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Course Outline

Prerequisites

No technical background is required. However, it is beneficial (though not mandatory) to have a basic familiarity with AI tools such as ChatGPT or Microsoft Copilot.

Audience

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

Introduction (Human Factors in AI Adoption)

  • Why AI adoption falters in real teams: the role of human factors rather than tool limitations.
  • Trust calibration: navigating under-reliance versus over-reliance (automation bias).
  • Accountability: understanding that while AI can assist, humans remain ultimately responsible.

1. Calibrated Reliance (Safe Use in Daily Work)

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

2. Verification Standards (Maintaining Quality Without Slowing Down)

  • Practical verification tiers (light, standard, strict).
  • Red flags: identifying hallucinations, outdated facts, missing sources, and sensitive content.
  • The importance of a "second source" and traceability basics (what to document).

3. Accountability and Decision Hygiene

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

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 documents).
  • Aligning agreements with company policy and confidentiality regulations.

5. Trust and Psychological Safety

  • Addressing typical fears: replacement anxiety, loss of competence, and status concerns.
  • Manager scripts: discussing AI effectively without hype or panic.
  • Managing conflict patterns between "pro-AI" and "anti-AI" factions to reduce polarization.

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

  • Classifying incidents by impact level: low, medium, or high.
  • Containment and communication strategies (internally and with customers when necessary).
  • The learning loop: updating agreements, templates, and rituals based on learnings.

7. 30-Day Adoption Plan

  • Team rituals: weekly check-ins, prompt reviews, incident reviews, and decision reviews.
  • Key metrics: adoption quality, rework rates, escalation frequency, and trust indicators.
  • Defining next steps and establishing a follow-up plan.

Requirements

  • A basic understanding of everyday workplace workflows (email, documents, meetings).
  • Beneficial but not essential: previous exposure to AI tools such as ChatGPT or Microsoft Copilot.

Audience

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

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