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Course Outline

Prerequisites

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

Audience

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

Introduction: Human Factors in AI Adoption

  • Understanding why AI adoption fails in real teams: focusing on human factors rather than tools.
  • Trust calibration: balancing under-reliance versus over-reliance (automation bias).
  • Accountability principles: "AI assists, but humans remain responsible."

1. Calibrated Reliance: Safe Usage in Daily Work

  • Defining use-case boundaries: determining what is and isn't suitable for AI.
  • Establishing 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

  • Applying practical verification levels (light, standard, strict).
  • Identifying red flags: hallucinations, outdated facts, missing sources, and sensitive content.
  • Implementing "second source" checks and understanding traceability basics (documentation requirements).

3. Accountability and Decision Hygiene

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

4. Team Agreements Workshop (Core Deliverable)

  • Structuring working agreements: triggers, actions, evidence, owners, and consequences.
  • Reviewing examples for common workflows (emails, analysis, customer communications, internal documents).
  • Aligning team agreements with company policy and confidentiality regulations.

5. Trust and Psychological Safety

  • Addressing common fears: replacement anxiety, loss of competence, and loss of status.
  • Manager scripts: techniques for discussing AI without hype or panic.
  • Navigating conflict patterns: bridging the gap between "pro-AI" and "anti-AI" perspectives to reduce polarization.

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

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

7. 30-Day Adoption Plan

  • Implementing team rituals: weekly check-ins, prompt reviews, incident analysis, and decision reviews.
  • Tracking meaningful metrics: adoption quality, rework rates, escalation frequency, and trust indicators.
  • Defining next steps and the follow-up plan.

Requirements

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

Audience

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

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