Every engineering discipline, read like a market.
What each field does, what it takes to get in, and where the labour market is heading — 14 disciplines scored on a live demand index and mapped against graduate supply to show where the real leverage sits.
DET. ADemand Spectrum
live index 0–100 · click a bar to open the fieldSECT. B–BSupply vs Demand — where the leverage is
projected annual growth · click a point to open the fieldDET. CExposure to AI — which fields are actually vulnerable
share of core work technically automatable · click a row to open the fieldExposure tracks one thing more than any other: whether the output is a digital artefact or a physical, licensed, liability-bearing one. Code, drawings, and calculations are directly generable. A commissioned substation, a certified airframe, or a stamped structural drawing carries legal accountability that does not transfer to a model. Note that high exposure is not the same as a threat — in three fields AI is the reason demand is rising.
DET. DCan you get in? — subject requirements
pick your qualification and subjectsEngineering is gated at school-subject level more tightly than almost any other degree, and the gate closes early — by the time you pick at 16, some doors are already shut. Select what you are taking and see which of the 14 disciplines stay open.
The demand index is a composite score (0–100) blending projected employment growth, hiring volume, salary momentum, and the strength of current demand drivers (AI, clean energy, infrastructure, semiconductors). Supply growth is the projected annual change in graduate output / new entrants for each discipline. The gap between the two — market tightness (demand growth − supply growth) — is what actually sets candidate leverage: a field can have high demand and still be crowded if graduates pour in just as fast.
AI exposure (0–100) estimates the share of a discipline's core work that current models can technically generate or automate. It is scored on the nature of the output — digital artefacts (code, drawings, calculations, documents) score high; physical, safety-critical, or licensed work scores low, because a PE stamp or a certification signature is a legal instrument a model cannot hold. Exposure is deliberately separated from stance: a field can be highly exposed and still gain, which is why Computer Engineering and Robotics are marked amplifiers rather than casualties.
Entry requirements show the subjects departments actually gate on, not the full offer. Typical grade ranges span from the most selective departments down to lower-tariff ones, so treat them as a band rather than a target, and always check the individual course page — requirements vary between universities and change year to year. Two details are worth singling out: IB Maths AA versus AI is a genuine trap, since most engineering departments will not accept Applications & Interpretation; and Further Maths is rarely listed as essential but is close to expected at the most selective UK departments. US admission works differently — you are admitted to the university or its engineering school rather than to a named course, so AP subjects are recommended preparation rather than hard gates.
Salary figures are US medians drawn from BLS and 2026 market surveys, shown as entry / median / senior bands. Use the ordering to compare disciplines, not to pin down a single number — actual pay and demand swing hard by country, industry, company, and specialisation. In the UK, UAE, and elsewhere absolute figures differ, but the relative ordering largely holds.
The comparison console at the foot of the page resolves discipline names from your question and builds a side-by-side table from this dataset, then asks a model for the written read. If the model call fails the console answers from the on-page data alone, so the comparison always works — but note that self-hosting this file requires routing the model call through your own backend with an API key, since the browser cannot hold one safely.
On "live": the ticker and demand index move in real time as a simulated market layer — small intraday drift around each field's fixed baseline, the way a terminal shows a quote ticking between data releases. The underlying demand, supply, salary, and growth figures are editorial estimates from BLS / 2026 surveys and do not update in real time.