Journalists

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 10 task statements that define Journalists (ISCO-08 2642) score an average of 0.54 on a 0–1 exposure scale — more exposed than about 91% of the 427 placed occupations. Roughly 100% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Gradient 3 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 10 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Liaising with production staff in checking final proof copies immediately prior to printing;”

Scores 0.67 on the 2025 scale. The task of liaising with production staff and checking final proof copies involves ensuring the quality of print-ready materials, which combines both procedural checks and creative judgment. Similar semantically proximate tasks such as "conducting successive corrections until the text is free from composition errors" have an adjusted score of 0.675, reflecting substantial potential for automation due to Generative AI's strong capabilities in text analysis and pattern recognition. Given the structured nature of proof-checking and the task being performed in a high-income context like Poland, where access to AI resources is widespread, the automation potential is significant. However, human expertise is still required for nuanced judgment and final approval, particularly in understanding tone and intent. Balancing these aspects, a score of 0.65 reflects the substantial role AI can play in this task while recognizing the necessity for human oversight in ensuring the qualitative and subjective aspects of liaising and proof-checking are adhered to.

Moving fastest, 2023 → 2025

“Liaising with production staff in checking final proof copies immediately prior to printing;”

Model capability on this task changed by +0.37 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 2642, 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.

• Editors

In context

Part of the 2 - Professionals major group. Return to the full gradient to see how the whole group sits.

Journalists sit at the 91st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Journalists rank in the 91st 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 100% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.02 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Liaising with production staff in checking final proof copies immediately prior to printing;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Journalists". https://singulariki.com/gradient/2642-journalists.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.