EXPOSED
Truing a wheel, bleeding hydraulic brakes, chasing a creak, and pressing bottom brackets are dexterity problems no current robot handles at shop economics, so the physical core is effectively untouched by AI. What AI does erode is the surrounding layer: diagnostic Q&A, parts lookup and compatibility checks, quotes, scheduling, and the how-to content that once brought customers through the door. There is no license and no personal liability, so the moat is hands and trust with local riders, not regulation — and the real employment risk here is retail economics and DIY substitution rather than automation.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $30,330 → $42,780 +12.8% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-2.3% 13,200 → 12,900 on the projections basis
Shrinking, but not obviously because of AI
The BLS projects -2.3% by 2034, but at 55/100 this work is only moderately exposed — not the profile of a job current AI can simply do. Occupations shrink for many reasons, and the score does not point at automation as this one's cause.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~1,600 openings a year on average, including replacing people who leave.
Bike MechanicShop MechanicBicycle FitterBike AssemblerBike TechnicianShop TechnicianBicycle MechanicBicycle RepairerBicycle AssemblerBicycle RepairmanBicycle TechnicianService TechnicianBicycle Repair TechnicianBicycle Service TechnicianService Shop Technician (Service Shop Tech)Bike Assembler Tech (Bicycle Assembler Technician)
Holding it up: task resistance . Weakest point: liability shield .
Tasks largely resist digitisation Lacing a 32-spoke wheel from loose parts, feeling for the exact tension that pulls a hop out without adding a wobble, and tracing a creak that could be the seatpost, the pedals, or a cracked chainstay are tasks with no digital handle at all — 17 rather than 20 only because the front-of-shop work (checking a derailleur's compatibility with a new 12-speed cassette, writing the estimate, ordering the part) is now genuinely done faster with a model.
Hands-on in uncontrolled environments Every billable minute is hands on a bike in a stand — cutting and facing a head tube, pressing a BB30 shell, bleeding a Shimano caliper without a bubble, wrestling a tubeless tire onto an unfamiliar rim — and the 17 rather than 19 reflects that it happens in your own shop with your own tools and lighting, not roadside in the rain or on a race-support tailgate.
No licence, no signature requirement No state licenses bicycle repair, there is no ASE-equivalent exam you must pass, and a bike you assembled that fails is a shop insurance and CPSC-recall matter rather than something attached to your name — the 2 acknowledges only that a signed pre-delivery inspection can be pulled into a lawsuit, which is nothing like a mechanic's or electrician's personal exposure.
Meaningful discretion You make real calls that manuals do not settle — whether a scored carbon fork is done, whether a 1997 frame is worth a $300 drivetrain, whether to overrule the torque spec on a stripped insert — but most days run on published spec sheets and standard tune-up sequences, and the consequence of a wrong call is a returned bike rather than an unrecoverable one, which is why this sits at 8.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (17/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (2/20) is whether the law requires a licensed human to sign. Trust premium (11/20) is whether buyers specifically pay for a person. Judgment and accountability (8/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 21 of this occupation's 55 points (38%).
Embodiment (17/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 75/100 — SAFE.
Certification schemes (Barnett's, United Bicycle Institute, Shimano/SRAM/Bosch factory service authorization) becoming a purchase criterion because warranty coverage on high-value e-bike drivetrains and batteries is void unless work is done at an authorized service center — manufacturer-enforced, already partly in place for Bosch and Shimano STEPS.
Growth in the share of work that is e-bike electrical and structural triage rather than mechanical adjustment — proprietary diagnostic tools, sealed packs, and manufacturer-restricted firmware make the diagnostic tier both less scriptable and less DIY-substitutable.
E-bike and speed-pedelec service becoming a regulated safety inspection: a state or CPSC rule (following CPSC's 2023-25 attention to lithium battery fires and NYC Local Law 39) requiring battery/charger and brake work on Class 2-3 e-bikes to be performed and signed off by a certified technician, with shop liability attached. UL 2849/2271 recertification-after-repair requirements would do the same by insurer mandate.
Insurers or fleet operators (bikeshare, delivery fleets, e-cargo) requiring a named certified mechanic's signed pre-deployment inspection record as a condition of coverage — already contractually normal in some municipal bikeshare maintenance agreements, and expandable if e-bike fire/brake-failure claims rise.
Task-mix shift: as AI absorbs parts lookup, compatibility checks, and quoting, the remaining paid work concentrates in intermittent-fault diagnosis, frame/fork damage go-no-go calls on carbon, and battery pack condemn decisions where the mechanic owns a safety verdict a customer cannot verify. This raises judgment weight without any new law.
The limit. Ceiling is low: no licensing body exists, headcount is small and shrinking on retail economics, and DIY substitution plus AI how-to content pressures demand regardless of dimension scores. The e-bike regulatory route is the only real path above ~65, and it would concentrate work in authorized dealers rather than lift the occupation broadly.
| New York-Newark-Jersey City, NY-NJ | 760 | $52,150 +22% |
| Los Angeles-Long Beach-Anaheim, CA | 560 | $44,780 +5% |
| Chicago-Naperville-Elgin, IL-IN | 470 | $38,250 -11% |
| Denver-Aurora-Centennial, CO | 330 | $47,860 +12% |
| San Francisco-Oakland-Fremont, CA | 320 | $48,300 +13% |
| Portland-Vancouver-Hillsboro, OR-WA | 250 | $47,930 +12% |
| Seattle-Tacoma-Bellevue, WA | 220 | $51,550 +21% |
| Dallas-Fort Worth-Arlington, TX | 210 | $38,730 -9% |
| New York-Newark-Jersey City, NY-NJ | 760 | $52,150 +22% |
| Seattle-Tacoma-Bellevue, WA | 220 | $51,550 +21% |
| Portland-South Portland, ME | 40 | $49,580 +16% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 55. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.