Will AI replace Bioinformatics Technicians?
On paper, AI could touch ~87% of the work in Bioinformatics Technicians — and unlike most jobs, it's already showing up in the real workday, not just the theory.
O*NET-SOC 15-2099
How your 11 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 high share of this job's tasks (~87%). By late 2025, real-world AI use had reached about 48% of its task activity (already common). 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 (~87%), real-world use (~48%) 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 11 tasks, ratedBased on real task-level AI scores — click to collapse
- Analyze or manipulate bioinformatics data using software packages, statistical applications, or data mining techniques.
- Extend existing software programs, web-based interactive tools, or database queries as sequence management and analysis needs evolve.
- Conduct quality analyses of data inputs and resulting analyses or predictions.
- Develop or maintain applications that process biologically based data into searchable databases for purposes of analysis, calculation, or presentation.
- Participate in the preparation of reports or scientific publications.
- Write computer programs or scripts to be used in querying databases.
- Document all database changes, modifications, or problems.
- Create data management or error-checking procedures and user manuals.
- Maintain awareness of new and emerging computational methods and technologies.
- Enter or retrieve information from structural databases, protein sequence motif databases, mutation databases, genomic databases or gene expression databases.
- Confer with researchers, clinicians, or information technology staff to determine data needs and programming requirements and to provide assistance with database-related research activities.
- ⚠️ None — every core task is at least partly within AI's reach. The job won't vanish, but almost all of it changes.
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.