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Understanding how automation changes work — task by task, with the evidence shown and the uncertainty admitted.

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On this pageFlying it by handWorking the automationWhen two systems disagreeThe decision that is signedKeeping the licence aliveA type rating for an aircraft that did not exist
Occupations›Airline pilot›Tasks, one by one

Airline pilot — tasks, one by one

The unit of analysis is the task, not the job title. Each one below carries its direction, whether the judgement rests on evidence or on platform inference, the reasoning, and what it does not establish.

Tasks
6
With evidence
2/6
Assessed
2026-09-23
Being augmented×2Still human-led×3New task×1

Every task on this page#

Flying it by hand

Still human-led✓ Evidence-backed

Take-off, the approach, the landing, and any moment the automation is switched off — the part of the job where the aircraft goes where your hands put it.

AI / softwareRobotics
Why

European law does not merely permit a person to do this; it requires them to keep doing it. FCL.060 states that a pilot shall not operate an aircraft in commercial air transport or for carrying passengers as pilot-in-command or co-pilot unless they have carried out, in the preceding 90 days, at least three take-offs, approaches and landings as the pilot flying. Very few rules anywhere in this evidence base are written that way round — not who may use a machine, but how recently a named person must have done the thing themselves.

What this does NOT mean

A currency rule is a floor, not a description of the day: three landings in ninety days is compatible with a great deal of the rest being flown by the autopilot, and on a long-haul roster it often is. The rule also accepts a full flight simulator in place of the aircraft, so even this requirement is partly met by a machine. What it establishes is that the authorisation is tied to a person who has recently done it, not how much of the flight that person flew.

Working the automation

Being augmented≈ Platform inference

Programming the flight management system, choosing which level of automation to use, watching what it does, and deciding when it is doing something you did not ask for.

AI / softwareRPA / self-service
Why

This is the oldest automation story in any occupation on this site and it long predates language models: autopilots, flight management systems and autoland have been standard equipment for decades. The direction is augmenting rather than automating for a structural reason rather than a hopeful one — the machine flies, and the licensed person remains the one the rules hold responsible for what it does, which converts the work from flying into supervising rather than removing it.

What this does NOT mean

Supervising is not obviously less work than flying, and nothing on this page measures whether it is. There is also a known cost that this direction does not capture: skill fade on the manual task underneath, which is part of why the currency rule exists at all. A task labelled augmenting says the machine does more of it than before; it does not say the person's day got easier.

When two systems disagree

Still human-led≈ Platform inference

An engine failure, a decompression, a warning that contradicts another warning, weather that closes the destination after the point where you could have gone elsewhere.

AI / software
Why

These are defined by falling outside the case the checklist was written for, which is also the case the system was designed and trained on. They are rare per pilot and admit no delay when they happen. The regulatory architecture puts the resolution with a person on purpose: the commander's authority is not a courtesy, it is where the responsibility is assigned when the procedure runs out.

What this does NOT mean

Rare and critical does not mean numerous. A task can stay with people while the number of people needed to cover it falls, if the rest of the flight thins out around it — which is precisely what reduced-crew proposals are about. Nothing here counts how often this task is reached, and the regulation does not report it.

The decision that is signed

Still human-led≈ Platform inference

Accepting the aircraft, the fuel, the weather and the plan — and being the person named when any of them turns out to have been wrong.

AI / softwareRPA / self-service
Why

Almost every input to this decision is already computed: the flight plan, the fuel figure, the weather package, the performance numbers. What has not moved is who accepts them. That is not a gap in capability — accepting a computed plan is exactly what software could do — it is where the legal system has placed accountability, and accountability is assigned to persons rather than to systems.

What this does NOT mean

An accountability rule is a rule, and rules change: this judgement would flip if liability were reassigned, and that would arrive as a legislative proposal rather than as a product. It also says nothing about how much judgement is left in the decision itself once every input arrives pre-computed, which is a different question and one this page does not answer.

Keeping the licence alive

Being augmented✓ Evidence-backed

Recurrent simulator checks, line checks, the medical, and the ratings that lapse on a date whether or not you have been flying.

AI / softwareRPA / self-service
Why

The same currency rule that requires three take-offs and landings in ninety days accepts a full flight simulator representing that type or class in place of the aircraft. That is a machine standing in for the thing the rule is about, written into the rule itself — which makes this one of the clearest augmenting judgements on the site, because the substitution is not inferred from a vendor's claim but from the text that governs it.

What this does NOT mean

A simulator substituting for an aircraft in a currency check is not the same as a simulator substituting for flying, and the regulation does not claim it is. Nor does any of this say how much recurrent training a pilot actually does, or whether the total is rising or falling — the rule sets a minimum and operators set the rest.

A type rating for an aircraft that did not exist

New task≈ Platform inference

Learning to operate a class of aircraft that only exists because of new propulsion and control automation — and helping work out what its training and checking should even consist of.

AI / softwareAutonomous driving
Why

The aircrew regulation now names VTOL-capable aircraft alongside aeroplanes, helicopters and airships, and sets out the conditions under which a licence and type rating entitle the holder to operate one under instrument flight rules. A new licence category in a licensing regulation is work being created rather than removed, and it is created by automation: these aircraft are flyable because of their control systems, not in spite of them.

What this does NOT mean

A category existing in a regulation is not the same as people being employed in it, and this page holds nothing that counts how many are. Rule-making runs ahead of fleets on purpose, so the honest reading is that the door has been defined, not that anyone is through it.

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