Soil Scientists

With an automation risk score of 24%, Soil Scientists has a low risk of AI replacement. Most tasks in this role require skills that are difficult for AI to replicate, such as complex decision-making, physical dexterity, or deep interpersonal interaction. AI is more likely to serve as a supportive tool.

The AI automation risk score for Soil Scientists is 24% (2025 data). Overall AI exposure is 37%, with 55% theoretical exposure and 18% observed exposure. The risk trend from 2023 to 2025 is +8 points.

The tasks with the highest automation potential for Soil Scientists are: Map soil types using GIS and remote sensing technologies (60%), Analyze soil samples for chemical and physical properties (55%), Write technical reports and environmental compliance documents (52%). 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 +5% employment change for Soil Scientists from 2024 to 2034. Combined with an overall AI exposure of 37%, 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 Soil 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.