AI, Robotics and the Reality of Job Risk
AI & robotics displacement risk
Adjusted risk score by role and industry — sorted high to low within each row
There is no shortage of charts showing which jobs are “at risk” from AI. Most of them miss the point. They focus on what technology can do, not what organisations will actually implement. The reality is more nuanced. There are two distinct forces at play:
AI replaces thinking
Robotics replaces doing
These operate independently. A role may be highly exposed to one and not the other. But even that doesn’t determine the outcome. A third factor matters just as much:
Economics
Just because something can be automated does not mean it will be. Cost, complexity, trust, and real-world constraints all play a role in whether a job is actually reduced or replaced.
How to Read This Page
The table below is designed to give a more practical view of job risk by combining three elements:
AI Exposure – how much of the role involves language, analysis, or structured digital work
Robotics Exposure – how much of the role involves physical, repeatable tasks
Role Compression Constraint – how difficult it is to reduce or replace the role in practice
From this, we calculate:
Combined Risk – the higher of AI or Robotics exposure
Adjusted Risk – Combined Risk adjusted for real-world constraints
This approach separates:
theoretical capability
from practical likelihood
What You’ll Notice
A few patterns stand out quickly:
Some roles are highly exposed and easy to replace
Some are highly exposed but difficult to automate in practice
Some are relatively protected, often for reasons that have nothing to do with complexity
You’ll also see a consistent split within professions:
Junior, execution-heavy roles are under more pressure
Senior, judgment-based roles tend to become more valuable
The Key Takeaway
This is not about industries. It is about the type of work being done within them.
Some roles are exposed.
Some are affordable to automate.
Very few are both.