Sports Data Analysts

With an automation risk score of 51%, Sports Data Analysts 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 Sports Data Analysts is 51% (2025 data). Overall AI exposure is 64%, with 84% theoretical exposure and 45% observed exposure. The risk trend from 2023 to 2025 is 0 points.

The tasks with the highest automation potential for Sports Data Analysts are: Build predictive models for player performance (75%), Analyze game footage and tracking data (70%), Present strategic insights to coaching staff (20%). 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 +20% employment change for Sports Data Analysts from 2024 to 2034. Combined with an overall AI exposure of 64%, 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 Sports Data Analysts 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.