Agentic buying: automated media buying arrives in 2026

What agentic buying is and why everyone is talking about it now

Agentic buying means media buying managed by autonomous AI agents: software that plans, buys and optimizes ad space without waiting for human instructions on every single decision. It's not just another feature inside a platform. It's an architectural shift in how budget moves.

According to research by IAB Europe reported by Digiday, 58% of advertising executives expect this model to reach operational scale within a year. The industry draws a parallel with mobile: for years people said it would become the main channel, until one day it really was, and those who hadn't prepared had to play catch-up.

What the source numbers really say

The key finding is clear: more than half of industry executives believe agentic buying is not a marginal experiment but an imminent evolution. IAB Europe is the European association for the digital advertising industry, so the people answering these surveys are those who decide budgets and strategy, not academic researchers.

What does that 58% mean in practice?

• Platforms are already building infrastructure for autonomous agents. They aren't waiting for the market to be ready.
• Those who buy media on behalf of client companies, whether agencies or in-house media buyers, will see their role change sooner than you think.
• Those who sell ad space, such as publishers and ad sales houses, will have to adapt their APIs and formats to talk to software, not just to people.

Who needs to act this week, and who doesn't

If you run campaigns with small budgets and still optimize ads manually on Meta or Google, agentic buying won't affect you tomorrow morning. But the platforms you already use are adding increasingly advanced automation: what you now call "smart bidding" or "Advantage+" is the precursor of this model. Understanding the direction helps you read the choices Meta and Google are making on their platforms, as the analysis of how Meta is structuring its 2026 Christmas campaigns with AI shows.

If instead you manage significant budgets across multiple channels, have a media buying team or work with an agency, the topic is already operational:

• Are your campaigns structured so an agent can read and optimize them? Clean data, clear naming conventions, measurable goals.
• Does your team know where human control must stay and where it can delegate?
• Are your ad tech vendors evolving in this direction?

The real risk: delegating without understanding what you delegate

The most common mistake with any new ad automation is switching it on without setting boundaries. With agentic buying the risk grows: an autonomous agent can optimize toward metrics that don't match your real goals, spread budget across inventory (available ad space) you haven't vetted, or react to short-term signals that hurt your brand positioning.

This isn't a theoretical problem. It's the same one you already face with Google's Performance Max campaigns, where the algorithm decides where to go and the advertiser's control shrinks. The issue of Customer Lifecycle Goals in Google Ads is a concrete example of how platforms are already shifting control to the machine, and of when it makes sense to follow them and when it doesn't.

The same reasoning applies to new formats: ChatGPT click-to-chat ads work on a completely different logic from traditional website traffic, and they require redefined goals even before you launch them.

Three things to do before the change goes mainstream

You don't need to wait for agentic buying to become the standard to start preparing. Here are three concrete actions, in the order that makes sense:

• Clean up your campaign data. Autonomous agents work on signals: if your data is fragmented, poorly labeled or missing correctly tracked conversions, the automation optimizes in a vacuum. Start here, regardless of everything else.
• Define your goals in measurable terms. "Increase brand awareness" is not a goal an agent can optimize. Cost per lead, average order value, repurchase rate: those are. The topic of the hidden costs of AI in marketing shows clearly where automation without clear goals erodes efficiency instead of boosting it.
• Map where you want to keep human control. Creativity, brand positioning, decisions about excluding sensitive contexts: these are areas where human oversight isn't a cost, it's protection.

If you want a fuller picture of how digital advertising and paid media are evolving, the topic cluster gathers the most relevant updates for anyone running campaigns in Italy.