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Course Outline

Prerequisites

No technical background is required. Helpful (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)

  • Understanding why AI adoption fails in real-world teams: human factors outweigh tool capabilities.
  • Trust calibration: addressing under-reliance vs. over-reliance (automation bias).
  • Accountability: reinforcing the principle that “AI assists, but humans remain responsible.”

1. Calibrated Reliance (Safe Use in Daily Work)

  • Use-case boundaries: identifying appropriate versus inappropriate AI applications.
  • Stop rules: knowing when to pause, verify, or escalate.
  • Recognizing common failure patterns and early warning signs.

2. Verification Standards (Maintaining Quality Without Slowing Down)

  • Implementing practical verification levels (light, standard, strict).
  • Identifying red flags: hallucinations, outdated facts, missing sources, sensitive content.
  • Understanding “second source” concepts and traceability basics (what needs to be logged).

3. Accountability and Decision Hygiene

  • Ownership: clarifying who validates, decides, and signs off.
  • Defining escalation triggers and decision thresholds.
  • Maintaining a decision log: establishing minimum evidence and documentation standards.

4. Team Agreements Workshop (Core Deliverable)

  • Structure of the working agreement: trigger, action, evidence, owner, consequence.
  • Examples for common workflows (emails, analysis, customer communications, internal documents).
  • 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: discussing AI without hype or panic.
  • Navigating conflict patterns: managing “pro-AI” vs. “anti-AI” dynamics to reduce polarization.

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

  • Classifying incidents by impact (low, medium, high).
  • Containment and communication strategies (internal updates and customer notifications as needed).
  • The learning loop: updating agreements, templates, and rituals based on insights.

7. 30-Day Adoption Plan

  • Establishing team rituals: weekly check-ins, prompt reviews, incident reviews, decision reviews.
  • Tracking meaningful metrics: adoption quality, rework rates, escalations, and trust indicators.
  • Defining next steps and follow-up plans.

Requirements

  • Basic familiarity with standard workplace workflows (email, documents, meetings).
  • Helpful (not mandatory): prior experience 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
 7 Hours

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