Reach a 600,000 annual global EV run rate
Not delivered by the deadline
AI-assessed · human review in progress Found and assessed by AI from the cited sources. Shown with its evidence; it is not counted in any Kept Score until confirmed.
- Announced
- 21 Jul 2022
- Due
- 31 Dec 2023
- Checked
- 17 Oct 2026
- Deadline
- Met
- Late
- Not met
- Today
What the company said
“reach its targeted annual run rate of 600,000 electric vehicles by late 2023”
What we found
Evidence strength A What the grades mean
The company's filings consistently reference lower-than-anticipated EV adoption rates and volumes, and do not confirm the achievement of the 600,000 annual run rate target by the end of 2023.
-
A Ford Motor Company 10-K filed 2024-02-07
“As a result of the lower-than-anticipated adoption rates, near-term pricing pressures, and other factors, we recorded about $0.7 billion of charges in 2023” ✓ confirmed on the page
Market reaction: the shares moved +3.6% against the S&P 500 over the three sessions around the disclosure (6 Feb 2024 to 9 Feb 2024). What this measures
Checked 17 Oct 2026.
Commitment lineage
Every time the company restated this commitment. The original is never changed, and the outcome is always measured against version 1.
- 1 versions
-
Version 1 · original · stated 21 Jul 2022
Deadline 31 Dec 2023 (“by late 2023”) · target 600,000 EV run rate
-
Version 2 · stated 27 Jul 2023
Deadline 31 Dec 2024 (“during 2024”) · target 600,000 units · wording expected
“Farley said that Ford now expects to reach a 600,000-unit EV production run rate during 2024”
Commitment DNA
The structured record of this commitment. Fields the company did not state are left blank rather than guessed.
- Event type
- Product other
- Indicative materiality
- Low rules
- Action
- Reach
- Deliverable
- 600,000 annual global EV run rate
- Target
- 600,000 EV run rate
- In the company’s control
- High
- Specificity
- High
- Depends on
- Supplier
How this entry was checked
- Commitment recordedThe company's words were matched word for word against the filing.
- First checkAn AI model, Gemini (Google), read the company's later filings and recorded the outcome with a quoted passage.
- Second check: agreesA different AI model, Claude (Anthropic), re-read the evidence without being told the outcome and reached the same answer.
- Third check on a negative finding: disagreesBecause a negative finding could harm a company if wrong, a stronger model re-read the evidence fully blind and read it as “no_evidence”, so a person decides.
Not yet confirmed. Shown on the record, but it will not count in any score until it is confirmed. How verification works
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Report an error in this entry Reference: KI-C-2022-F-012796 · Corrections policy