About This Site
What aidisruption.fyi is, how it works, what its data can and cannot tell you, and who builds and maintains it.
What this is
aidisruption.fyi tracks public labor-market data and published AI-exposure research to provide a real-time, evidence-based view of how AI is affecting the US workforce. I have taken pains to avoid commentary, bias or prediction. Instead, the goal is an accurate and useful monitoring tool, built to show where and how quickly labor-market patterns are changing, which published research suggests those changes may be AI-related, and which careers and metropolitan areas are being most impacted.
Many different sites and better-funded research exist, much of it confusing and contradictory (case in point). Better minds are on this problem, but a meta-analysis that draws on the best practices for measuring economic impact and tracks them over time seemed more useful to the general population and to policy makers than point-in-time snapshots using the same methodology.
To accomplish this, the site aggregates a range of public data sources into three composite indices: labor-market stress, structural AI exposure, and community adaptive capacity. There is also a research library that uses a local AI tuned to detect sentiment to read the latest released AI papers and determine whether a paper paints a rosy, neutral or negative picture of AI's impact on the United States' economy.
What the data can and cannot tell you
One caveat is worth stating plainly: nothing on this site establishes causation. No single layoff, hiring change, or shift in unemployment can be attributed to AI alone; the economy has too many simultaneous drivers for that kind of clean attribution.
What the site's indices can show is that certain patterns are consistent with AI-driven displacement — not proof of it. That distinction is treated carefully throughout the methodology and in how the scores themselves are presented. See how scores are computed and the glossary.
Data provenance commitments
Who runs this
I am Dan Rohan, and I built and maintain this site independently. I do it on my own time and the work here is completely unaffiliated with my employer, IBM.
I spent the first half of my career as a network and systems engineer, then transitioned into product management about a decade ago, working on infrastructure and security tools. I hold a Master's degree in Public Policy from Carnegie Mellon's Heinz College. Professionally, I lead a product team building secure access tools for both human users and AI agents. My work puts me close to how AI agents are actually being deployed inside large organizations, and it has shaped how I think about this project.
While I attempt to present unbiased data, I think it's important to admit my own real biases instead of pretending that they don't exist: I am both fascinated and terrified by AI. I use AI every single day of my life and am amazed by the quality and speed at which the technology is advancing. And at the same time, I lay awake at night thinking about the future of my career and how I will provide for my family if my industry and career were to be impacted. During the daytime, I hear people close to me question whether their jobs, or their children's future jobs, will exist in five or ten years. I began looking into the data and quickly discovered that building a data-based opinion was impossible by reading studies alone.
This site is my attempt to answer that question to the best of my ability: to ground my own opinion in real data, based on facts describing where labor-market stress is emerging, which industries and regions appear structurally exposed to AI, and which communities have greater capacity to adapt.