The dataset that didn't exist — until now
Map your daily tasks. See which ones are in the automation zone — and which ones are protected by the informal knowledge, relationships, and human judgment that AI agents can't access.
The Framework
Is the task digital-in, digital-out? This is the only layer most analysts look at. It defines the theoretical automation zone.
Does the task actually depend on hallway conversations, gut feelings, 15 years of pattern recognition? A task can look digital on paper but depend entirely on informal knowledge. AI has zero access to this layer.
Does performing this task also build trust, maintain relationships, or signal presence? The lunch with a client isn't just information transfer — it's the relationship itself. Remove the human and you lose the value.
How It Works
Enter your job title. We look up typical tasks from our database of real job profiles. If your role is new to us, AI fills in the gaps. You confirm, edit, or add what's missing.
As you interact, a visual map of your job assembles in real time. Each task is classified across all three layers — you see the picture sharpen as you go.
Your personal automation exposure profile. Which tasks are most exposed. Where your strongest human advantage is. How you compare to peers in your profession.
"Apparently only 23% of my job is actually automatable." A shareable card designed for the conversation everyone's already having.
How our data evolves
We launched with AI-generated task profiles as a starting point — a way to cover thousands of job titles before real users arrived. Every time someone completes an assessment, that real-world input is added to the database. Over time, profession by profession, AI estimates are replaced by actual human responses. The more people use it, the more grounded the data becomes. Learn more →
Privacy
We don't collect personal data because we don't need it. The system is designed so that identifying you is structurally impossible, not just prohibited.
Full details: scoring model, synthetic data, and data use plans →
Why This Matters
Every automation forecast you've read is top-down — economists guessing from the outside. This is the first tool collecting bottom-up, task-level, worker-reported automation data.
As the dataset grows, it becomes a resource for AI companies understanding their real market, policymakers designing evidence-based workforce strategy, and universities building curricula for the skills that actually matter.
You get your personal profile. The world gets better data.
Explore
The dataset is already large enough to surface patterns. What does genuine automation exposure look like across junior roles versus executives? Which professions are protected by physical presence alone? Where is the human advantage actually strongest?
Three minutes. No login. No personal data.
Start your assessment →This project runs on private savings. If you find it useful, a small contribution helps keep it going.