Automatic Data Processing (ADP) Income Taxes Paid (2015 - 2026)
Automatic Data Processing's Income Taxes Paid came in at $187.2 million for fiscal Q1 2027 (quarter ended Sep 30, 2026), up 153.7% from $73.8 million a year earlier but down 65.6% from the prior quarter.
Automatic Data Processing (ADP) Income Taxes Paid (2015 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Automatic Data Processing reported Income Taxes Paid of $1.12 billion, down 7.2% year-over-year; for FY2026 (ended Jun 30, 2026), it came in at $1.01 billion, down 16.0% from FY2025.
- Income Taxes Paid carries a five-year compound annual growth rate of 0.7% (FY2021 to FY2026).
- Going back by fiscal year, Income Taxes Paid was $1.2 billion in FY2025 (+1.1%), $1.19 billion in FY2024 (+9.7%), $1.08 billion in FY2023 (+26.1%) and $856.8 million in FY2022 (-12.0%).
- The five-year range for quarterly Income Taxes Paid is $57.5 million (fiscal Q1 2023) to $544.6 million (fiscal Q4 2026).
- Year-over-year, Income Taxes Paid increased in five of the last eight quarters, with growth averaging 17.7%.
- The fastest year-over-year change in Income Taxes Paid over five years came in fiscal Q1 2027 (growth of 153.7%), and the weakest in fiscal Q2 2026 (a decline of 55.7%).
- Business Quant data shows ADP's Income Taxes Paid at $544.6 million (Q4 2026), $158.4 million (Q3 2026) and $229.9 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes Paid (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 386.60 Bn | 351.42 Bn | 1.93 Bn | - |
| 2 | Oracle | 343.94 Bn | 216.07 Bn | - | - |
| 3 | Sap Se | 272.35 Bn | 199.75 Bn | 8.64 Bn | -790.34 Mn |
| 4 | Salesforce | 175.46 Bn | 131.33 Bn | 8.70 Bn | 222.00 Mn |
| 5 | Automatic Data Processing | 122.07 Bn | 108.86 Bn | 2.53 Bn | 187.20 Mn |
| 6 | ServiceNow | 105.47 Bn | 84.73 Bn | 2.90 Bn | 68.00 Mn |
| 7 | Intuit | 94.25 Bn | 73.60 Bn | 3.44 Bn | - |
| 8 | Relx | 73.66 Bn | 72.75 Bn | - | - |
| 9 | Strategy | 51.78 Bn | 38.91 Bn | 89.63 Mn | - |
| 10 | Thomson Reuters | 50.52 Bn | 46.49 Bn | - | -51.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 187.20 Mn |
| Jun 30, 2026 | 544.60 Mn |
| Mar 31, 2026 | 158.40 Mn |
| Dec 31, 2025 | 229.90 Mn |
| Sep 30, 2025 | 73.80 Mn |
| Jun 30, 2025 | 361.10 Mn |
| Mar 31, 2025 | 253.40 Mn |
| Dec 31, 2024 | 518.80 Mn |
| Sep 30, 2024 | 64.70 Mn |
| Jun 30, 2024 | 379.10 Mn |
| Mar 31, 2024 | 215.70 Mn |
| Dec 31, 2023 | 502.50 Mn |
| Sep 30, 2023 | 87.90 Mn |
| Jun 30, 2023 | 301.90 Mn |
| Mar 31, 2023 | 241.70 Mn |
| Dec 31, 2022 | 479.60 Mn |
| Sep 30, 2022 | 57.50 Mn |
| Jun 30, 2022 | 268.90 Mn |
| Mar 31, 2022 | 222.20 Mn |
| Dec 31, 2021 | 310.70 Mn |
Automatic Data Processing Income Taxes Paid API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=income-taxes-paid&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "income-taxes-paid", "ticker": "ADP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=income-taxes-paid&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();