Enterprise marketers budget for AI search as traffic channel grows

Enterprise marketers are no longer treating AI search like a lab experiment. A survey of 300 marketing executives at large companies points to a real budget shift, with AI discovery now carrying measurable traffic impact and traditional search still expected to remain a major source of visits in 2026.

That is the important takeaway for agencies: clients are not choosing between SEO and AI search. They are moving toward a two-layer search stack, and the shops that can show how those layers work together will be the ones winning new retainers.

AI search is not replacing search, it is sitting on top of it

The report’s most useful signal is also the simplest one: AI search is additive. Executives do not appear to believe that AI answers will wipe out classic search behavior, and they still expect traditional search to remain a major traffic channel next year. That should change how you position your services.

If you sell AI search as a replacement for SEO, you are already behind. If you sell it as a new discovery layer that amplifies visibility across the buying journey, the pitch becomes much more believable. In practical terms, that means your offer should bundle classic search work with AI-specific visibility work instead of forcing a false either-or decision.

For agencies, the business implication is clear. Large brands are starting to budget for AI search because they see traffic moving there, and smaller agencies need packaged offers ready before clients ask for them. The winning positioning is not “we do AI search too.” It is “we help you show up wherever buyers ask, compare, and validate.”

The measurement problem is where the money will move

The report puts a lot of weight on attribution, and that is where the real agency opportunity lives. Executives say they are struggling to separate traffic and conversions coming from ChatGPT-like interfaces, AI Overviews, and standard Google results. That is not a strategy problem so much as an infrastructure problem, and clients will soon start demanding answers their current reporting stacks cannot cleanly produce.

This is exactly where you can create demand. If you can help a brand understand which surfaces are driving discovery, which ones are helping conversion, and where the overlap exists, you become more than a traffic vendor. You become the team that can connect AI visibility to revenue.

The proof points you should start gathering are concrete:

• Share of traffic coming from AI-assisted discovery
• Visibility in AI answers and summaries
• Mentions or citations in generative responses
• Assisted conversions from users who first touched AI search, then returned through organic search
• Pipeline impact by surface, not just by channel

Clients are going to ask harder questions about where pipeline comes from. If your reporting can only show rankings and generic sessions, you will look underprepared. If you can show how AI search and organic search work together, you have a retainable service line.

Behavior is fragmented, so the workflow has to be too

The report also makes a point that matters more than it first appears: people do not use AI search in a clean, linear way. They may use AI tools for ideation or comparison, then return to traditional search for validation, shopping, or follow-up research. That means the buyer journey is not splitting into separate worlds. It is becoming more layered.

For agencies, that kills the old habit of building siloed dashboards and pretending one channel owns the whole story. You need workflows that cover both retrieval and decision support. In plain English, that means content and measurement have to serve two jobs at once: get the brand discovered in AI environments, and help users verify, compare, and act once they move back into search.

That is a different kind of search strategy. It is less about chasing one keyword list and more about designing a path across surfaces. A user may encounter your brand in an AI summary, confirm it in a search result, and convert after a follow-up visit from organic search. If your team cannot see that sequence, you will undervalue the work that is actually moving the buyer.

What to build first if you want the retainer

You do not need to invent an entirely new agency model to capitalize on this. You need to productize the parts that clients will ask for first, then prove them quickly. The report suggests a market that is still early enough for smart agencies to define the categories.

Start with these capabilities:

• A clear AI search visibility audit that shows where the brand appears in AI answers and where it does not
• A combined reporting view that tracks AI search, AI Overviews, and traditional organic search together
• Content recommendations built for both retrieval and decision support
• A measurement framework that ties visibility to revenue, not just impressions
• A client-ready explanation of how AI discovery and search validation interact during the buying journey

The first package you sell should not be a vague innovation workshop. Make it a defined audit plus reporting sprint, with a follow-on roadmap. That gives clients something they can budget for now, and it gives you a path into ongoing work when they realize the attribution gaps are bigger than they expected.

The agencies that win will prove the overlap

The report’s real message is not that AI search is taking over. It is that search is getting wider, messier, and more measurable at the same time. Enterprise marketers are already budgeting accordingly, and they will keep funding the teams that can help them navigate both the AI layer and the traditional search layer without guessing.

That is where the next wave of retainers sits: in proof, not hype. The agencies that can show how AI search contributes to discovery, how organic search still carries the validation load, and how both feed revenue will have the cleanest story to sell.