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 Duration 7 hours (1 days)

Course Outline

Prerequisites

No technical background is necessary. It is helpful (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.
  • Heads of Departments (Operations, Customer Service, Sales).
  • HR Business Partners (optional).

Introduction (Human Factors in AI Adoption)

  • Why AI adoption often fails in real-world teams: it is about human factors, not just tools.
  • Calibrating trust: avoiding under-reliance and over-reliance (addressing automation bias).
  • Accountability: reinforcing that "AI can assist, but humans remain responsible."

1. Calibrated Reliance (Safe Usage in Daily Operations)

  • Use-case boundaries: identifying what is suitable for AI and what is not.
  • Stop rules: knowing when to pause, verify, or escalate.
  • Common failure patterns and early warning signs.

2. Verification Standards (Quality Assurance Without Delays)

  • Practical verification levels (light, standard, strict).
  • Red flags: detecting hallucinations, outdated facts, missing sources, or sensitive content.
  • Basics of "second source" verification and traceability (what to document).

3. Accountability and Decision Hygiene

  • Ownership: clarifying who validates, who decides, and who signs off.
  • Escalation triggers and decision thresholds.
  • Decision logs: requirements for minimum evidence and documentation.

4. Team Agreements Workshop (Key Deliverable)

  • Structure of working agreements: trigger, action, evidence, owner, and consequence.
  • Examples for common workflows (emails, analysis, customer communications, internal documentation).
  • Aligning agreements with corporate policy and confidentiality rules.

5. Trust and Psychological Safety

  • Addressing common fears: job replacement, loss of competence, or loss of status.
  • Managerial scripts: how to discuss AI without hype or causing panic.
  • Navigating conflict patterns: managing "pro-AI" vs. "anti-AI" sentiments and de-polarizing the team.

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

  • Categorizing incidents: low, medium, and high impact.
  • Containing and communicating (internally and with customers as necessary).
  • Continuous 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

  • A 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.
  • Heads of Departments (Operations, Customer Service, Sales). 
  • HR Business Partners.

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