Diagnose and evidence AI's effect on customer experience before acting
AI for Business Institute · D6
Customer & Employee Experience
Domain 6 of the AI for Business Institute practitioner standard. Diagnose and evidence AI's effect on customer experience before acting; distinguish genuine employee experience applications from surveillance; design the controls that protect a customer in AI contact; capture feedback through mechanisms that reach the people the tool failed; and close the loop by telling users what changed.
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Time3.4 hours
Structure5 modules · 20 lessons
What you get
$250, and exactly what that buys.
- 5 modules, 20 lessons
One module per framework criterion, about 3.4 hours of material.
- Applied practice, not just reading
Applied scenarios, Card sorting, Matching exercises and more.
- Work at your own pace
Progress is saved as you go, so you can stop and resume on any device.
- Access that does not expire
Once bought, the course stays in your account. There is no renewal to keep it.
- Counts toward the full programme
Complete all nine domains and the Institute issues your programme completion certificate.
This does not include the accreditation exam. This course builds and evidences capability. Accreditation is a separate assessment, available with the full programme for $2,000, and the credential is awarded only if you pass it.
Why this course
Know what good looks like. Practise the decisions that make it real.
Domain 6 of the AI for Business Institute practitioner standard. Diagnose and evidence AI's effect on customer experience before acting; distinguish genuine employee experience applications from surveillance; design the controls that protect a customer in AI contact; capture feedback through mechanisms that reach the people the tool failed; and close the loop by telling users what changed.
Capabilities
What you'll be able to do
distinguish genuine employee experience applications from surveillance
design the controls that protect a customer in AI contact
capture feedback through mechanisms that reach the people the tool failed
and close the loop by telling users what changed.
How you will learn
Learn. Practice. Prove.
Learn
Short, evidence-led lessons establish the standard and the reasoning behind it.
Practice
Interactive decisions, sorting and scenarios turn concepts into applied judgement.
Prove
A cumulative final exam checks mastery, followed by a spoken capstone.
Inside this courseApplied scenariosCard sortingMatching exercisesPriority rankingConfidence checksReflection journal
Curriculum
A concise view of the complete course.
AI in customer experience
How to diagnose a fall in customer satisfaction after an AI deployment before acting on it, and how to demonstrate a genuine improvement in customer experience with before-and-after evidence rather than activity counts.
AI in employee experience
What distinguishes a genuine employee experience application from surveillance presented as one, why the test is who receives the output, and how co-design turns a tool staff tolerate into one they use.
Automation with human oversight and escalation
The combination of controls an AI system handling customer contact must have, why disclosure and a working human route are protections rather than niceties, and when automating a customer interaction is least appropriate.
Feedback capture
Why a single feedback mechanism gives a biased picture, how combining in-the-moment and periodic mechanisms captures both what and why, and the sampling problem that flatters AI tool feedback specifically.
Closed-loop improvement
What distinguishes a closed feedback loop from feedback collection, how to turn feedback themes into the right improvement, and why recurring themes signal a loop that collects but does not act.
Ready when you are