AI has a reputation problem. Not with technologists or early adopters; they’re still bullish. But with the people actually trying to use it every day to do their jobs.
I spend a lot of time in conversations around AI, tracking the media, leading a team of marketers, talking to peers, and working inside an AI company. And what I can tell you is that the mood has shifted. The early enthusiasm is still there, but it’s sitting alongside something else now. A growing frustration. A creeping exhaustion. A vocabulary that didn’t exist two years ago: AI fatigue. AI brain fry. AI FOMO. AI anxiety. AI slop.
These terms aren’t appearing out of nowhere. They’re signals.
There’s truth in the terms
Each term is naming something real that marketing teams are feeling right now. And underneath all of them is the same root cause: AI is adding work before it’s removing it. I’m seeing this in three key ways.
First, there’s a learning curve to using AI. New tools are coming out faster than anyone can keep up with. Six months ago, my team put together a list of tasks we wanted to automate and ranked them by difficulty. When we revisited that list recently, half the things we thought would be the most difficult to automate weren’t anymore. The technology had caught up. But that doesn’t mean we were ready for it.
Our AI Maturity Report found that 65% of marketers say their organization introduces new tools faster than they can learn them. And 69% feel pressure to use AI even when they’re not sure it helps. This pressure isn’t coming from AI mastery. It’s coming from fear of falling behind. That’s AI FOMO.
Then there’s the output gap. AI is genuinely useful, especially when you’re staring at a blank page. But when the output isn’t quite right—when it sounds generic, off-brand, like it could belong to anyone—that’s AI slop. And the review process, the tweaking, the quality control that comes with that slop all add up. Seventy-three percent of marketers say AI creates extra work to review or fix. That cognitive overhead has its own name too: AI brain fry.
Underneath all of it, there’s a subtler dynamic that doesn’t get talked about enough. Productivity gains from AI aren’t translating into less work. Theyre being reinvested into more ambitious work. We’re producing more, which means more data to ingest, more to report, more to make sense of. The ceiling keeps moving. That’s creating AI fatigue.
And the quiet worry that you’re still not doing enough with it? That’s AI anxiety.
We’ve gotten very good at naming the friction. What we’re still working on is fixing it.
AI isn’t failing us. The conditions are.
The fix isn’t straightforward. Most AI tools weren’t built for how marketing teams actually work.
They were bolted onto preexisting workflows as an afterthought. They live in separate tabs, on different surfaces, disconnected from the work itself. Every task requires figuring out which tool to use, switching to it, reexplaining your context, and bringing the output back into wherever the work actually lives.
And training hasn’t kept pace either. The irony is that the most valuable AI learning isn’t coming from formal company onboarding or top-down guidance. It’s coming from peers. I belong to a number of comms communities, and the pattern is the same across all of them: practitioners sharing specific use cases, swapping workflows, showing each other what’s actually working. We’re figuring it out together because nobody handed us a playbook.
That’s because AI is personal. What works for one team won’t work for another. What fits one person’s workflow may add friction to the next person’s. The tools that earn real adoption aren’t the ones that get mandated. They’re the ones that fit so naturally into the work that people want to tell their colleagues about them.
Which points to what AI actually needs to be to solve the productivity question. Not another tab to track down. Not another tool to learn. What you need is AI that works where your team already is, that knows what you’re working on without being re-briefed every time, and that connects across your work instead of fragmenting it further. That’s not a nice-to-have. For most teams right now, it’s the difference between AI that adds to the pile and AI that actually starts reducing it.
Fixing the framing
The crux of AI’s reputation problem is that AI’s promise has not kept pace with its reality. The promise was productivity. The reality, for most teams, has been more tools, more friction, more work to manage. The gap between what AI was supposed to do and what it’s actually doing day-to-day is where all those terms we talked about—the fatigue, the anxiety, the brain fry—live.
But here’s what I’m also seeing: The teams navigating this best aren’t the ones with the most AI tools. They’re the ones who know exactly what AI can and can’t do.
AI can generate. It can automate. It can scale. But it can also overproduce and overcomplicate. That’s when you start spiraling in rewrites, tweaking, and perfecting. AI will keep spitting out new versions and that’s when it becomes counterproductive.
What AI can’t do is build trust. And right now, trust is the most valuable thing a brand can have.
Audiences are becoming more discerning, and they can feel the absence of a real point of view. They notice when content is technically polished but strangely empty. The reporters I respect most right now aren’t pretending AI doesn’t exist. They’re being transparent about how they use it, documenting their process, showing their thinking. That transparency doesn’t undermine their credibility. It builds it.
The same is true for brands. At Superhuman, we counter AI-generated with authenticity. Real voices. Real points of view. People showing up as human. In a sea of sameness, that’s not a soft advantage. It’s a strategic one.
Maybe the most important thing we can do right now is fix how the problem is framed. Not “Is AI making us more productive?” but “Is AI making space for the best of what our people can do?” The companies getting that right are the ones worth watching.
Want to dig into the data? The AI Maturity Report breaks down what marketing professionals are really experiencing with AI. Get the report →
