SOC 27-4010Canada NOC 52112Displacement risk

Broadcast, sound, and video technicians: AI exposure and career outlook

Broadcast, sound, and video technicians (SOC 27-4010) sit at the 42nd percentile for measured AI exposure among the 342 occupations tracked here, measured from a composite of Microsoft Research and Anthropic Economic Index telemetry. An estimated 21% of tasks are already automated and 46% are being reshaped rather than replaced — both modelled figures, not direct measurements. Of the Claude usage observed in this occupation, 63% follows an automation pattern and 37% an augmentation pattern, which places it in the Displacement risk group: the routine layer of this work is being automated outright. The judgment layer is not, so the move is to own more of it. In Canada the role maps to NOC 52112 (Broadcast technicians), and ESDC's COPS 2024–2033 outlook for that unit group is balance.

Figures last updated 2026-06. Every number on this page is labelled measured or modelled; where a source has no coverage for this occupation, it says so rather than showing a zero.

Key facts

SOC code
27-4010
Canada NOC 2021
52112
TEER level
2 — College / Apprenticeship 2+ yrs
COPS outlook
Balance

What the measurements actually say

Three independent studies measure AI exposure for this occupation directly. The two percentages below them are ours, modelled from those measurements.

Measured and modelled AI exposure figures for Broadcast, sound, and video technicians
MetricValueProvenance
AI applicability15%Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities. Occupation-group average of 4 detailed roles.
Observed AI usage1%Measured — Anthropic Economic Index, share of tasks observed being performed with Claude (CC-BY 4.0). Occupation-group average of 3 detailed roles.
Academic AI exposure60th percentileMeasured — Felten-Raj-Seamans AIOE index across 774 occupations; the index underlying Statistics Canada's Canadian estimates. Occupation-group average of 4 detailed roles.
Automation-pattern usage63%Measured — the share of observed Claude usage in this occupation where the task is handed over rather than iterated on (Anthropic Economic Index). Occupation-group average of 3 detailed roles.
Augmentation-pattern usage37%Measured — the complement of the row above; the two sum to 100% by construction. This is the pattern where the person stays in the loop.
Estimated task automation (modelled)21%Modelled from this occupation's measured telemetry composite, mapped through anchors calibrated to Anthropic's published aggregate findings. Our estimate, not per-occupation telemetry.
Estimated task reshaping (modelled)46%Share of tasks where AI acts as co-pilot rather than replacement. Modelled from the measured telemetry composite, calibrated to BCG's published aggregate reshaping rates. Our estimate.
Exposure band: Reshaping

AI is transforming how this work is done. Professionals who adapt their workflows will thrive; those who don't face increasing competition.

In Canada: NOC 52112

Broadcast, sound, and video technicians map to NOC 52112 — Broadcast technicians at TEER 2 (College / Apprenticeship 2+ yrs). ESDC's COPS 2024–2033 projection for this unit group is Balance.

Mapped via Statistics Canada's official SOC 2018 → NOC 2016 → NOC 2021 correspondence tables (closest match of several correspondence candidates). Several candidates were available, and this one matched the occupation title on every word — no other did — so the TEER level read off its second digit is reported.

What this job actually involves

These are the O*NET task statements for Broadcast, sound, and video technicians— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 87, core tasks first.

The exposure figures above are for the occupation as a whole. We do not have a per-task measurement: no published dataset tells us which of these specific tasks AI is doing. Read this as what the job is made of, not as a ranking of what is at risk.

1 of these 12statements do carry one measured signal: Anthropic publishes, per O*NET task, how much of the observed Claude usage on it looked like automation rather than iteration. Those are marked below. It still says how people use AI on that task, not how much of it AI can do — and the unmarked statements carry nothing rather than inheriting the occupation's figure.

Microsoft's applicability score was itself produced by classifying Copilot conversations against the O*NET work-activity catalogue — the same catalogue these groups come from. The published file gives one number per occupation, not one per activity, so we can tell you that 15% of this occupation's work activities are covered by observed AI usage, but not which ones.

SOC 27-4010 is a BLS occupation group. These statements are pooled across the 4 detailed occupations in it, so a given task may apply to only some of them.

Controlling Machines and Processes · 5 tasks

  • Regulate volume level and sound quality during recording sessions, using control consoles.

    Core task · Importance 4.8/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Record speech, music, and other sounds on recording media, using recording equipment.

    Core task · Importance 4.6/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Set up, test, and adjust recording equipment for recording sessions and live performances.

    Core task · Importance 4.6/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Play and record broadcast programs, using automation systems.

    Core task · Importance 4.5/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Set up, operate, and maintain broadcast station computers and networks.

    Core task · Importance 4.5/5 (O*NET) · reported by 1 of 4 occupations in this group

Making Decisions and Solving Problems · 3 tasks

  • Separate instruments, vocals, and other sounds, and combine sounds during the mixing or postproduction stage.

    Core task · Importance 4.6/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Prepare for recording sessions by performing such activities as selecting and setting up microphones.

    Core task · Importance 4.5/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Mix and edit voices, music, and taped sound effects for live performances and for prerecorded events, using sound mixing boards.

    Core task · Importance 4.4/5 (O*NET) · reported by 1 of 4 occupations in this group

Communicating with Supervisors, Peers, or Subordinates · 2 tasks

  • Confer with producers, performers, and others to determine and achieve the desired sound for a production, such as a musical recording or a film.

    Core task · Importance 4.8/5 (O*NET) · reported by 1 of 4 occupations in this group

  • Report equipment problems and ensure that required repairs are made.

    Core task · Importance 4.5/5 (O*NET) · 89% of observed AI use on this task is automation-pattern · reported by 1 of 4 occupations in this group

Monitoring Processes, Materials, or Surroundings · 1 task

  • Observe monitors and converse with station personnel to determine audio and video levels and to ascertain that programs are airing.

    Core task · Importance 4.4/5 (O*NET) · reported by 1 of 4 occupations in this group

Repairing and Maintaining Electronic Equipment · 1 task

  • Report equipment problems, ensure that repairs are made, and make emergency repairs to equipment when necessary and possible.

    Core task · Importance 4.5/5 (O*NET) · reported by 1 of 4 occupations in this group

Task statements and work activities from the O*NET Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under CC BY 4.0. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not reviewed or approved this material.

That's the average. Is this you?

Everything above describes Broadcast, sound, and video technicians as a whole. Three questions, and nothing is stored or sent.

Where are you in your career?

What does your week mostly look like?

Is your employer deploying AI?

Where the leverage is

Upskill in AI-driven automation (e.g., Make, Zapier) and generative tools in your domain. The opportunity is to pivot from execution to directing AI-augmented workflows.

AI is transforming tasks rather than replacing entire jobs. Routine scheduling and communication automate, but human decision-making remains critical.

Canada transition step

Master workflow automation platforms (e.g., Make, Zapier, CRM integrations) to double your output and position for fractional leadership roles.

This guidance is written per exposure band — three texts across all 342 occupations, framed on the ILO's transformation-versus-displacement distinction. It is editorial guidance for the reshaping band, not an occupation-specific research finding about broadcast, sound, and video technicians.

Sources for this occupation

Only the sources that hold data for broadcast, sound, and video technicians are listed. A study that does not cover this occupation is not cited here.

  • Microsoft Research — Working with AI (Tomlinson et al., arXiv:2507.07935): Measured AI applicability, from 200,000 anonymised Copilot conversations classified against O*NET work activities.
  • Anthropic Economic Index: Measured observed AI usage per occupation, from Anthropic's open per-SOC dataset (CC-BY 4.0).
  • Felten, Raj & Seamans — AI Occupational Exposure index: Measured academic exposure percentile; the index underlying Statistics Canada's Canadian AI-exposure estimates (Mehdi & Morissette, 2024).
  • O*NET Database 31.0 (USDOL/ETA), CC BY 4.0: The occupation's task statements and work activities, verbatim. Joined on SOC 2018 with no crosswalk — O*NET-SOC is built on SOC — and carrying no claim about which tasks AI touches.
  • Anthropic Economic Index — collaboration split (release 2026-06-26, CC-BY 4.0): Measured share of observed Claude usage following an automation rather than an augmentation pattern. This is the second axis of the grouping above.
  • Statistics Canada NOC 2021 concordance: Official SOC 2018 → NOC 2016 V1.3 → NOC 2021 V1.0 correspondence tables. TEER is the second digit of the resolved code, so we report it only where the concordance gave a single candidate.
  • ESDC COPS 2024–2033: Projected labour-market assessment per NOC 2021 unit group, from the Canadian Occupational Projection System open dataset.
  • BCG — AI Will Reshape More Jobs Than It Replaces (April 3, 2026): Published aggregate reshaping rates, used to calibrate our modelled percentages. The per-occupation figures here are our estimates, not BCG's data.

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