Automatic Data Processing (ADP) Tax Provisions (2009 - 2026)
Automatic Data Processing's Tax Provisions was $329.7 million in fiscal Q1 2027 (quarter ended Sep 30, 2026), up 12.0% from $294.5 million a year earlier and up 18.1% from the prior quarter.
Automatic Data Processing (ADP) Tax Provisions (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Automatic Data Processing's Tax Provisions was $1.35 billion through Sep 30, 2026, up 8.6% year-over-year; for FY2026 (ended Jun 30, 2026), it came in at $1.32 billion, up 7.0% from FY2025.
- Tax Provisions has now increased for eight consecutive fiscal years, with a five-year compound annual growth rate of 11.5% (FY2021 to FY2026).
- In earlier fiscal years, Tax Provisions was $1.23 billion in FY2025 (+9.8%), $1.12 billion in FY2024 (+9.2%), $1.03 billion in FY2023 (+19.9%) and $855.2 million in FY2022 (+12.1%).
- Quarterly Tax Provisions has moved between $177.9 million (fiscal Q4 2022) and $422 million (fiscal Q3 2026) over five years.
- Compared with a year earlier, Tax Provisions was higher in seven of the last eight quarters, with growth averaging 7.6%.
- The best year-over-year quarter for Tax Provisions over five years was fiscal Q4 2023 (growth of 28.7%); the worst was fiscal Q4 2026 (a decline of 0.3%).
- Per Business Quant data, ADP's Tax Provisions in the three fiscal quarters before Q1 2027 was $279.2 million (Q4 2026), $422 million (Q3 2026) and $321.2 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 413.65 Bn | 378.59 Bn | 1.93 Bn | 13.56 Mn |
| 2 | Oracle | 374.28 Bn | 246.84 Bn | - | 847.00 Mn |
| 3 | Sap Se | 294.90 Bn | 222.88 Bn | 8.64 Bn | -844.41 Mn |
| 4 | Salesforce | 186.99 Bn | 142.87 Bn | 8.70 Bn | 1.03 Bn |
| 5 | Automatic Data Processing | 120.08 Bn | 106.87 Bn | 2.53 Bn | 329.70 Mn |
| 6 | ServiceNow | 113.02 Bn | 92.28 Bn | 2.90 Bn | 93.00 Mn |
| 7 | Intuit | 95.72 Bn | 75.07 Bn | 3.44 Bn | 177.00 Mn |
| 8 | Relx | 74.73 Bn | 73.84 Bn | - | - |
| 9 | Strategy | 57.35 Bn | 44.49 Bn | 89.63 Mn | 1.41 Bn |
| 10 | Thomson Reuters | 52.16 Bn | 48.13 Bn | - | -59.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 329.70 Mn |
| Jun 30, 2026 | 279.20 Mn |
| Mar 31, 2026 | 422.00 Mn |
| Dec 31, 2025 | 321.20 Mn |
| Sep 30, 2025 | 294.50 Mn |
| Jun 30, 2025 | 280.00 Mn |
| Mar 31, 2025 | 372.40 Mn |
| Dec 31, 2024 | 298.10 Mn |
| Sep 30, 2024 | 279.90 Mn |
| Jun 30, 2024 | 260.00 Mn |
| Mar 31, 2024 | 361.40 Mn |
| Dec 31, 2023 | 265.40 Mn |
| Sep 30, 2023 | 233.40 Mn |
| Jun 30, 2023 | 228.90 Mn |
| Mar 31, 2023 | 320.90 Mn |
| Dec 31, 2022 | 245.00 Mn |
| Sep 30, 2022 | 231.00 Mn |
| Jun 30, 2022 | 177.90 Mn |
| Mar 31, 2022 | 261.40 Mn |
| Dec 31, 2021 | 215.70 Mn |
Automatic Data Processing Tax Provisions 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=tax-provisions&ticker=ADP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "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=tax-provisions&ticker=ADP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();