Computer and Information Research Scientists

With an automation risk score of 25%, Computer and Information Research 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 Computer and Information Research Scientists is 25% (2025 data). Overall AI exposure is 76%, with 90% theoretical exposure and 62% observed exposure. The risk trend from 2023 to 2025 is 0 points.

The tasks with the highest automation potential for Computer and Information Research Scientists are: Analyze experimental results and benchmark computational performance (72%), Write and review research papers and technical publications (58%), Design and implement novel algorithms and computational models (45%). 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 +21% employment change for Computer and Information Research Scientists from 2024 to 2034. Combined with an overall AI exposure of 76%, 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 Computer and Information Research 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.