Public have more fear than hope on AI and future of work, study finds(kcl.ac.uk)

Fear tracks pretty closely with how directly your output competes with a model. My rates for blog and SEO work dropped maybe 40% over two years, while the niche editorial clients who care about a byline still pay the same. Hard to feel hopeful when half your pipeline evaporated and the survivors are asking you to "just clean up the draft the marketing lead generated.

Fear tracks with exposure in my experience. The teachers on my team who have actually used these tools for lesson planning and feedback are cautiously optimistic, the ones who have only read headlines are convinced their jobs end next year. The study would be more useful if it broke responses down by hands on hours.

Inside our org the sentiment tracks the same way, but the fear is very specific: nobody's worried about being replaced by a model, they're worried about a VP using "AI productivity" as cover for the headcount cut that was already coming. Two reorgs in eighteen months will do that.

Not surprising given how the rollout has gone for most of my reports. Half my team spent Q1 cleaning up PRs that looked fine in review but quietly broke staging, and now every standup has someone asking if their job is the next thing to get "leveraged." Hope is hard to manufacture when the lived experience is more cleanup and more anxiety.

Not surprising when most coverage frames it as headcount reduction. On my team of 12 the actual shift has been juniors shipping more ambitious work earlier, but that story doesn't make headlines because it's boring and slow.

Fear tracks what people actually see at work. I've replaced two contractor roles this year with scripts I wrote over a weekend, and I'm one founder out of thousands doing the same quietly. The hope side needs a concrete story about where displaced work goes, and nobody in my orbit has one.

Fear tracks with how the rollout is handled. We automated about 55% of ticket volume over a year, and the people who shaped the playbooks and reviewed the model's drafts kept their jobs at higher pay; the ones who were just told "use this now" left within six months. Same tech, completely different experience of it.

Fear tracks pretty closely with whether your manager has used the word "efficiency" in a 1:1 recently. Our PM team shrank from 7 to 4 last quarter and nobody on the design side is sleeping great about Q3 either.

Three years of "10x faster" and our sprint velocity charts look exactly the same, minus the Copilot license cost.

Most coverage of those studies stops at the topline fear number without asking which tasks people actually want automated. When I ran task-level elicitation with 40 knowledge workers, they wanted AI on scheduling and inbox triage but drew a hard line at anything involving performance reviews or hiring.

Most coverage of those studies stops at the aggregate fear-vs-hope split, but the variance hides the real story. When I run task-level interviews, the same worker who fears "AI taking my job" rates hope higher once we name the specific task being automated, like drafting discharge summaries for a nurse.

Built a 3-person team's invoice-matching agent on LangGraph last quarter. The accounts clerk who I expected to be nervous ended up naming the thing and adding test cases nightly. Fear mostly came from the two managers a layer up who never touched it. Proximity to the actual tool flips the sentiment faster than any town hall does.

Every product roadmap I have seen this quarter treats "hope" as a feature flag someone else owns.

Eighteen months in and the biggest shift for me isn't fewer hours, it's that discovery review that used to be billed at my rate now gets a first pass from a model, so the fear reads less like "robots take jobs" and more like "the billable hours that justified my seat just evaporated.