Chemists

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 9 task statements that define Chemists (ISCO-08 2113) score an average of 0.39 on a 0–1 exposure scale — more exposed than about 74% 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 9 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Conducting research and improving or developing concepts, instruments, theories and operational methods related to chemistry;”

Scores 0.55 on the 2025 scale. The task of conducting research and improving or developing concepts, instruments, theories, and operational methods in chemistry requires a blend of creative problem-solving, significant domain expertise, and experimental work that Generative AI cannot fully automate. Similar tasks, like conducting scientific activities or developing statistical research methods, involve in-depth understanding, experimental design, and analysis, necessitating human oversight and judgment, despite AI's capabilities in assisting data analysis and generating initial drafts. The adjusted scores for such tasks were around 0.47 to 0.62, reflecting AI's assistive potential without full automation due to the need for human intuition and contextual understanding. Considering the nature of chemistry research, which often involves innovative thinking, hypothesis testing, and complex solution design, AI can assist particularly with data-related tasks but falls short in replacing expert judgment and creative ideation. For instance, the task of analyzing algorithms, which is highly data-driven, was adjusted to 0.77 as it relies on structured data processing, unlike chemistry research which is less routine and highly variable. Additionally, the capabilities of Generative AI to assist in repetitive and administrative aspects of the research process, such as data entry or literature review, are noteworthy, but the essence of research in chemistry remains intrinsically human-driven. Therefore, the adjusted score of 0.45 accounts for AI assistance in routine and computational aspects while highlighting the indispensable human role in the core research components of creativity and scientific discovery.

Moving fastest, 2023 → 2025

“Conducting research and improving or developing concepts, instruments, theories and operational methods related to chemistry;”

Model capability on this task changed by +0.20 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 2113, 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.

• Chemists
• Physical Scientists, All Other
• Remote Sensing Scientists and Technologists
• Materials Scientists

In context

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

Chemists sit at the 74th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Chemists rank in the 74th 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 rose by 0.07 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Conducting research and improving or developing concepts, instruments, theories and operational methods related to chemistry;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Chemists". https://singulariki.com/gradient/2113-chemists.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.