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ロボットか人か?

Any other job (build your own)

A person doing the job vs A robot doing the job

Whirrworkによるモデル推計であり、事実ではありません。 方法論 · 予測の検証記録

人 · 年額$92,465Person
ロボット · 年額$56,213Buy
回収期間23 か月
逆転する年すでにBase-case year (earliest to latest across scenarios)

On these numbers the robot option is clearly cheaper.

アメリカ合衆国 · USD · BLS OEWS May 2025 national medians by SOC occupation

自分の数字で計算する

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作業量
仮定

Units of work per day.

仮定

Operating hours per day.

仮定

Working days per month.

仮定

Months per year.

人員

BLS OEWS May 2025 national median hourly wage, SOC 00-0000.

Wages and salaries were 70.0% of total employer compensation cost for private industry workers in June 2026 (ECEC), so total cost = wage / 0.70.

Nominal 4.4% a year, 2015-2025 (ILOSTAT hourly earnings).

仮定

Units per person-hour.

ロボット
仮定

Robot units per hour relative to a person.

仮定

Robot price. Replace with a quote.

仮定

Lease per robot-month.

仮定

RaaS per robot-month.

仮定

Integration. In factories this is often 1-3x the robot price.

仮定

Yearly maintenance share of price.

仮定

Useful life in years.

仮定

Availability.

仮定

Work lost to faults.

仮定

Work that stays human.

仮定

Staff minutes per robot-hour.

仮定

kWh per robot-hour.

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Electricity price per kWh (USD). Check your bill; energy is rarely a big line.

資金
仮定

Annual financing / discount rate. Nobody publishes yours; 8% is a round mid-2026 commercial borrowing guess.

仮定

Years in the NPV comparison.

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Share of a human service price that is labour (rises with wages). Used to escalate and to adjust US service prices to other countries.

仮定

Share of a robot service price that is labour (pilot, technician). The rest is equipment, which learning curves make cheaper.

仮定

Share of a lease or RaaS fee that pays for hardware (learns down). The rest is service and support (moves with wages).

Download these results (CSV)

結果

選択肢月額年額Per unit (unit)初期費用回収期間Break-even utilisation5-year NPV vs baseline
人 Person 比較の基準 $7,705$92,465$3.50— — — —
ロボット Buy
Robots needed: 2
$4,684$56,213$2.13$120,000 23 か月 29%
Utilisation 63%
$170,382
ロボット Lease
Robots needed: 2
$5,382$64,582$2.45$20,000 7.5 か月 37%
Utilisation 63%
$135,899
ロボット RaaS
Robots needed: 2
$5,382$64,582$2.45$20,000 7.5 か月 37%
Utilisation 63%
$135,899

What moves the answer most

Each bar shows the 5-year NPV of the best robot option when one input moves to the low or high end of its range, with the rest held at your values.

5-year NPV vs baseline: Buy5-year NPV vs baseline: BuyRobot purchase pricelow value: 25000 → $227,118high value: 100000 → $56,909Robot output vs a personlow value: 0.5 → $77,949high value: 2 → $244,967Hourly wagelow value: 19.608000000000004 → $109,473high value: 29.412 → $231,291Employer on-cost multiplierlow value: 1.2790000000000001 → $138,414high value: 1.579 → $202,350Integration and setuplow value: 5000 → $185,382high value: 60000 → $130,382Financing and discount ratelow value: 0.05 → $193,803high value: 0.12 → $142,737Wage growth per yearlow value: 0.0236 → $159,351high value: 0.0636 → $181,836Electricity price per kWhlow value: 0.08 → $170,705high value: 0.3 → $169,690$170,382low valuehigh valueSource: Whirrwork Robot-or-Human model v1.0.0 (whirrwork.com/tools/robot-vs-human/generic/). Modelled estimate, not a fact.

Cost per unit to 2035

Real terms (today's money). Robot hardware follows Wright's law; wages follow each country's history. Shaded band: robots-slow to robots-fast scenarios. Whirrworkによるモデル推計であり、事実ではありません。

Chart単位あたりの人件費 (基本), 単位あたりのロボット費用 (基本), 単位あたりのロボット費用 (ロボット:進歩が速い), 単位あたりのロボット費用 (ロボット:進歩が遅い). Source: Whirrwork Robot-or-Human model v1.0.0 (whirrwork.com/tools/robot-vs-human/generic/). Modelled estimate, not a fact.$0.00$1.00$2.00$3.00$4.002026202720282029203020312032203320342035USD / unitscenario range単位あたりの人件費 (基本)単位あたりのロボット費用 (基本)単位あたりのロボット費用 (ロボット:進歩が速い)単位あたりのロボット費用 (ロボット:進歩が遅い)Source: Whirrwork Robot-or-Human model v1.0.0 (whirrwork.com/tools/robot-vs-human/generic/). Modelled estimate, not a f…

逆転する年: すでに

What the spreadsheet misses

安全性
Dull, dirty and dangerous tasks are where robots most often pay off beyond cost.
品質
Robots repeat; people adapt.
柔軟性
The more the job changes week to week, the more a person is worth.
Edge cases
List the exceptions before you buy; they are usually the expensive part.
Customer experience
Ask customers, not vendors.
Jobs and redeployment
Plan redeployment and training first; it decides whether staff help or hinder.
規制
Machinery, privacy and sector rules vary by country.

関連

このページの出典

注記と出典は英語です。英語版が正式な版です。

  1. Occupational Employment and Wage Statistics, May 2025 (median hourly wage by occupation) U.S. Bureau of Labor Statistics, 2025-05
  2. Employer Costs for Employee Compensation, June 2026: wages and salaries 70.0% of private-industry compensation (series CMU2020000000000P) U.S. Bureau of Labor Statistics, 2026-06
  3. Mean nominal hourly earnings of employees by sex and occupation (ISCO-08), DF_EAR_EHRA_SEX_OCU_CUR_NB ILOSTAT (International Labour Organization), from national labour force and earnings surveys, 2025
  4. Labour cost levels by NACE Rev. 2 activity (lc_lci_lev): Germany 2022-2025, total labour cost vs wages and salaries per hour Eurostat, 2025
  5. Rates and thresholds for employers 2025 to 2026 (employer Class 1 NIC 15% above £5,000) HM Revenue & Customs, 2025-04-06
  6. 令和6年賃金構造基本統計調査 (Basic Survey on Wage Structure 2024), table 1 by occupation Ministry of Health, Labour and Welfare, Japan (via e-Stat), 2024-06
  7. Average monthly earnings of employees by sex and economic activity, DF_EAR_EMTA_SEX_ECO_CUR_NB ILOSTAT (International Labour Organization), 2022
  8. Average annual wage of employed persons in urban units in 2024 (by position and by region) National Bureau of Statistics of China, 2025-05-20
  9. Euro foreign exchange reference rates (cross rates to USD), via Frankfurter European Central Bank, 2026-10-23
  10. Wright, T. P. (1936). Factors affecting the cost of airplanes. Journal of the Aeronautical Sciences, 3(4), 122-128 Journal of the Aeronautical Sciences, 1936
  11. Nagy, B., Farmer, J. D., Bui, Q. M., & Trancik, J. E. (2013). Statistical basis for predicting technological progress. PLoS ONE, 8(2), e52669 (62 technologies; Wright's law among the best hindcasters; errors grow with horizon) PLoS ONE, 2013