The State of AI in Marketing in 2026

In partnership with

EDITOR'S NOTE

Hey there 👋

Our friends from Jasper AI surveyed 1,400 marketers about their current use of AI, and the findings are... interesting. 

Turns out that there's a massive gap between what leadership thinks is happening and what's actually happening on the ground. There's confusion about ROI, and there's a new blocker that nobody saw coming.

Let's get into it. 👨‍💻

TL;DR 📋

• AI adoption among marketers hit 91%. That's up from 63% last year. We're past the "should we?" phase and firmly in the "how do we?" phase.

• The problem isn't budget or tools anymore; it's governance. Legal, compliance, and brand safety concerns have exploded 3.4x in the last year.

• Your CMO and your content team may be living in different realities. Leadership is bullish on AI, but the people actually using it aren’t. Only 12% of individual contributors feel the same way as their CMOs.

• Proving ROI has gotten harder, but the payoff has gotten bigger. Only 41% of marketers can prove AI ROI (down from 49% last year), but those who can are seeing returns of 2x or more.

NEWS YOU CAN USE 📰

AI in Marketing Adoption Went Mainstream. Jasper AI's new "State of AI in Marketing 2026" report surveyed 1,400 marketers and found that 91% now use AI, up from 63% a year ago. We've officially moved past the adoption question. Now, it's about execution at scale. [Source: Jasper AI]

The 5 Existential Barriers to AGI: Why scaling isn't working anymore. We have hit a ceiling. The industry assumption was that if we just kept making models bigger, they would eventually solve everything. However, verified research from Anthropic, Apple, and Nature confirms that "brute-force" scaling has reached diminishing returns.[Source: AI Weekly]

AI's Biggest Risk Is the Story We're Not Being Told. The AI boom needs a truth audit about the real risks. Like the surrealist work that emerged after World War I, AI is revolutionary, provocative, and disruptive. The conversation around AI is happening, whether we like it or not, and it's happening fast. [Source: CNET]

WELCOME TO THE OPERATIONAL ERA 🤖

Let's be honest: last year was about figuring out what AI could do, and this year is about building a system where it actually does it.

There's a big difference between using AI to write a blog post and building an AI-powered content engine that feeds every channel, maintains brand consistency, and learns from what works. The first is a tool, while the second is infrastructure.

The New Priority: Scale That Doesn't Break Things

Last year, marketers wanted AI to make them faster; this year, they want it to make them bigger. The top priority has shifted to scaling high-quality content, and demand for this has more than doubled.

While scaling content is easy, scaling content that's on-brand, factually accurate, and doesn't accidentally offend anyone is hard, and that's where the real challenge lives.

The Governance Gauntlet

When AI moves from a personal assistant to a core business process, the stakes change.

One off-brand sentence in a blog post is a small mistake; one off-brand sentence generated across 1,000 articles is a systemic crisis. One factual error in a social post is embarrassing, but one factual error in 50 social posts is a PR problem.

This is why your legal and brand teams are suddenly very interested in your AI workflows. They're not trying to slow you down; they're trying to make sure the company doesn't end up in the news for the wrong reasons.

The report shows that governance concerns have increased 3.4x over the past year. It's now the single biggest blocker to scaling AI, and honestly, that's probably a good sign. It means organizations are taking this seriously.

The CMO-IC Divide: A Problem Nobody's Talking About

Here's the most important finding in the entire report, and it's also the most uncomfortable one.

CMOs are optimistic; they report high levels of AI maturity, job satisfaction, and confidence in proving ROI, and they're excited about the possibilities.

However, individual contributors, the people actually using AI day to day, are stressed. 

Only 12% of them report the same positive experience as their CMOs. They're wrestling with clunky workflows, unclear guidelines, and the pressure to deliver results with tools they're still learning.

This gap is a problem because when leadership thinks the strategy is working, but the team on the ground is burning out, something's going to break, and it's usually the strategy.

If you're a leader, you need to close this gap. Get in the trenches, understand the real friction your team is facing, and ask them what's actually hard, not what you think should be hard.

The ROI Paradox

Here's a weird one: the percentage of marketers who can confidently prove AI ROI has actually gone down from 49% to 41%.

But this isn't because AI is less valuable; it's because the definition of "value" has expanded.

It's no longer just about efficiency and cost savings. Now it's about revenue growth, campaign performance, and brand governance, and these are harder to measure, but they're what actually matters.

The good news is that for the 41% who can prove it, the results are massive: most report 2x or more returns on their AI investments. The lesson is simple: if you're not measuring it, you're probably undervaluing it.

A PRACTICAL STEP-BY-STEP GUIDE: FIGURING OUT WHERE YOU REALLY ARE 🛠️

You move from the experimental phase to the operational one by being honest about where you are right now.

Here's a simple maturity assessment based on the findings in the Jasper report, and it's designed to be brutally honest.

Step 1: Where Does AI Actually Live in Your Organization?

• At Level 1 (Experimental) AI is used by individuals for ad-hoc tasks, there are no official tools or processes, and everyone's doing their own thing.

• At Level 2 (Sanctioned) You have a few officially approved AI tools; they're used within specific teams, but not across the whole department. There's some structure, but it's still pretty loose.

• At Level 3 (Operational) AI is a formal part of your marketing infrastructure; you have governed workflows, clear ownership, and it's integrated into your core platforms, your CMS, your CRM, your analytics tools. It's not a bolt-on anymore; it's part of how you work.

Step 2: How Do You Actually Measure Success?

• At Level 1 (Activity) You measure success by outputs. "We created 50 blog posts with AI this month." It's about volume.

• At Level 2 (Efficiency) You measure success by time and cost savings. "AI helped us reduce content production time by 30%." It's about productivity.

• At Level 3 (Outcomes) You measure success by business results. "The content created by our AI pipeline generated a 15% increase in inbound leads." It's about impact.

Step 3: Who Actually Owns This?

• At Level 1 (No One) It's a free-for-all, everyone does their own thing, and there's no coordination.

• At Level 2 (A Few Champions) A couple of passionate people are driving adoption, but there's no formal ownership. When they leave, the momentum dies.

• At Level 3 (Clear Ownership) You have a dedicated person or team responsible for AI strategy, governance, and tool selection. One in three marketers now has this in their job description. It's a real role.

Your Score

If you're mostly at Level 1, you're in the experimental phase (time to level up!). If you're at Level 2, you're transitioning (good job!). If you're at Level 3, you're in the operational era (noice!).

The goal is to get to Level 3 across the board.

But most organizations are a mix. You might be Level 3 on content creation but Level 1 on analytics, and that's normal. The key is knowing where you are, and then being intentional about where you want to go.

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THIS WEEK'S PROMPT 🧠

Use this with your preferred LLM to create a realistic plan for advancing your team's AI maturity.

The Scenario: You just read the 2026 State of AI in Marketing report. You realized your team is stuck in the experimental phase (Level 1 or 2) while the industry is moving to operational (Level 3). You need to present a clear, actionable plan to your CMO that doesn't require a massive budget or a complete overhaul.

The Prompt:

"You are an AI Strategy Consultant for a marketing team. I need to create a presentation for my CMO that outlines a realistic 12-month plan to advance our marketing team's AI maturity from Level 1 (Experimental) to Level 3 (Operational). Our goal is to build a governed, scalable, and ROI-driven AI program, but we need to do it without a massive budget increase or a complete reorganization."

Current Situation:

• Our Current AI Maturity: [Describe your team's current level. For example: "We are at Level 1. AI is used ad hoc by a few team members with no official tools or governance."]

• Our Biggest Pain Point: [What's the main problem you're trying to solve? For example: "We can't produce enough high-quality content to keep up with our marketing calendar."]

• Our Primary Business Goal for Next Year: [What is the company's main objective? For example: "Increase marketing-sourced revenue by 25%."]

Questions:

1. The Vision: What is the one-sentence vision for our AI program? (Not a mission statement. Just one sentence that everyone can remember.)

2. The Roadmap (Quarters 1-4): What are the key milestones for each quarter? (Be specific. "Q1: Establish governance and select a primary AI platform" is better than "Q1: Get started with AI.")

3. Governance First: What are the three most important governance policies we need to establish in Q1? (Think: brand voice guidelines, human review processes, approved tools.)

4. Measuring What Matters: What are the top 3 outcome-based metrics we should track to prove ROI? (Not activity metrics like "posts created." Real business metrics.)

5. Closing the CMO-IC Divide: What is one concrete action we can take immediately to better understand the challenges our team is facing with AI on the ground?

For each question, give me practical and realistic suggestions that I can actually put on a slide and present with confidence.

TOOLS WE USE ⚒️

These are the most popular AI tools we use at Rise Up Media. If you're not using them already, they're worth a look.

• Claude Cowork: Claude Code but for non-devs (like us!)

• Manus AI: General-purpose AI agent we love (and use to create this newsletter)

• n8n: Open-source automation (if you like that sort of thing)

• Relevance AI: No-code create-your-own AI agents platform

• OpusClip: Auto-clips long videos into shorts (and is really good at it)

Full disclosure: some links above are affiliate links. If you sign up, we’ll earn a small commission at no extra cost to you.

HAVING FUN WITH AI 😊

WRAPPING UP 🌯

The shift to the operational era of AI is one of the significant changes our industry is facing in a new way of working.

The teams need to build AI systems around their work, with clear governance, dedicated ownership, and a relentless focus on measurable business outcomes.

The toying around phase is over. It's time to get serious.

Until next time, keep exploring the horizon. 🌅

Alex Lielacher

P.S. If you want your brand to gain more search visibility in Google AI Mode, ChatGPT, and Perplexity, reach out to my agency, Rise Up Media. We can help you with that!