01
Create one quality language
Connect what supervisors define, what AI monitors and what agents experience.
← Alipta BallavLeadership
02
Microsoft · Dynamics 365 Contact Center · 2025–2026
Transforming Quality Management with AI
A continuous system that turns quality standards into guidance while the agent can still improve the interaction.
Business goal
Improve quality during every conversation
My role
Product and design leadership
Design shift
Retrospective scoring → active guidance
Evidence
Evaluation plan + live coaching experience
01 · Business problem
Quality arrived after the moment had passed.
Post-call scoring created evidence, but agents could not correct missed empathy cues or compliance risks while a customer was still present.
02 · Design challenge
Turn standards into proportionate intervention.
The experience had to improve behavior without overwhelming agents or turning quality management into surveillance.
Goal
Improve interaction quality
Friction
Delayed feedback · manual review
Design
Transparent, proportional coaching
Outcome
Act before the conversation ends
03 · Key decisions
Design the operating model, not only the prompt.
02
Intervene proportionately
Indicators invite coaching; guardrail breaches trigger mandatory guidance.
03
Close the loop
Feed coaching outcomes back into evaluation plans and supervisor review.
04 · Product evidence
One plan. Two levels of intervention.
A supervisor defines an empathy indicator and a financial-advice guardrail. During the call, the system responds according to risk.
Indicator · contextual nudge
Improve the interaction.
Missed empathy cue → acknowledge the customer’s frustration.
Guardrail · mandatory alert
Stop unsafe behavior.
Financial advice detected → enforced guidance tells the agent to stop.
05 · Outcome and evidence
Quality becomes actionable.
These are directional product benefits; no unsupported performance metric is claimed.
Evidence
Define → Improve
A complete quality-management loop
Evidence
2 modes
Contextual nudges and mandatory alerts
Intended impact
Earlier action
Agents adjust before the interaction ends
Intended impact
More leverage
Supervisors focus on patterns and development
06 · Leadership takeaway
Trust requires visible boundaries.
“AI coaching earns trust when teams can see what triggers it, why it intervenes and where human judgment remains.”