Broadcasting and Audio-visual Technicians

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 7 task statements that define Broadcasting and Audio-visual Technicians (ISCO-08 3521) score an average of 0.35 on a 0–1 exposure scale — more exposed than about 65% of the 427 placed occupations. Roughly 0% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Minimal band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 7 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Controlling equipment to edit and mix image and sound recordings to ensure satisfactory quality and to create special image and sound effects;”

Scores 0.52 on the 2025 scale. The task of controlling equipment to edit and mix image and sound recordings involves both technical skills and creative input. Generative AI can significantly aid in the technical aspects, such as initial sound editing, image processing, and automatically suggesting edits based on typical workflows or historical data. Semantically similar tasks, like conducting sound recordings (0.6), designing sound systems (0.3675), and performing audio system configurations (0.6000000000000001), reflect a moderate to high potential for automation. The score aligns with these tasks but accounts for the creative judgment needed in mixing image and sound, which requires human expertise to achieve the desired artistic effect and make complex decisions in real-time. Given the advanced technological infrastructure in high-income countries like Poland, where AI tools are accessible, the automation potential is significant but not without necessity for human oversight, thus justifying the adjusted score of 0.59.

Moving fastest, 2023 → 2025

“Applying knowledge of principles and practices of image and sound recording and editing in order to identify and solve problems;”

Model capability on this task changed by +0.10 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 3521, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Audio and Video Technicians
• Camera Operators, Television, Video, and Film
• Broadcast Technicians
• Sound Engineering Technicians
• Media and Communication Equipment Workers, All Other

In context

Part of the 3 - Technicians and associate professionals major group. Return to the full gradient to see how the whole group sits.

Broadcasting and Audio-visual Technicians sit at the 65th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Broadcasting and Audio-visual Technicians rank in the 65th percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 0% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.01 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Controlling equipment to edit and mix image and sound recordings to ensure satisfactory quality and to create special image and sound effects;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Broadcasting and Audio-visual Technicians". https://singulariki.com/gradient/3521-broadcasting-and-audio-visual-technicians.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.