Authors and Related Writers

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 6 task statements that define Authors and Related Writers (ISCO-08 2641) score an average of 0.55 on a 0–1 exposure scale — more exposed than about 92% 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 6 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Selecting material for publication, checking style, grammar and accuracy of content, arranging for any necessary revisions and checks proof copies before printing.”

Scores 0.66 on the 2025 scale. The task of selecting material for publication, checking style, grammar, and accuracy of content, arranging for necessary revisions, and checking proofs before printing is largely text-focused and similar to tasks like "Conducting successive corrections until the text is free from composition errors" and "Applying corrections, text editing etc." These tasks, which involve editing and proofreading, are highly automatable with Generative AI due to its capabilities in pattern recognition and error detection in text, aligning with scores around 0.65 to 0.675. However, the task also contains elements requiring human oversight, such as nuanced stylistic judgment and final proof validation to ensure content meets specific editorial standards. This aligns with the automation potential yet necessitates human involvement for contextual nuances and strategic decisions. Given the high-income country context like Poland with prevalent digital infrastructure, the adjusted score reflects the strong capabilities of AI to support this task while acknowledging the indispensable human role in the final quality assurance stages.

Moving fastest, 2023 → 2025

“Analysing material, such as specifications, notes and drawings, and creating manuals, instructions for use, user guides and other documents to explain clearly and concisely the installation, operation and maintenance of software, electronic, mechanical and other equipment;”

Model capability on this task changed by +0.03 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 2641, 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
• Technical Writers
• Writers and Authors
• Poets, Lyricists and Creative Writers

In context

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

Authors and Related Writers sit at the 92nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Authors and Related Writers rank in the 92nd 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 0.14 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Selecting material for publication, checking style, grammar and accuracy of content, arranging for any necessary revisions and checks proof copies before printing.". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Authors and Related Writers". https://singulariki.com/gradient/2641-authors-and-related-writers.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.