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Automation Engineer

Based on 10 assessments · 1 from real users

37% Moderate risk

Average realistic automation risk across all Automation Engineer profiles in the dataset.

Raw potential
83%
Realistic risk
37%
Research benchmark ?
50%

Raw potential = I/O automation ceiling. Realistic risk = adjusted for informal knowledge and social context. Research benchmark: Eloundou et al. (2023)

Distribution across 10 profiles. Middle half of Automation Engineers score between 34% and 40%.

0% 50% 100%
p10 · 33%
42% · p90
On-screen work 84%

Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.

In-person + screen 13%

Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.

Computer + action 1%

Computer input, real-world output — needs someone to act on it, not just software.

Fully in-person 2%

No computer required. Furthest from automation — the strongest human advantage.

3 synthetic profiles for a Automation Engineer, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Collaborate with stakeholders and document solutions: gathering requirements from business teams, explaining technical approaches, writing runbooks and handoff documentation
deep expertise
35% AD 7%
Write and debug automation code: developing scripts, workflows, and configuration files using tools like Python, RPA platforms, or workflow engines
19% DD 49%
Test automation deployments: validating that automated processes work correctly across different environments, handling edge cases, and troubleshooting failures
14% DD 53%
Monitor and maintain deployed automations: reviewing logs, fixing broken workflows, optimizing performance, and making incremental improvements to live systems
13% DD 45%
Design and architect automation solutions: analyzing business processes, identifying bottlenecks, and creating technical specifications for new automation projects
deep expertise
11% DD 12%
Research new tools and technologies: evaluating emerging automation platforms, staying current with industry standards, and assessing whether new tech fits organizational needs
deep expertise social element
6% DD 30%

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