Marketing leaders expect AI to automate more than a third of all marketing work within two years, according to new research published today by Gartner. AI currently drives automation across around 16% of marketing activity, but CMOs surveyed expect this to more than double, reaching 36% by 2028. The finding comes from a Gartner survey of 402 CMOs conducted between August and October 2025, released at the Gartner Marketing Symposium in London.
As AI takes on a growing proportion of marketing execution, the volume of AI-mediated touchpoints across the customer journey will rise sharply. How organisations manage that shift will increasingly define how customers experience their brands.
The Competency Trap
The research identifies a fault line running through marketing organisations right now. A majority of CMOs remain in an experimentation phase, testing AI use cases focused on productivity and efficiency gains. A smaller but growing group, which Gartner labels "market-shaper" CMOs, have moved beyond this and are using AI to drive enterprise growth, customer confidence and competitive differentiation.
Gartner warns that CMOs who fail to make the transition risk falling into the "AI competency trap", as Jay Wilson, VP Analyst in the Gartner Marketing Practice, explains: “Most CMOs are currently stalled in at least one AI competency trap, where their early AI success limits their future progress… CMOs reach a point where further investment simply doesn’t deliver the return they’re expecting. This inflection point is particularly dangerous in marketing’s AI journey, because leadership’s expectations are so high.”
To help CMOs navigate the journey, Gartner analysts at the Symposium outlined a three-stage maturity model. The first stage, AI Curious, describes organisations piloting tools for efficiency. The second, AI Competent, sees teams scaling multiple use cases but encountering diminishing returns. The third, AI Confident, is where CMOs integrate human judgement with AI to reshape operating models, customer engagement and enterprise decision-making. For organisations trying to build a coherent CX AI roadmap, the model offers a useful framework for assessing where they currently sit and what progress requires.
Caution Still Required
Despite the promise of automation, separate Gartner consumer research published in March is a reminder to consider customer experience within implementation strategies. A Gartner survey of 1,539 US consumers found that half would prefer to give their business to brands that do not use GenAI in consumer-facing content. A further 68% said they frequently wonder whether the content they encounter is real, and 61% frequently question whether information they use for everyday decisions is reliable.
Emily Weiss, Senior Principal Analyst in the Gartner Marketing practice, frames the implication clearly: "Marketers should treat GenAI as a trust decision as much as a technology decision". Consumer familiarity with AI tools does not automatically translate into comfort with brands deploying them across advertising, messaging and content.
These reports do not contradict each other; they combine to more fully represent what is at stake. While AI has the potential to deliver many benefits to marketing outcomes that does not mean it is a slam dunk. Brands still need to tread carefully, particularly around issues of trust. Gartner recommends therefore making generative AI “optional rather than mandatory” and being open about where it is being used.
Make CX a Priority
Analysts at Gartner put forward three ‘AI Accelerators’ to help escape the competency trap: boost customer confidence, marketing teams’ confidence, and C-Suite confidence. The first of these, “Boost customer confidence in the brand and themselves”, also points to the need for drawing a distinction between the kinds of AI experiences provided: “The CMOs who move ahead use AI to build customer confidence, creating tools and experiences that help customers make better decisions”.
Backing approaches with strong AI governance matters too, given that consumer verification behaviour is rising. Organisations that design human and AI workflows with transparency and customer control at the centre are likely to be better positioned than those treating automation purely as an efficiency lever.
As AI's share of marketing work heads toward 36%, the organisations best placed to realise genuine ROI from that investment will be those that keep the quality of customer interactions in mind, not just the volume.