelerate quickly, especially among categories such as ecommerce, travel, education, BFSI, auto and marketplaces where search remains a lower-funnel workhorse.

But performance is not evenly distributed. Large brands with rich first-party data, cleaner websites, better product feeds and stronger measurement frameworks are more likely to benefit. Smaller advertisers with patchy sites, weak conversion tracking and inconsistent landing pages may simply automate their existing problems at scale.

This is where agency value also gets rewritten. Mehrotra says the shift is not about Google removing agencies, but removing low-value agency work. “The agencies that survive will move from campaign managers to growth intelligence partners,” he says.

Instead, agencies may need to move into governance, experimentation, measurement, creative systems and business strategy. The premium skill may no longer be bid management. It may be signal management.

Sini Magon, COO and Global Partner at Grapes Worldwide, offers the more optimistic reading. “The move away from Dynamic Search Ads reflects a clear change in how search advertising works today,” she says. “With newer formats like AI Max, the focus is clearly moving toward more adaptive, intent-led advertising that can respond to user behaviour in real time.”

She adds that brands investing in “first party data, clear audience signals, compelling creatives, and well structured landing pages” will be better positioned.

There is also the matter of dependence. In a market where Google’s search dominance remains overwhelming, advertisers cannot easily shift equivalent budgets elsewhere if they dislike the rules of engagement. That makes every migration less optional than it appears.

Google’s wider hold over India’s digital economy only sharpens that point. The company has said its Play and Android ecosystem generated Rs 4 lakh crore in revenue for app publishers and the wider economy in India in 2024. Search is one pillar of a much larger machine. Though as we’ve pointed out before, that machine is seeing new challenges.

Google’s play

None of this means AI Max is bad for advertisers. It may prove highly effective. It may unlock demand that manual systems routinely missed. It may even spare thousands of overworked media planners from another afternoon spent arguing over match types in spreadsheet tabs last edited during the first Modi government.

But it does mean Indian marketers should read this moment correctly. Google is not merely replacing one campaign type with another. It is nudging Search from a system advertisers operated toward one that advertisers supervise.

And as always with Google, the real test will arrive after the rollout decks end and the invoices begin.