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Course Outline

Prerequisites

No technical background is required. Helpful (though not mandatory): basic familiarity with AI tools such as ChatGPT or Microsoft Copilot.

Audience

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

Introduction (Human Factors in AI Adoption)

  • Why AI adoption often fails in real teams: human factors outweigh tool capabilities.
  • Trust calibration: balancing under-reliance versus over-reliance (automation bias).
  • Accountability: understanding that "AI can assist, but humans remain responsible."

1. Calibrated Reliance (Safe Use in Daily Work)

  • Use-case boundaries: determining what is and isn't appropriate for AI.
  • Stop rules: knowing when to pause, verify, or escalate.
  • Recognizing common failure patterns and early warning signs.

2. Verification Standards (Quality Without Slowdowns)

  • Practical verification levels (light, standard, strict).
  • Red flags: hallucinations, outdated facts, missing sources, and sensitive content.
  • The "Second source" concept and traceability basics (what needs to be logged).

3. Accountability and Decision Hygiene

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

4. Team Agreements Workshop (Core Deliverable)

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

5. Trust and Psychological Safety

  • Addressing typical fears: replacement, loss of competence, and loss of status.
  • Manager scripts: how to discuss AI without hype or panic.
  • Handling conflict patterns: navigating "pro-AI" versus "anti-AI" dynamics and de-polarizing discussions.

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

  • Classifying incidents: low, medium, or high impact.
  • Containment and communication strategies (internal and with customers when necessary).
  • Learning loop: updating agreements, templates, and rituals based on lessons learned.

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 planning.

Requirements

  • Basic familiarity with everyday workplace workflows (email, documents, meetings).
  • Beneficial but not mandatory: prior exposure to AI tools such as ChatGPT or Microsoft Copilot.

Audience

  • Team Leaders and Middle Managers
  • Project / Product Managers
  • Heads of Functions (Operations, Customer Service, Sales)
  • HR Business Partners
 7 Hours

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