Over 70% of global ad spend will pass through AI-driven self-service ad platforms by 2028, according to data from Gartner. This is up from 50% in 2025, highlighting how increasingly important AI could become to the purchase and distribution of ads over the next few years.
Gartner warns in its forecast that the increasing usage of AI could undermine transparency, measurement and accountability for advertisers, weakening their ability to direct and manage campaigns, while also potentially raising costs. But there are numerous actions brands can already take to mitigate this situation, and tighten their control over how ad spend translates into results.
AI ‘exerting greater influence over how marketers reach their audiences’
“AI is not merely helping marketers execute campaigns faster,” said Eric Schmitt, VP Analyst in the Gartner Marketing practice. “Advertising platforms are using it to exert greater influence over how marketers reach their audiences, what they pay, and the outcomes they achieve.”
Gartner forecasts that, over the next few years, AI will become more embedded in the processes of audience selection and pricing, something which may insert an uncertain, uncontrollable element in self-service ad platforms.
“AI was expected to make advertising more efficient, but improved platform economics does not necessarily translate into lower costs for the advertiser,” added Schmitt. “CMOs need independent evidence that they’re getting the returns they expect.”
CMOs need independent evidence that they’re getting the returns they expect
According to Schmitt, AI is already operating in various ways within self-service platforms, mostly in relation to deciding who is exposed to which ads, and at what times and in what contexts. “The decision about what ad to show someone is made in the moment, and typically based on many factors, each of which may employ AI-generated reasoning or score,” he tells Raconteur.
AI’s calculate a number of factors, including the likelihood that a user will pay attention to an ad, that they’ll take an action, the likelihood that ad exposure will contribute to objectives, the impact of exposure on cost, and the wider impact of the ad’s delivery.
Near-term versus long-term
Yet Schmitt explains that platforms are also using AI to make other decisions. This includes deciding the “number of ads a person is exposed to in the platform environment,” as well as the “choice and sequence of which ad placement(s) to use” and the “specific creative version to show.”
And with AI moving into other areas (e.g. campaign planning, audience targeting, campaign monitoring), Schmitt affirms that this could create issues for brands and marketers. This is particularly the case when “the great majority” of AI functions are focused on near-term outcomes, whereas core ad spend goals such as brand awareness and recognition are generally long-term endeavours.
He adds, “Advertisers with brand-building, top-of-funnel goals must now be especially vigilant when spending money on opaque, algorithmically driven channels with respect to assessing confidence that a given ad buy is achieving the desired goals at the efficiency (e.g. impression CPM) required.”
The more influence AI has over advertising decisions, the more important independent measurement becomes
Another disadvantage for marketers is that using AI-based platforms usually requires establishing API connections to these platforms, as well as sharing proprietary signal data. This imposes a technical burden on the advertiser, according to Schmitt, while raising “important questions around data governance.” It also puts marketers in regulated industries at a disadvantage in relation to marketers in other categories.
Given such cons and risks, Gartner’s forecast advises brands and marketers to take three steps in particular to improve their oversight and control of ad spend.
Firstly, marketers should prioritise the most strategically important ad platforms, concentrating resources only or mostly on the channels that deliver the strongest results. Secondly, they should create a list of additional platforms they can use selectively to test new markets and potentially expand their reach. Thirdly, and perhaps most importantly, marketers should prioritise platforms that offer greater transparency and enable independent measurement, so that they can continue to evaluate and compare results.
“The more influence AI has over advertising decisions, the more important independent measurement becomes,” explains Schmitt. “CMOs need confidence that platform performance reflects real business impact, not just platform-reported results.”
The future is coming fast
Examples of self-service and other ad platforms integrating AI have been proliferating in recent months. In November, Amazon launched its Ads Agent tool, which automates many of the processes inherent to self-service campaigns. Similarly, Criteo launched its self-service Criteo Go ad platform at the end of March, enabling SMEs and growth-stage companies in the UK and the US to harness an AI-based solution that “automatically optimizes spend to drive the best outcome.”
Then there’s the fact that OpenAI has very recently branched out into providing ad space with ChatGPT, which appears to be gaining traction as a channel for advertising. In May, it launched a self-service platform for its ads, with Criteo reporting that over 1,000 brands had used its APIs to launch campaigns on ChatGPT. Even more impressively, the digital advertising company revealed that ads on ChatGPT were, on average, garnering click-through rates “roughly three times higher than comparable formats in other environments.”
Such data ultimately supports Gartner’s prediction of a future where most ad spend flows through AI-powered self-service channels. Of course, time will tell as to just how prepared brands are for such a future.
Over 70% of global ad spend will pass through AI-driven self-service ad platforms by 2028, according to data from Gartner. This is up from 50% in 2025, highlighting how increasingly important AI could become to the purchase and distribution of ads over the next few years.
Gartner warns in its forecast that the increasing usage of AI could undermine transparency, measurement and accountability for advertisers, weakening their ability to direct and manage campaigns, while also potentially raising costs. But there are numerous actions brands can already take to mitigate this situation, and tighten their control over how ad spend translates into results.
