Answer capsule
The code that took effect April 1, 2025 added language covering obligations carried out through software, databases, technology-assisted tools, and artificial intelligence.
What the source establishes
- ICF states that the current Code of Ethics took effect on April 1, 2025.
- New Standard 2.5 expressly applies ethical and legal obligations through technology systems and AI.
- New Standard 3.7 requires disclosure when an ICF professional is acting in another professional capacity.
Decision implication
Private AI coaching engagements should state when the coach is coaching, training, advising, building, or consulting because those modes allocate authority and responsibility differently.
The accountable team should translate this point into a named workflow, affected population, source data, human owner, approval right, exception path, retained evidence, and review date. That translation is what separates an interesting AI development from a decision that can be governed and evaluated.
Evidence to inspect
Inspect the engagement agreement for tool disclosure, recording and transcription choices, model access, file retention, subcontractors, and role changes during the work.
The accountable team should translate this point into a named workflow, affected population, source data, human owner, approval right, exception path, retained evidence, and review date. That translation is what separates an interesting AI development from a decision that can be governed and evaluated.
Boundary and caveat
The ICF code governs members and credential holders within its ecosystem; it is not a license regime for everyone who markets AI coaching.
The accountable team should translate this point into a named workflow, affected population, source data, human owner, approval right, exception path, retained evidence, and review date. That translation is what separates an interesting AI development from a decision that can be governed and evaluated.
What to do next
Ask the coach to walk through one hypothetical role transition and one data-handling scenario before any sensitive executive material is shared.
The accountable team should translate this point into a named workflow, affected population, source data, human owner, approval right, exception path, retained evidence, and review date. That translation is what separates an interesting AI development from a decision that can be governed and evaluated.
Decision test
Ask whether the source changes the decision itself, the evidence required, the implementation sequence, or only the language used to describe an existing capability. Record which claims are directly supported, which are provider statements, which require an independent test, and which remain unknown. A source-linked review should make uncertainty easier to see, not bury it inside a blended score.
Questions to take into review
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