AI was supposed to shrink marketing teams. Instead, the biggest survey of marketing budgets found companies spending a bigger share on people, not a smaller one. Here's why, and what it means for who you hire.
Gartner's 2026 CMO Spend Survey found that while CMOs put 15.3% of budgets into AI, labour's share of marketing budgets rose from 21.9% to 24.5%. 70% say their processes aren't mature enough to scale AI, and lack of AI talent is the top barrier. AI's value depends on people, skills and execution. The question for founders isn't AI or people, but whose people: keep the capability, prompts and workflows inside your business.
- Labour's share of marketing budgets rose from 21.9% in 2025 to 24.5% in 2026, even as AI spending grew (Gartner).
- The top barrier to AI efficiency is a lack of internal AI expertise and talent, cited by 38%.
- McKinsey found the biggest barrier to scaling AI is leadership, not employees; only 1% of leaders call their companies mature.
- AI high performers redesign workflows and have senior leaders who own AI.
- Build capability in-house: hire for judgment, document workflows, train continuously and keep the know-how in your accounts.
What did Gartner find?
Gartner's 2026 CMO Spend Survey of 401 marketing leaders found budgets effectively flat, while CMOs put an average of 15.3% of marketing budgets into AI initiatives. Only 30% said they're ready to scale AI (Gartner, May 2026).
A follow-up release from the same survey added a twist. Despite the assumption that AI would reduce people costs, labour's share of marketing budgets rose from 21.9% in 2025 to 24.5% in 2026. Gartner's reading: AI value depends on people, skills and execution, not just technology (Gartner, June 2026).
Labour's share of total marketing budgets
The barriers tell the same story. 70% of CMOs said their internal processes aren't mature enough to implement and scale AI, and the single biggest barrier to AI-driven efficiency, cited by 38%, was a lack of internal AI expertise and talent. Gartner's Ewan McIntyre put it bluntly: "AI is not a shortcut around marketing capability." AI changes the kind of capability organisations need, he said, "but it does not eliminate the need for capability."
The wider evidence points the same way
McKinsey's research on AI at work, based on 3,613 employees and 238 C-level executives surveyed in late 2024, found nearly all companies are investing in AI but only 1% of leaders describe their companies as mature. Its conclusion: the biggest barrier to scaling is not employees, who are ready, but leaders who aren't steering fast enough. Employees' top request was formal training, which 48% said would increase how much they use AI (McKinsey, Jan 2025).
McKinsey's 2025 State of AI survey found the small group of "AI high performers" were nearly three times as likely to have fundamentally redesigned workflows, three times as likely to have senior leaders who own AI initiatives, and more likely to have defined how people validate AI outputs (McKinsey, 2025). In other words, the winners invested in how people work, not just in tools.
Why aren't tools replacing teams?
- Tools need direction. Someone has to decide what to make, for whom and why.
- Outputs need judgment. AI drafts quickly; people decide what's good, accurate, on-brand and allowed.
- Context lives in people. Your customers, your history, your market: that knowledge sits with the people who've worked on your business.
- Workflows need redesigning. Getting value from AI means changing how work is done, which takes people who understand the work.
- Accountability can't be automated. When results dip, someone has to own the fix.
The real question: whose people?
For founders, the question isn't "AI or people?" It's "whose people?" If the people who understand your business and run your AI tools work for an agency, the capability isn't yours. When the contract ends, the knowledge, the prompts, the automations and the workflows leave together.
It's the same dependency problem we wrote about in why 39% of CMOs are cutting agency budgets, with an AI layer on top. And it's why we don't think the right response to AI is a smaller team. It's a more capable one, inside your business.
What capable teams look like now
| Old marketing team | AI-era marketing team |
|---|---|
| One specialist per channel | Fewer, broader people who can direct AI across channels |
| Time spent producing | Time spent deciding, checking and improving |
| Know-how in people's heads | Know-how in documented workflows and prompts |
| Annual training, if any | Continuous learning as tools change |
| Reports compiled by hand | Automated reporting, with people interpreting it |
How to build the right capability
1. Hire for judgment and learning
Curious generalists who learn tools quickly, and who can tell good output from plausible output, are worth more than a specialist for every platform. Our guide to your first in-house hire covers what to look for.
2. Give AI clear jobs inside documented workflows
Write down how each workflow runs today, then decide which steps AI does, which a person does, and who checks what. See why only 30% of teams can scale AI.
3. Train continuously
Tools change every quarter. Build training into the team's month, not just its onboarding. Keeping talent energised is the top concern for companies running in-house teams, cited by 63% in ANA research (ANA, 2019).
4. Make a leader own it
McKinsey's data is clear that leadership ownership separates high performers. In a smaller business, that's often the founder or a fractional marketing leader.
5. Keep the know-how in-house
Prompts, automations, dashboards and playbooks should live in your accounts and your documents, not a vendor's.
A real estate developer replaces two content writers with an AI tool to save costs. Six months later, there's more content than ever, but enquiries are flat: posts are generic, project details are sometimes wrong, and nobody notices when RERA details are missing.
The fix is one experienced content lead who uses AI for first drafts, checks every claim, knows the projects inside out and owns the content calendar. Fewer people than before, but more capability, and the output finally sells.
For the big-brand picture, read why 82% of large advertisers now run in-house teams, and on what AI can't do, 1 in 5 CMOs say GenAI cut their agency reliance.
AI is the tool. Your people are the capability. Own the capability.
How Ad Asthra builds AI-ready teams
We build capable marketing teams inside your business, then make sure they keep learning.
Frequently asked questions
Is AI reducing marketing team sizes?
Not on average. Gartner found labour's share of marketing budgets rose from 21.9% in 2025 to 24.5% in 2026, even as CMOs put 15.3% of budgets into AI.
Why do marketing teams still need people if AI can create content?
AI drafts quickly, but people decide what to make, check accuracy and compliance, bring context about customers and history, redesign workflows and take responsibility for results.
What is the biggest barrier to using AI in marketing?
Gartner found the top barrier to AI-driven efficiency is a lack of internal AI expertise and talent, cited by 38% of CMOs, and 70% say processes aren't mature enough to scale AI.
What do companies that succeed with AI do differently?
McKinsey found AI high performers are nearly three times as likely to have redesigned workflows and three times as likely to have senior leaders who own AI initiatives.
What skills should a modern marketing team have?
Judgment about quality and accuracy, the ability to learn tools quickly, comfort working with data, and an understanding of your customers and business. Broader people who can direct AI across channels are increasingly valuable.
Should my agency run our AI tools?
Be careful. If the prompts, automations and data live in an agency's accounts, the capability leaves when they do. Keep AI workflows in your own accounts and documents.
How does Ad Asthra help build AI-ready marketing teams?
Through BOT we hire and train your team on modern tools during a 90-day pilot and hand it over; through BOM we keep upskilling the team; and our Enablement Programs train leaders to direct it.
Sources
- Gartner 2026 CMO Spend Survey Finds CMOs Allocate 15.3% of Marketing Budgets to AI, But Only 30% Are Ready to Scale AI Capabilities, Gartner, 11 May 2026
- Gartner Marketing Survey Finds Awareness and Conversion Account for 62.6% of Total Media Spend, Gartner, 8 June 2026
- Superagency in the workplace: Empowering people to unlock AI's full potential at work, McKinsey & Company, 28 January 2025
- The state of AI in 2025: Agents, innovation, and transformation, McKinsey & Company, 2025
- New Study Reveals Concerns For In-House Agency Management, Association of National Advertisers (ANA), 2019
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