AI Adoption Is Widespread. AI Maturity Is Not.
New research from 500+ enterprise marketing leaders reveals a widening gap between AI tool adoption and operational maturity across the Analyze–Optimize–Act cycle.
Find out where teams are stalling, and what advanced AI users do differently.
Get the Full Report - Free
Join 500+ marketing leaders who have already accessed this research
83%
of marketing leaders say they’re satisfied with their ability to analyze performance
37%
BUT only 37% have a single unified source of truth
78%
say performance data is fragmented across platforms and spreadsheets
8%
Only 8% orchestrate multi-step AI workflows across tools and teams
If most enterprise marketing teams report confidence in their AI tools, but almost none have centralized intelligence or orchestrated execution, then AI satisfaction and AI maturity are two very different things.
This report reveals exactly where the gap is, how it’s widening, and what the top performers are doing differently.
What’s Inside
What You’ll Learn in the Research Report
Analyze
Why Data Fragmentation Is Defeating Your AI Investment
How 73% of teams are wasting time reconciling data — and what unified intelligence actually looks like.
Optimize
The Orchestration Gap: Why AI Insight Rarely Becomes Action
What separates teams who identify opportunities from teams who actually act on them — at scale.
Act
Manual Execution Is Killing Performance — Here’s the Data
72% of teams still say reporting is highly manual. Average turnaround: 5 days. What AI agents change.
Benchmark
The AI Maturity Roadmap: Where Does Your Team Stand?
A practical framework for assessing your team’s current maturity level and identifying the highest-leverage next step.
Who This Is For
Is This Report Right for You?
CMOs & Marketing Leaders
If you’re measuring AI success by tool adoption, not by whether insight is turning into faster, better decisions, this report will change how you think about your stack.
Key question it answers: How do top-performing teams actually operationalize AI across their full marketing cycle?
Marketing Operations & Analytics Leaders
If your team still runs on manual exports, spreadsheet reconciliation, and human handoffs between tools, AI maturity is incomplete.
Key question it answers: What does a centralized AI intelligence layer look like in practice, and what does it take to build one?
Research Methodology
Who We Asked. What We Found.
500+
Marketing & Advertising Leaders surveyed globally
$26.2M
Average annual paid media spend among respondents
$10M–$100M+
Respondents span brands, agencies and media companies investing per year in paid media
5+
Covers enterprise teams across paid search, paid social, programmatic, and direct digital
“The bottleneck is no longer access to data. It is the ability to act on it quickly, consistently, and across systems.”
72% of marketing teams say their reporting process is highly manual
— The Next Phase of Marketing Intelligence: 2026 Research Report
“88% of respondents were satisfied with the impact AI has had on marketing performance outcomes, yet nearly three-quarters use isolated AI point tools or rely on AI capabilities embedded in individual marketing platforms.”
Only 8% orchestrate multi-step AI workflows across tools and teams
— The Next Phase of Marketing Intelligence: 2026 Research Report
The AI-Powered Marketing Intelligence Platform
UserEvidence
Verified Customer Research
Co-produced with UserEvidence for independent research validation
Ready to Move Beyond AI Experimentation?
NinjaCat brings centralized intelligence and AI Agent-powered execution to your marketing stack — closing the gap between insight and action.
Request a Demo →