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 Duration 7 hours (1 days)

Course Outline

Prerequisites

No technical background is required. It is beneficial (but not required) to have basic familiarity with AI tools such as ChatGPT or Microsoft Copilot.

Target Audience

  • Team Leaders and Middle Managers
  • Project and Product Managers
  • Function Heads (Operations, Customer Service, Sales)
  • HR Business Partners (optional)

Introduction (Human Dynamics in AI Adoption)

  • Why AI adoption fails in real teams: It is driven by human factors, not just the tools.
  • Calibrating trust: Avoiding under-reliance and over-reliance (automation bias).
  • Accountability: AI can support, but humans remain responsible.

1. Calibrated Reliance (Safe Usage in Daily Operations)

  • Use-case boundaries: Determining what is suitable for AI and what is not.
  • Stopping criteria: When to pause, verify, or escalate.
  • Common failure patterns and early warning indicators.

2. Verification Criteria (Ensuring Quality Without Delay)

  • Practical verification levels (light, standard, strict).
  • Red flags: Hallucinations, outdated facts, missing sources, and sensitive content.
  • “Second source” validation and traceability fundamentals (what to document).

3. Accountability and Decision Discipline

  • Ownership: Identifying who validates, who decides, and who approves.
  • Escalation triggers and decision thresholds.
  • Decision logging: Minimum evidence and documentation requirements.

4. Team Agreement Workshop (Core Outcome)

  • Structuring working agreements: Trigger, action, evidence, owner, consequence.
  • Examples for common workflows (emails, analysis, customer communications, internal documents).
  • Aligning agreements with corporate policy and confidentiality requirements.

5. Trust and Psychological Safety

  • Common concerns: Job displacement, loss of competence, or status.
  • Manager scripts: Discussing AI without hype or panic.
  • Managing conflict: Navigating “pro-AI” vs. “anti-AI” viewpoints to reduce polarization.

6. Lightweight Incident Response (AI Errors and Near-Misses)

  • Classifying incidents: Low, medium, or high impact.
  • Containing and communicating (internally and to customers when necessary).
  • Learning loop: Updating agreements, templates, and rituals.

7. 30-Day Adoption Plan

  • Team rituals: Weekly check-ins, prompt reviews, incident reviews, and decision reviews.
  • Key metrics: Adoption quality, rework rates, escalations, and trust indicators.
  • Next steps and follow-up strategy.

Requirements

  • Basic understanding of standard workplace workflows (email, documentation, meetings).
  • Beneficial (but not mandatory): Previous experience with AI tools such as ChatGPT or Microsoft Copilot.

Target Audience

  • Team Leaders and Middle Managers
  • Project and Product Managers
  • Function Heads (Operations, Customer Service, Sales) 
  • HR Business Partners

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