Will AI replace Biochemists and Biophysicists?
Work in Biochemists and Biophysicists sits in the in-between: AI reaches some of it (~45% in theory) but is only measured doing about 8% today — part human, part machine.
O*NET-SOC 19-1021
How your 20 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~45%). By late 2025, real-world AI use had reached about 8% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~45%), real-world use (~8%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 20 tasks, ratedBased on real task-level AI scores — click to collapse
- Share research findings by writing scientific articles or by making presentations at scientific conferences.
- Write grant proposals to obtain funding for research.
- Prepare reports or recommendations, based upon research outcomes.
- Teach or advise undergraduate or graduate students or supervise their research.
- Study physical principles of living cells or organisms and their electrical or mechanical energy, applying methods and knowledge of mathematics, physics, chemistry, or biology.
- Manage laboratory teams or monitor the quality of a team's work.
- Develop new methods to study the mechanisms of biological processes.
- Determine the three-dimensional structure of biological macromolecules.
- Study spatial configurations of submicroscopic molecules, such as proteins, using x-rays or electron microscopes.
- Study the chemistry of living processes, such as cell development, breathing and digestion, or living energy changes, such as growth, aging, or death.
- Study the mutations in organisms that lead to cancer or other diseases.
- Research the chemical effects of substances, such as drugs, serums, hormones, or food, on tissues or vital processes.
- Develop or execute tests to detect diseases, genetic disorders, or other abnormalities.
- Develop or test new drugs or medications intended for commercial distribution.
- Examine the molecular or chemical aspects of immune system functioning.
- Research how characteristics of plants or animals are carried through successive generations.
- Design or perform experiments with equipment, such as lasers, accelerators, or mass spectrometers.
- Design or build laboratory equipment needed for special research projects.
- Research transformations of substances in cells, using atomic isotopes.
- Isolate, analyze, or synthesize vitamins, hormones, allergens, minerals, or enzymes and determine their effects on body functions.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.