The bottom line
Roughly 80% of the work in Science is information-shaped — already within reach of AI delivery. The question here is not whether it shifts, but which tasks go first and who staffs the residual.
Why: Based on the primary signal, the skill name 'Science' and its description of 'using scientific rules and methods to solve problems' indicate cognitive, analytical knowledge work. Like mathematics or systems analysis, this is an information-processing capability rather than a hands-on physical task, placing it solidly in the digital band.
grounded in the economy graph · digital scalar 0.80 · digital
The problems this exposes
Node-intrinsic problems read straight off the graph (exposesProblem) — the evergreen wedges a builder could take into this space.
- Accelerate Patent Filing Processes
- Accelerated IP Patenting
- Automate Research Data Pipelines
- Cold Chain Specimen Logistics
- Discovery To Market Lag
- Experiment Reproducibility Failures
- Experiment Reproducibility Tracking
- Grant Funding Attrition
- High-Throughput Data Analysis
- IRB Protocol Compliance
+18 more problems on the graph
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Problems
- Experiment Reproducibility Trackingops
- Research Protocol Compliancecompliance
- Niche STEM Talent Sourcingtalent
- R&D Grant Acquisitioncapital
- Accelerated IP Patentingcompetitive
- Specialized Reagent Procurementsupply-chain
- Research Commercialization Transferdemand-gen
Opportunities
- Autonomous Lab NotebookAgent
- Grant Acquisition ServiceService-as-Software
- Reagent Sourcing APIHeadless SaaS
- AI Prior Art AnalystAgent
- Tech Transfer ValuatorService-as-Software