Marketing budgets are flat at 7.7% of revenue, but AI-mature companies are spending 11%

Marketing budgets have essentially flatlined as a share of company revenue, but a clear winner class is separating from the pack. Organizations that Gartner calls "AI strategists", those with fully optimized internal AI processes, are allocating an average of 11% of total revenue to marketing, compared with 7.8% across all respondents in the firm's 2026 CMO Spend Survey, which polled 401 senior marketing leaders. That 3.2-percentage-point gap may look small, but on a $500 million revenue base it is the difference between a $39 million and a $55 million annual budget.

The broader headline from Gartner, reported by Chief Marketer, is that overall marketing budgets are holding near 7.7% of revenue, essentially unchanged from the prior year. A parallel data set from the CMO Survey, run jointly by Deloitte, Duke University, and the American Marketing Association, puts the figure higher at 9.4% of revenue, up from 7.7% in 2024. As Boomcycle notes in its July 2026 analysis of the two surveys, the divergence reflects methodology more than market reality: Gartner draws heavily from companies with more than $1 billion in revenue, while the CMO Survey includes a broader mix of company sizes, and smaller organizations consistently spend a higher share of revenue on marketing.

The AI maturity divide is reshaping budget baselines

Gartner segments respondents by how far along they are in deploying AI within their marketing organizations. Only 9% of CMOs rated their processes as fully optimized for AI; another 21% considered themselves mature. Together, Gartner calls this group AI strategists. The remaining 70% described their organizations as developing, early-stage, or not yet started.

The budget gap between those two camps is striking. AI strategists allocate a mean 21.3% of their marketing budgets to AI initiatives specifically, against a 15.3% mean across all respondents, according to Chief Marketer's reporting on the survey. They also direct a mean 34.2% of their budgets toward innovation-oriented spending, compared with 27.2% for all respondents. The implication for procurement and operations leaders is concrete: companies already ahead on AI are reinvesting the efficiency gains into more marketing capacity, not pocketing them.

Labor costs are moving with the AI trend in a somewhat counterintuitive direction. The mean share of marketing budgets going to labor rose from 21.9% to 24.5% year over year, according to Gartner, as organizations scramble to hire or develop AI-capable talent. A lack of internal AI skills was the single most frequently cited barrier to marketing efficiency, named as the top obstacle by 19% of CMOs and ranked in the top three by 38%, per Chief Marketer. Lack of integrated marketing data came second, cited as the primary barrier by 13%.

Martech spend hits a five-year low despite broader investment intent

One of the more counterintuitive findings in this year's Gartner data: martech's share of the overall marketing budget has dropped to 19.4%, its lowest point in five years and down sharply from 26.6% in 2021, even as 62% of CMOs say they plan to increase martech investment. Chief Marketer reports that a significant driver is the shift toward consumption-based, or usage-based, pricing models. In the past year, 56% of respondents increased the share of their martech budget allocated to this pricing model, while only 9% reduced it.

The appeal of consumption-based martech is straightforward: organizations stop paying for licenses they rarely use. But Gartner cautions that the model carries its own financial risks. Unexpected usage spikes, unforeseen demand trends, and inadequate internal oversight can push actual costs well above initial projections. Half of all organizations that have adopted consumption-based solutions are in continuous contract renegotiation to avoid overages, according to Chief Marketer's account of the findings. Gartner recommends building real-time oversight controls into existing processes; 41% of organizations say they have already done so or are in the process.

A secondary factor suppressing the martech percentage: many organizations have already made their headline AI tool purchases and are now in an optimization phase rather than an acquisition one. That maturation dynamic helps explain why the dollar commitment to AI within marketing is rising even as martech's overall budget share falls.

Industry and company size benchmarks still vary enormously

Both the Gartner and CMO Survey averages obscure variation that is directly relevant to anyone setting a budget target. According to Boomcycle's synthesis of available research, consumer packaged goods companies spend roughly 18% of revenue on marketing, while energy companies spend around 3%. Technology and software companies land between 11% and 15%. B2C companies on average spend 13.9% of revenues on marketing; B2B companies average 9.3%. Within B2B, Forrester has pegged the benchmark at 8% of annual revenue for U.S. companies, with European counterparts reporting 9%.

Company size complicates the picture further. The CMO Survey data shows a negative correlation between total revenues and marketing spend as a percentage of revenue: larger companies consistently spend a lower share. The U.S. Small Business Administration recommends that businesses under $5 million in revenue allocate 7-8% to marketing, assuming gross margins of 10-12%, per Boomcycle's analysis. A company running on thinner margins cannot carry that level of investment without eroding operating income.

Gartner's own survey underlines how averages mislead even at the enterprise level: while the mean marketing budget sits near 7.7% of revenue, half of the CMOs surveyed are working with budgets of 6% or less, meaning the distribution is skewed by a relatively small group of heavy spenders. For operations and finance leaders reviewing marketing budget proposals this planning cycle, the more actionable question is not what the average company spends, but what the top-performing companies in their specific vertical and revenue tier are allocating, and what AI maturity level corresponds to that spending.