Will AI replace Management Analysts?
Work in Management Analysts sits in the in-between: AI reaches some of it (~40% in theory) but is only measured doing about 24% today — part human, part machine.
O*NET-SOC 13-1111
How your 10 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~40%). By late 2025, real-world AI use had reached about 24% of its task activity (already common). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~40%), real-world use (~24%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 10 tasks, ratedBased on real task-level AI scores — click to collapse
- Design, evaluate, recommend, and approve changes of forms and reports.
- Gather and organize information on problems or procedures.
- Analyze data gathered and develop solutions or alternative methods of proceeding.
- Document findings of study and prepare recommendations for implementation of new systems, procedures, or organizational changes.
- Plan study of work problems and procedures, such as organizational change, communications, information flow, integrated production methods, inventory control, or cost analysis.
- Review forms and reports and confer with management and users about format, distribution, and purpose, identifying problems and improvements.
- Develop and implement records management program for filing, protection, and retrieval of records, and assure compliance with program.
- Confer with personnel concerned to ensure successful functioning of newly implemented systems or procedures.
- Interview personnel and conduct on-site observation to ascertain unit functions, work performed, and methods, equipment, and personnel used.
- Prepare manuals and train workers in use of new forms, reports, procedures or equipment, according to organizational policy.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.