AI fails to deliver business value in marketing, McKinsey finds
A new McKinsey study reveals a vast gap between AI adoption and actual business value in marketing, warning that a narrow focus on cost-cutting is fuelling executive anxiety and stalling competitive advantage.
The vast majority of companies are using artificial intelligence in their marketing operations, but fewer than one in ten are extracting real business value from it, according to new research from McKinsey.
The consulting firm drew on surveys of more than 1,000 marketers globally alongside interviews with senior leaders for a report released at the Cannes Lions festival. It found that while 88% of companies now use AI and over 60% of marketers use it multiple times a week, less than 10% report meaningful value capture. This disconnect presents a significant challenge for corporate strategy.
Rather than boosting confidence, this widespread adoption is fuelling anxiety. 86% of marketers expressed excitement about AI, yet 57% admitted to feeling highly anxious. Surprisingly, this fear is most acute at the top. 96% of chief marketing officers were excited, but 71% were anxious, with 80% actively worried about losing their jobs. Kelsey Robinson, a senior partner at McKinsey, noted that this unease cut uniformly across all roles, from copywriters to creative strategists.
For businesses, this anxiety signals a flawed approach to deployment. Robinson argues that too many leaders frame AI primarily as an efficiency tool. When the narrative centres on cost-cutting and productivity, it naturally triggers workforce fears about redundancy and fails to inspire the organisational buy-in needed to drive growth.
To translate usage into revenue, companies must shift their focus to growth aspirations like advanced personalisation, which can deliver tangible revenue uplift. Furthermore, McKinsey advises against waiting for perfect data infrastructure. Leading firms are adopting a two-speed strategy: capturing immediate value in areas like customer support while simultaneously upgrading their data foundations.
The fintech company Chime exemplifies this phased approach. Its marketing transformation began by normalising basic AI tools before moving to transform specific functions. By applying AI to media optimisation, Chime reduced a ten-week campaign cycle to just four weeks and increased return on ad spend by almost 20%.
Only an estimated 5% to 10% of companies are currently successfully re-architecting their marketing functions around AI. For the rest, the competitive stakes are clear. As Robinson summed up the threat: "It might not be AI that takes your job, but it might be someone who’s just better at using AI."
