Jacks, Kings, and Jokers…
Luxury Presence CEO Malte Kramer argues that AI is splitting the workforce into three groups, and only two of them are positioned to thrive. In a column for Fast Company’s Executive Board, he put it simply: “Value concentrates at the extremes.”
Here’s how his framework could map onto a dealership.
The Three Types of Workers in the AI Era
Type | Kramer’s definition | What it could look like in a dealership |
|---|---|---|
Extreme specialist | Knows a field so deeply that AI can’t replicate the work, and can direct AI because they know what good output looks like | A master technician diagnosing complex problems, or an F&I director who knows compliance inside and out |
Extreme generalist | A high-agency person who uses AI as a multiplier across several functions | A marketing manager running email, paid ads, and SEO, work that once took three people |
The middle | Someone who has done one job competently for years without going deeper or broader | Anyone whose role hasn’t changed in years, and who hasn’t started using AI to expand it |
The dealership examples are our illustrations, not Kramer’s.
Why Specialists Get the Most Out of AI
It sounds backward, but deep expertise makes AI more useful, not less. AI can produce work quickly, but someone has to know whether that work is right.
Specialists can spot mistakes in AI output that others would miss.
They write better instructions, because they know exactly what a good result looks like.
They can evaluate tools before the whole store adopts them.
Generalists win differently. AI removes the bandwidth limit that used to keep one person from covering several jobs well.
The Middle Has Two Ways Out
Kramer is clear that middle-of-the-road skills aren’t worthless. But their value is falling, and the path forward is to go deeper or go broader. When he hires, he looks for curiosity, a bias toward action, fast learning, and a habit of pushing past the edges of what someone already knows.
For dealers, that last trait may be the most useful one to develop across the whole team.
More on this with Paul and Michael on Automotive State of the Union
Try This Prompt
Use this to help an employee map their own next step. It works best when the employee runs it themselves.
I work at a car dealership as a [your role]. Here’s what I do on a typical day: [describe your main tasks]. Based on this, suggest two ways I could go deeper in my specialty and two ways I could use AI to take on work from a related role. For each, give me one small thing I could try this week.
AI won’t replace your best people. But it will widen the gap between people who keep learning and people who don’t, and dealers can decide which way their team grows.
Something to consider: Which person on your team is already experimenting with AI, and what would happen if you gave them room to teach everyone else?
