What kind of AI expert are you?
Written by Jesse Weltevreden
Understanding the 4 layers of the AI expert iceberg
Everywhere you look, someone is calling themselves an “AI expert.”
Some are. Many… aren’t.
So how do we make sense of all the noise?
I like to think of it as an iceberg.
What we see at the surface—on LinkedIn, YouTube, or in trend-driven conference talks—is only a small (and often shallow) part of the full picture. Beneath that surface is where the real depth begins.
Here’s a look at the four levels of today’s AI expert ecosystem, from most visible to most foundational.
1. Above the Surface — Self-Proclaimed Experts
Loud, visible, but often shallow.
These are the AI influencers, prompt gurus, self-branded coaches, and motivational poster-makers.
They’re confident. They post daily. But their understanding is often limited to buzzwords and basic tool usage.
Experts like this often don't take a data-driven or objective approach to evaluating AI tools. Many are shaped by commercial incentives—think affiliate deals, product partnerships, or hype-driven content. It’s more about visibility than verifiability.
They’re also masters of persuasion.
Through viral formats like “Rip tool X”, “You’re falling behind if you’re not using this”, or “This AI will replace your job”, they create FOMO and urgency, tapping into fear, disruption, and the desire to stay ahead. The result? Hype spreads faster than insight.
2. Half Above, Half Below — Practical AI Professionals
The bridge between real work and real tools.
This is where things get interesting. These are domain professionals—marketers, educators, trainers, HR folks—who are actively integrating AI into their workflows.
They’re not building models, but they’re figuring out what actually works in real life.
Even better? Many of them share openly, helping others learn along the way.
Still, this group often evaluates tools based on experience, anecdote, or usability—not necessarily with objective or data-backed comparisons. While their insights are valuable, they can unintentionally reinforce hype rather than challenge it.
3. Below the Surface — Applied AI Professionals
They make AI work in the real world.
These are your data scientists, ML engineers, AI-savvy product managers, and consultants.
They work with real models, code, infrastructure, and business goals. They’re translating complex AI into usable products—but usually doing it quietly, without the hype.
They understand not just how AI looks, but how it performs—and where it breaks.
4. Deep Below the Surface — True AI Experts
They laid the foundation, and continue to shape the future.
This is the bedrock: AI researchers, model architects, open-source contributors, ethicists.
They write the academic papers, build the frameworks, challenge the assumptions, and publish the breakthroughs that the rest of us stand on.
Their work is complex, rigorous, and often underappreciated. But without them, the entire iceberg collapses.
Not an AI Expert? You're Not Alone.
If you don’t see yourself in any of these layers, that’s completely fine.
Most people engaging with AI today aren’t experts—they’re curious observers, learners, and professionals trying to make informed decisions.
If that’s you, here are a few simple tips to help you navigate the noise:
- Be skeptical of confident claims, especially ones that create fear or urgency.
- Look for people who show their work, not just those who sound convincing.
- Seek out data and real-world examples, not just flashy tool demos.
- Don’t confuse popularity with reliability.
- Stay curious—ask questions, try things, and reflect on what works for you.
You don’t need to be an expert to think critically about AI.
You just need to be aware of who you're trusting—and why.
So… What Kind of AI Expert Are You?
You don’t have to be at the bottom of the iceberg to do meaningful work.
But it helps to be honest about where you stand—and to stay curious about what’s deeper.
Me?
I don’t consider myself an AI expert.
I’m a market researcher, trying to make sense of a landscape that’s changing at an incredible pace. I observe, compare, ask questions, and look for patterns—so others don’t have to chase the hype blindly.
That’s exactly why we started RankmyAI.
AI experts in tiers 1 and 2—while often creative and enthusiastic—rarely take a data-driven, objective approach to evaluating AI tools. Group 1, in particular, is often shaped by commercial incentives, affiliate deals, or hype cycles.
At RankmyAI, we help cut through that noise.
We provide independent, evidence-based insights into how AI tools actually perform—across languages, tasks, and use cases.
Because in a world full of claims, someone has to measure what’s real.
