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Bioinformatics Scientists

Life, Physical & Social Sciencesvery highaugment
BLS 2024-34: +9%
Median Wage: $103,500
Employment: 36K

Overall Exposure

68+16

2025 vs 2023

Theoretical Exposure

82

What AI could do

Observed Exposure

50

What AI actually does

Automation Risk Score

48

Displacement risk

3-Year Outlook (2025 → 2028)

Projected changes in AI automation metrics over the next 3 years based on estimated data.

Overall Exposure

68→83
+15

2025 → 2028 (estimated)

Theoretical Exposure

82→94
+12

2025 → 2028 (estimated)

Observed Exposure

50→68
+18

2025 → 2028 (estimated)

Automation Risk

48→61
+13

2025 → 2028 (estimated)

Exposure Metrics (2023 - 2028)

Detailed Metrics Table

YearOverallTheoreticalObservedRiskData Type
202352703035actual
202460764042actual
202568825048actual
202674875753estimated
202779916357estimated
202883946861estimated

Task Breakdown

Analyze genomic and proteomic data using computational methods
78%β 1
Develop algorithms and statistical models for biological data
62%β 0.5
Manage and curate large biological databases
72%β 1
Design experiments and interpret results in collaboration with lab teams
35%β 0.5
Write research papers and communicate findings to stakeholders
55%β 0.5

About This Occupation

If you work as a Bioinformatics Scientist, AI is reshaping your profession. With an automation risk of 48/100 and overall exposure at 68%, this role faces very high transformation. The highest-impact area is analyze genomic and proteomic data using computational methods at 78% automation. This is classified as an 'augment' role. BLS projects +9% growth through 2034. AI-driven sequence analysis and protein folding predictions are accelerating discovery timelines dramatically.

Frequently Asked Questions

With an automation risk score of 48%, Bioinformatics Scientists faces a moderate level of AI-driven change. Some tasks can be automated, but many require human judgment, creativity, or interpersonal skills that AI cannot yet replicate. The role is more likely to evolve alongside AI than be replaced.

The AI automation risk score for Bioinformatics Scientists is 48% (2025 data). Overall AI exposure is 68%, with 82% theoretical exposure and 50% observed exposure. The risk trend from 2023 to 2025 is +13 points.

The tasks with the highest automation potential for Bioinformatics Scientists are: Analyze genomic and proteomic data using computational methods (78%), Manage and curate large biological databases (72%), Develop algorithms and statistical models for biological data (62%). These rates reflect how much of each task current AI systems can handle, based on research data from Anthropic and academic sources.

The BLS projects +9% employment change for Bioinformatics Scientists from 2024 to 2034. Combined with an overall AI exposure of 68%, this occupation is experiencing both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.

Since AI primarily augments capabilities in this role, professionals in Bioinformatics Scientists should embrace AI as a productivity multiplier. Focus on learning to use AI tools effectively, developing higher-order analytical and creative skills, and positioning yourself as someone who can leverage AI to deliver greater value.

Recent AI Impact Changes

Mar 2026: Published evergreen blog post analyzing AI impact on bioinformatics scientists (68% exposure, 48% risk, augment mode)

[Source: AI Changing Work Blog]