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Intermediate CoursePart of AI Operator

AI Transformation & KPIs

Redesign how your organization works alongside AI. Over three weeks, you will audit legacy processes for automation opportunities, design an executive KPI dashboard for AI operations, and deliver a full 30-day change management and adoption playbook.

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3 weeks

What You'll Learn

Audit legacy workflows to locate automation bottlenecks and redesign SOPs for the hybrid workforce
Distinguish tasks requiring human empathy from those suitable for autonomous execution
Design operational KPIs that measure system latency, error rates, and API throughput
Quantify efficiency gains through automated resolution rates and human time saved
Build a 30-day AI rollout playbook with phased deployment and an AI Champion program

Course Content

W1
Week 1: Process Mapping for the Hybrid Workforce
Locate exactly where AI should replace, augment, or defer to human judgment.
1
Systemic Limits
Understanding the physical limits of manual, legacy processes in data-dense environments and where they create the highest cost.
2
The Accountability Gap
Balancing agentic autonomy with necessary human skill retention to avoid creating organizational dependencies on fragile AI systems.
3
Process Auditing
Dissecting legacy workflows step-by-step to locate bottlenecks, handoffs, and repetitive tasks suitable for AI automation.
4
Empathy vs. Execution
Determining which tasks strictly require human empathy, ethical judgment, or relationship context — and which can be safely automated.
Weekly Win
SOP Redesign
Deliver a redesigned standard operating procedure for one legacy process, mapping each step to either an AI agent or a human owner.
W2
Week 2: AI KPI Design & Measurement
Replace vanity metrics with operational data that proves AI is working.
1
Rejecting Vanity Metrics
Understanding why basic usage counts and prompt volumes fail to measure true operational success or business impact.
2
Operational Metrics
Tracking critical indicators including system latency, error rates, API throughput, and queue depth for AI infrastructure health.
3
Efficiency KPIs
Quantifying automated resolution rates, ticket deflection, and exact human hours reclaimed through AI task offloading.
4
Continuous Quality Measurement
Utilizing online evaluations for ongoing monitoring of output sentiment, accuracy drift, and model degradation in production.
Weekly Win
KPI Dashboard
Design and present a comprehensive executive reporting interface that tracks real-time AI operational health, efficiency, and output quality.
W3
Week 3: Change Management & Adoption
Turn skeptical employees into AI champions through structured rollout design.
1
Navigating AI Fatigue
Understanding and systematically mitigating the employee resistance and fear that derails AI adoption programs.
2
Competency Mapping
Utilizing skill matrices to identify capability gaps and design targeted reskilling paths for roles affected by automation.
3
The RACI Framework
Formalizing governance, accountability, and multi-departmental coordination across AI owners, operators, and reviewers.
4
Rollout Playbooks
Designing phased deployment plans — pilot, expand, scale — to maximize early wins and organizational adoption momentum.
Weekly Win
30-Day Playbook
Draft a complete 30-day AI rollout playbook including internal communications calendar, training schedule, and an AI Champion program framework.

Prerequisites

Leadership or management experience
Understanding of business strategy

Tools You'll Use

ClaudeClaude
ChatGPTChatGPT
NotionNotion
Power BIPower BI
SlackSlack
Microsoft TeamsMicrosoft Teams
📚
Intermediate Level
Course Price
₹6,999
India
$149
International · One-time payment
Next cohort starts Mar 30
Duration3 weeks
LevelIntermediate
FormatCohort-based
Modules3

What's included:

Live cohort sessions
Hands-on projects
Certificate of completion
Lifetime access
Career support

Part of Learning Track

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AI Operator
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