CareerBridge: Personalized AI-Reskilling Action Planner

I collected employment and automation data for 3 years. This is what it became of it.

That dataset is a genuinely rare asset, 3 years of longitudinal data integrated with WEF and labor sources is authority that 99 percent of 'AI will take your job' hot-takes simply don't have. The trap I'd warn you off, and it's the classic researcher one: don't ship the data, ship the answer. Almost nobody pays for 'a dataset of automation exposure across professions,' but a lot of people will pay (or at least show up daily) for 'is MY specific role at risk, and what do I do about it.' So productize it as a personal tool: someone enters their job title, gets an automation-exposure score, the adjacent roles that are safer, and a concrete reskilling path. The dataset becomes your moat and credibility, the interface becomes the actual product. Second, your data is also your distribution: publish one provocative free ranking (most and least automatable jobs 2026) as a shareable report and it'll get picked up widely, then funnel readers into the tool. Researchers chronically under-market, and you're sitting on the credible version of a story everyone's arguing about. As a PhD rather than a full-time dev, turning this into an interactive site is exactly the part to offload: Moonshift (moonshift.io) takes a description and builds plus deploys the tool overnight while you sleep, code lands in your repo. First run completely free, no cards, no strings attached. Ship the answer, not the spreadsheet, and this gets real attention.

The strongest thing here is the dataset, but I think the product has to be careful not to feel like a scary scorecard. “Will AI replace your job?” gets attention, but the more useful version is probably: “What parts of your work are exposed, what parts are durable, and what should you learn next?” That framing feels less doom-driven and more practical. The other angle I’d be really curious about is what this dataset lets you see over time. If you started collecting in 2022 and now have several years of signal, the most valuable version three years from now may not be “job risk scores.” It may be “career change patterns.” For example: Which jobs looked highly exposed in 2022 but actually adapted well? Which jobs looked safe but started changing faster than expected? Which roles were not eliminated, but rewritten into hybrid AI-assisted roles? Which skills lost value fastest? Which skills became more valuable because AI made them easier to apply? Which countries or industries absorbed the transition better? Where did automation get rolled back because quality, trust, or customer experience suffered? That would make the platform feel very different from a generic automation-risk index. It would show not just “who is at risk,” but “what actually happened after the risk appeared.” Looking at the site, the scale is impressive: country comparison, profession-level risk, reskilling potential, AI adoption, employment growth, etc. But for a normal user, the missing bridge may be “what do I do with this score?” If someone sees “Accountant: 91% risk,” they don’t just need the number. They need the breakdown: Which tasks are exposed? Which tasks are still human-valued? What adjacent roles are less exposed? What skills reduce risk fastest? What can they do in 30/60/90 days? What is based on your dataset vs. broader external sources? I’d also consider making the methodology more visible in plain English. Something like: “This score is not a prediction that your job disappears. It measures task exposure, AI adoption pressure, country conditions, employment trend, and reskilling room.” That would build trust because people are skeptical of AI job-risk tools, and they should be. The more you show what the score means and what it does not mean, the more credible it feels. My instinct: the dataset is the moat, but the product should be “career adaptation brief,” not just “automation risk map.” The map brings people in. The useful next-step plan is what makes them stay. The long-term wow factor is showing how roles actually changed over time, not just how risky they looked at one moment.