Somewhere in a boardroom last year, a slide went up. It had a line going down and the line was labelled “headcount”.
The Number Nobody Put On A Slide
Gartner’s 2026 CMO Spend Survey, 401 marketing leaders across North America, the UK and Europe, most of them at organisations north of a billion dollars in revenue found that labour’s share of the total marketing budget rose from 21.9% in 2025 to 24.5% in 2026
That is the same year those organisations put an average of 15.3% of their marketing budgets into AI.
Read those two figures next to each other for a moment. Spending on the technology that was going to reduce the cost of people went up. And the cost of people went up with it. Not despite it. Alongside it.
Meanwhile, martech’s share of the budget fell to a five-year low of 19.4%, down from 26.6% in 2021. The tools got cheaper to rent. The people got more expensive to keep.
What Actually Happened?
AI didn’t fail. It worked exactly as advertised at the task level. It drafts faster. It variants faster. It optimises faster. Anyone who has watched a competent operator run a campaign through a modern stack knows the speed is real.
What it did not do was supply the thing that decides which task was worth doing.
Gartner puts a number on that gap too. Seventy percent of CMOs say their internal marketing processes are not mature enough to effectively implement and scale AI. Only 30% report mature or fully developed AI readiness. And when asked what is actually blocking AI-driven efficiency, the top answer cited by 38% was not cost, not vendor lock-in, not integration. It was a lack of internal AI expertise and talent.
So the budget went where the constraint was. It always does. The constraint turned out to be human.
As Gartner’s Ewan McIntyre put it “AI is not a shortcut around marketing capability.”
Where The Mature Ones Put Their Money
The most useful finding in the survey is the one that reads like a footnote.
Awareness and conversion now account for 62.6% of total media spend, up over 10% since 2024 while spend on loyalty and retention has fallen 29% to under 15%. Budget is flooding toward the top and bottom of the funnel.
But the most AI-mature organisations in the study do the opposite. They allocate a larger share to loyalty and retention, and a smaller share to digital channels.
Think about what that means. The organisations best equipped to let AI optimise everything have chosen to optimise less of it. Not because they distrust the tools, but because they can tell the difference between what is easy to measure and what is worth measuring. Everyone else is being quietly steered by their own dashboards toward whatever the machine can score.
Optimisation is not a strategy. It never was. AI just made it much easier to confuse the two.
Why This Lands Harder On Smaller Firms
Gartner surveyed billion-dollar organisations. If they’re struggling with this, it is worth asking what it looks like for a fifty-person manufacturer or a mid-sized legal practice.
The Business Development Bank of Canada surveyed 1,500 small and mid-sized businesses in the same window and found the shape of it. Ninety-six percent had invested in digital technologies. Only 30% were using generative AI and those that did were 24% more productive than those that didn’t.
Investment was near-universal. Outcomes were not. The gap between the two is not a budget gap. It’s a Digital Maturity gap between owning capability and being able to direct it.
For a smaller firm the math is unforgiving in a specific way. A large organisation can absorb a year of expensive learning inside a rounding error. A firm with one marketing manager and a retainer cannot. When the tools multiply output but nobody has decided what the output is for small teams don’t get efficiency. They get more work, faster, in more directions, with the same number of hours to review it.
The Uncomfortable Conclusion
The promise was that AI would let you do the same work with fewer people.
The data says something narrower and more useful – AI lets you do more work with the same people and the value of those people goes up, because judgment is now the scarce input rather than production capacity.
Which reframes the question every business owner should be asking this quarter, What decisions are we making badly, and would doing them faster make that worse?
Because it will. Speed is a multiplier, and multipliers do not care about the sign of the number they’re applied to.
The firms pulling ahead in this data are not the ones who bought the most. They are the ones who sequenced its capability first, tools second, volume last. That order is not intuitive, and it is not what anyone selling software will tell you. It is simply what the mature 30% did.
The rest are discovering…
Essentiate brings the judgment layer, the part AI does not ship with. We work with small and mid-sized firms as a digital engagement partner, not a production line: sequencing where technology genuinely earns its place, and where a decision made properly the first time is worth more than ten iterations made quickly. If you want to see where your organisation actually sits on the maturity curve before you spend another rupee on tooling, start with our PIE Framework.
Ref,
https://www.gartner.com/en/newsroom/press-releases/2026-06-08-gartner-marketing-survey-finds-awareness-and-conversion-account-for-62-6-of-total-media-spend
https://www.bdc.ca/en/about/mediaroom/news-releases/350b-opportunity-canadas-next-phase-of-growth-to-be-driven-by-ai-and-digital-technologies
