Key takeaway: Marketers are saving 13 hours a week with AI. The teams getting revenue impact are the ones deliberately redirecting those hours to higher-leverage work. Most teams are just doing more execution.
The ActiveCampaign survey conducted in May and June 2025 produced a number that should have changed how every marketing leader thought about their team structure: the average marketer using AI saves 13 hours per week. Daily AI users save 14.8 hours and approximately $5,000 per month per person in time value.
Thirteen hours is not a rounding error. It is 32% of a 40-hour work week, returned to the team. At the team level, for a marketing team of five, that is 65 hours per week. More than one and a half full-time employees, recovered without a hire.
What most teams do with that time is the problem. A March 2025 Harvard Business Review analysis found that the majority of teams reallocate saved AI time to more execution: more content, more campaigns, more tasks from the backlog. The output volume goes up. The strategic quality of the work does not.
Why Saved Time Gets Absorbed by More Execution
This is not a mystery. Execution tasks are visible, urgent, and measurable. If AI frees up two hours, there are always two hours of execution work waiting. The content backlog is never empty. The campaign queue never clears. The reporting requests do not stop coming.
Strategy work, by contrast, is neither urgent nor immediately measurable. Spending two hours on a competitive positioning analysis or a customer interview does not produce an artifact that appears in the sprint board or the weekly report. The value is real but diffuse, showing up months later in better campaign hypotheses and sharper messaging. Organisations that do not explicitly protect time for strategy work will see it crowded out by execution, with or without AI.
The HBR finding suggests AI is making this worse by removing the natural constraint that execution time used to impose. When execution was slow, strategy time was protected by default because there was only so much execution capacity. When AI makes execution fast, the execution queue expands to absorb the freed capacity, and strategy time shrinks rather than grows.
What High-Performing Teams Do Differently
The teams in the minority who are seeing genuine revenue impact from AI time savings share a specific behaviour: they made an explicit decision about where the saved time would go before they started saving it.
This is not a complicated insight, but it requires resisting the default. The default is more execution. The deliberate choice is a different allocation. High-performing teams treat recovered AI time as a budget line, the same way they would treat a new headcount. If you hired a junior marketer, you would think carefully about what you wanted them to work on. The same decision needs to be made for recovered time.
What recovered hours are actually worth investing in
Customer research is the highest-leverage redirect for most marketing teams. Most teams are running on assumptions about their audience that were formed during an initial launch and have never been updated. A customer interview programme that was previously not feasible because the team had no capacity to conduct and synthesise interviews becomes feasible when AI recovers 13 hours per person per week. Customer insight improves everything downstream: messaging, campaign targeting, content strategy, product feedback.
Competitive analysis is the second. Most teams have a quarterly or annual competitive review, which means they are making budget and positioning decisions on information that is months out of date. Weekly competitive monitoring with AI synthesis, a task that takes 30 minutes rather than half a day, keeps the team current and allows for faster strategic adjustments.
Campaign hypothesis development is the third. The difference between a campaign that tests an interesting hypothesis and one that tests the obvious hypothesis is often whether the team had time to think carefully before briefing the creative. Recovered time invested in sharper hypothesis development produces better A/B test insights, which compounds into better campaigns over successive iterations.
A Framework for Deliberate Reallocation
The practical mechanism is straightforward. At the team level, identify the three to five activities that would most improve marketing performance if the team had more time to do them. These are typically things that everyone agrees are important but that keep getting deprioritised because execution is always more urgent.
Then commit, explicitly, to allocating a portion of recovered AI time to those activities. Block it on calendars. Make it a standing agenda item in team check-ins. Measure whether it is actually happening. The point is to make the reallocation intentional rather than letting execution absorb the capacity by default.
The $5,000 per month per person figure from the ActiveCampaign data represents time value, not revenue. Converting time value into revenue requires the deliberate redirect. Teams that execute more efficiently but do not improve the quality of their strategic decisions will see the time savings appear as throughput, not as revenue growth. That is not nothing, but it is a fraction of the potential value.
The Compounding Effect
There is a second-order effect worth naming. Teams that redirect recovered time to customer research and competitive analysis are building better institutional knowledge. That knowledge improves the quality of their AI prompts, their briefs, their campaign hypotheses, and their strategic decisions. Better inputs produce better AI outputs. The quality of execution improves alongside the quality of strategy.
Teams that redirect recovered time to more execution are not building this knowledge base. Their AI use gets more efficient over time, but the quality of the underlying strategic direction does not improve. Over 12 to 24 months, the compounding difference between these two approaches will be significant.
Conclusion
Thirteen hours per week is a meaningful return, and daily AI users are generating close to 15 hours. The ROI multiplier is not in the hours saved. It is in what you do with them. Most teams are absorbing recovered time into more execution because execution is always more urgent than strategy. The teams generating revenue impact from AI are the ones who made an explicit reallocation decision before the time was recovered, protected it from execution pressure, and measured whether it was actually happening. That decision is available to any team. Most just have not made it yet.
