Public Relations Professionals

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 8 task statements that define Public Relations Professionals (ISCO-08 2432) score an average of 0.43 on a 0–1 exposure scale — more exposed than about 81% 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 2 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 8 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Undertaking and commissioning public opinion research, analysing the findings and planning public relations and promotional campaigns;”

Scores 0.58 on the 2025 scale. The task involves undertaking and commissioning public opinion research, analyzing the findings, and planning public relations and promotional campaigns. This falls under the capability of Generative AI to automate parts of the task, especially in data processing, analysis, and initial content generation for campaigns. However, like similar tasks such as "Conducting survey research" (adjusted score 0.65) and "Promoting and conducting activities in related fields" (adjusted score 0.665), human oversight remains crucial for designing research frameworks, interpreting complex data, and making strategic decisions based on nuanced cultural and societal contexts. The creative and strategic components of planning promotional campaigns further necessitate human involvement, aligning this task with the tasks in the same cluster that were adjusted to 0.62 and 0.635 for promoting services. Thus, an adjusted score of 0.62 reflects the blend of high automation potential in data handling and the indispensability of human insight for strategic planning and execution, particularly in a setting with good technological infrastructure such as Poland.

Moving fastest, 2023 → 2025

“Advising executives on the public relations implications of their policies, programmes and practices preparing and controlling the issue of news and press releases;”

Model capability on this task changed by +0.18 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 2432, 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.

• Public Relations Specialists

In context

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

Public Relations Professionals sit at the 81st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Public Relations Professionals rank in the 81st 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 rose by 0.05 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Undertaking and commissioning public opinion research, analysing the findings and planning public relations and promotional campaigns;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Public Relations Professionals". https://singulariki.com/gradient/2432-public-relations-professionals.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.