A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-13-2099-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot,
where humans remain in the loop, and what the labor market is doing. Built from observed
Claude.ai conversations mapped to O*NET tasks and from published research — measures of
usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
About average employment outlook (+3.1% by 2034)
10,300 openings/yr
High AI exposure
Median pay $80,190/yr
Can largely be done remotely (teleworkable)
A reversal from 2013 — rated low automation risk then (40th), high AI task-overlap now (87th)
↔87th-percentile task overlap — yet
about 10,300 openings a year
(+3.1% projected, BLS)
. What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is
actually being used in it, and where employment is headed. These are positions
within published studies — measures of exposure and usage, not predictions
that this job will disappear.
This is a broad “All Other” catch-all that groups many different jobs, so treat
the figures below as a rough average for the category, not a precise estimate for
any single role within it.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows —
the percentile (this job's rank among all U.S. occupations with
data) is the comparable figure, and sizes the bars.
Measure
Rank vs all occupations
Percentile
Score
Overall AI exposure (Felten et al.) High
93rd
1.4
LLM task exposure, γ (OpenAI / Eloundou) High
73rd
0.9
AI assistant applicability (Microsoft) High
79th
0.2
OpenAI's exposure study scores tasks three ways: with a language model alone
(α 0.1), with simple added tooling
(β 0.5), and including AI-powered software
(γ 0.9). Higher means more of the job's
tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.3 ·
40th percentile among occupations ·
Moderate
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 —
a labor-market forecast, not an AI-impact forecast.
Outlook
About average · +3.1% by 2034
Projected annual openings
10,300
Employment 2024 → 2034
137,100 → 141,400
“Annual openings” counts new jobs plus replacements for workers who leave the
occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08
occupation system, not US SOC. Bridged through the published (and approximate,
many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the
international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task
overlap, not automation, adoption, or jobs lost.
Financial Specialists, All Other sits at the 82nd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
Read the whole six-band gradient on the GenAI exposure gradient page.
The crosswalk is approximate: a US occupation can map to several international ones, and the
ILO scores describe the international occupation, not this exact US role.
Annual wages by percentile — U.S. (BLS OEWS). The light
band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line
is the median.
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for
the occupation, not an AI-impact forecast.
10th percentile
$46,420
25th percentile
$60,140
Median (50th)
$80,190
75th percentile
$109,120
90th percentile
$151,780
People employed
127,450
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is
the occupation's national median, not industry-specific.
Industries where this occupation is far more common than in the economy as a whole.
The location quotient is how many times more concentrated it is here (a value of 5
means five times its economy-wide share).
▸Write a report on thisheadline · factoids · citation
Financial Specialists, All Other show 87th-percentile AI task overlap — and about 10,300 annual U.S. openings
Financial Specialists, All Other rank in the 87th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
The occupation is projected to see about 10,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
BLS projects employment to be about average (+3.1%) from 2024 to 2034.BLS Employment Projections 2024–34
Median annual pay is $80,190, across about 127,450 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Financial Specialists, All Other show 87th-percentile AI task overlap — and about 10,300 annual U.S. openings
• Financial Specialists, All Other rank in the 87th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 10,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be about average (+3.1%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $80,190, across about 127,450 U.S. workers. (BLS OEWS (May 2024))
Source: Singulariki — "Financial Specialists, All Other". https://singulariki.com/roles/role-13-2099-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
Every line is built only from figures this page already shows and cites. AI task overlap means
what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not
hand-written opinion. See the full methodology for what each
measure does and does not mean.
O*NET 30.3U.S. Department of Labor / National Center for O*NET Development
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Financial Specialists, All Other." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-13-2099-00
APA
Singulariki. (2026). Financial Specialists, All Other. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-13-2099-00
BibTeX
@misc{singulariki-role-13-2099-00,
title = {Financial Specialists, All Other},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-13-2099-00}
}
Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.
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