About

The idea

AI is changing tech roles faster than any single source can track. Research papers land daily on arXiv. Labour statistics update quarterly. Hiring patterns shift month to month. No one reads all of it, and the result is that most professionals are flying blind about how their specific role is actually evolving.

Revalue was built to close that gap. It continuously pulls from academic research, government labour data, open-source activity, and industry publications, then synthesises everything into role-level signals: how much of the work AI can already do, whether hiring demand is growing or contracting, and how much leverage the role gives you over AI tools.

What it is not

Revalue is not a career coach, a recruiter, or an oracle. The scores are statistical aggregations: useful context, not verdicts. A high AI coverage number means a meaningful share of the role's task surface can be handled by current AI tools; it says nothing about whether you personally will be replaced, or when.

The goal is sharper situational awareness, not panic. Understanding the landscape clearly is the first step to navigating it well.

How the data works

• ›Role-level granularity: Each role is assessed on its own task profile. A Staff Engineer and a Data Analyst face different AI pressures; the scores reflect that.
• ›Multiple independent signals: No single source drives the conclusions. Research, labour statistics, hiring trends, and open-source patterns each contribute a piece.
• ›Automatic updates: The pipeline runs continuously. When new evidence comes in, the scores update to reflect it.
• ›Transparent methodology: The How it works page explains exactly what each number means and how it is calculated.

Sources