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AI Automation Index
Will AI Replace Biofuels/Biodiesel Technology and Product Development Managers?
Task-level automation exposure for Biofuels/Biodiesel Technology and Product Development Managers: 18 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
48%
weighted task index
18 of 18 tasks scored
Median Salary
$171,270 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
220,260 people hold this job — size, not growth
Projected 2025–35
+5.5%
employment change
14,900 openings a year · BLS line item
Pay by state
BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$100,740 – $215,120
Highest medians
New Mexico $215,120
California $210,280
Massachusetts $201,430
Washington $189,680
District of Columbia $185,220
Lowest medians
Guam $100,740
Puerto Rico $130,560
Arkansas $140,600
Nebraska $141,020
Wisconsin $142,060
State figures come from the 11-9041 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 48%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 35%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 19/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
18 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 34%
5 tasks
Medium exposure (≥ 35%) 31%
7 tasks
Low exposure (below 35%) 36%
6 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#15574 · Core · 50% automatable
Design or conduct applied biodiesel or biofuels research projects on topics, such as transport, thermodynamics, mixing, filtration, distillation, fermentation, extraction, and separation.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
#15578 · Core · 75% automatable
Analyze data from biofuels studies, such as fluid dynamics, water treatments, or solvent extraction and recovery processes.
data analysis — Energy production data evaluation is quantitative
Evaluate energy production data.
#15567 · Core · 60% automatable
Prepare, or oversee the preparation of, experimental plans for biofuels research or development.
text generation — Strategies drafted; operational feasibility human-owned
Develop operating strategies, plans, or procedures for green or sustainable operations.
#15566 · Core · 28% automatable
Provide technical or scientific guidance to technical staff in the conduct of biofuels research or development.
interpersonal — Directing workers in the field is human supervision
Supervise workers performing environmentally sustainable activities.
#15580 · Core · 60% automatable
Propose new biofuels products, processes, technologies or applications based on findings from applied biofuels or biomass research projects.
decision support — Specs drafted; human validates feasibility
Develop specifications for new products or processes.
#15576 · Core · 30% automatable
Conduct experiments on biomass or pretreatment technologies.
physical manipulation — Testing green tech installations requires physical setup
Test green technologies or processes.
#15568 · Core · 60% automatable
Prepare biofuels research and development reports for senior management or technical professionals.
text generation — AI drafts green energy communications; human reviews
Communicate green energy production information.
#15563 · Core · 68% automatable
Develop lab scale models of industrial scale processes, such as fermentation.
data analysis — Process modeling from specs; human validates model
Model operational processes.
#15579 · Core · 28% automatable
Oversee biodiesel/biofuels prototyping or development projects.
decision support — Plant operations direction needs real-time human control
Direct green energy production operations.
#15577 · Core · 30% automatable
Conduct experiments to test new or alternate feedstock fermentation processes.
physical manipulation — Testing green tech installations requires physical setup
Test green technologies or processes.
#15572 · Supplemental · 50% automatable
Develop methods to estimate the efficiency of biomass pretreatments.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
#15569 · Supplemental · 30% automatable
Perform protein functional analysis and engineering for processing of feedstock and creation of biofuels.
physical manipulation — Testing green tech installations requires physical setup
Test green technologies or processes.
#15581 · Supplemental · 30% automatable
Conduct research to breed or develop energy crops with improved biomass yield, environmental adaptability, pest resistance, production efficiency, bioprocessing characteristics, or reduced environmental impacts.
physical manipulation — Testing green tech installations requires physical setup
Test green technologies or processes.
#15564 · Supplemental · 50% automatable
Develop computational tools or approaches to improve biofuels research and development activities.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
#15570 · Supplemental · 50% automatable
Develop separation processes to recover biofuels.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
#15575 · Supplemental · 50% automatable
Design chemical conversion processes, such as etherification, esterification, interesterification, transesterification, distillation, hydrogenation, oxidation or reduction of fats and oils, and vegetable oil refining.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
#15573 · Supplemental · 50% automatable
Design or execute solvent or product recovery experiments in laboratory or field settings.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
#15571 · Supplemental · 50% automatable
Develop methods to recover ethanol or other fuels from complex bioreactor liquid and gas streams.
decision support — AI proposes biofuel processes; lab validation required
Develop technical processes to improve the efficiency of biofuel production.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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