The news: AI is deeply ingrained in marketers’ content creation, campaign planning, and optimization workflows. However, bottlenecks are emerging as some teams remain doubtful about whether AI is making work meaningfully easier.

• 76% of global marketing leaders spend at least three hours per week editing, fact-checking, or correcting AI outputs, per an Optimizely survey.
• Just 4% say AI saves them time at every stage. They cite hallucinations and fact-checking (48%), copy and pasting between disconnected tools (40%), and compliance checking (37%) as the biggest time killers.
• Two-thirds (65%) would like to pause or adjust their company’s AI implementation plans if they had the chance to improve guardrails and governance or rethink operating models.

Optimizely’s data suggests that, instead of eliminating work and improving efficiencies, AI is moving the work to different tasks. Hallucinations, fragmented tool workflows, and reviews are eroding the time savings AI is supposed to deliver.

What it means: There’s a disconnect between AI’s potential and marketers’ day-to-day reality, with many teams still lacking the processes, tool integrations, and internal systems needed to turn experimentation into measurable business outcomes.

In other words, AI adoption is outpacing operational maturity. This is evident by the fact that one-quarter of marketing leaders frequently or always publish AI content that they know isn’t totally on brand when they’re under deadline pressure, raising brand risks when speed takes precedence over quality.

Recommendations for marketers: Governance, integrations, and workflow design will be deciding factors in whether AI reduces work or just changes how it happens. As marketers evaluate how AI can increase efficiency, they need to determine what improved productivity actually looks like and what the future of daily tasks will be.

To maximize AI’s benefits, teams should:

• Tailor AI tool selection to exact tasks, such as using coding agents for web development rather than generic chatbots.
• Limit AI use to back-end tasks rather than customer-facing applications, which could include leaving more crucial tasks to humans to cut down risks to brand image if AI reviews are rushed.

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