Course Outline
Prerequisites
No technical background is necessary. It is helpful (but not required) to have basic familiarity with AI tools like 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: the role of human factors rather than tool limitations.
- Calibrating trust: balancing under-reliance and over-reliance (mitigating automation bias).
- Clarifying accountability: while AI can assist, humans remain ultimately responsible.
1. Calibrated Reliance (Safe Integration into Daily Work)
- Use-case boundaries: distinguishing what is appropriate for AI and what is not.
- Stop rules: knowing when to pause, verify, or escalate.
- Identifying common failure patterns and early warning signs.
2. Verification Standards (Ensuring Quality Without Delays)
- Practical verification levels (light, standard, and strict protocols).
- Recognizing red flags: hallucinations, outdated facts, missing sources, and sensitive content issues.
- “Second source” verification and traceability basics (what needs to be logged).
3. Accountability and Decision Hygiene
- Ownership: defining who validates, who decides, and who signs off.
- Setting escalation triggers and decision thresholds.
- Decision logging: minimum requirements for evidence and documentation.
4. Team Agreements Workshop (Core Deliverable)
- Structuring working agreements: triggers, actions, evidence, owners, and consequences.
- Examples for common workflows (emails, data analysis, customer communications, and internal documentation).
- Aligning team agreements with company policies and confidentiality rules.
5. Trust and Psychological Safety
- Addressing typical fears: job replacement, loss of competence, and loss of status.
- Manager scripts: communicating about AI without hype or causing panic.
- Managing conflict patterns: resolving “pro-AI” vs. “anti-AI” stances and reducing polarization.
6. Light Incident Response (Handling AI Errors and Near-Misses)
- Classifying incidents by impact: low, medium, and high.
- Containment and communication strategies (internal and, when necessary, with customers).
- The learning loop: updating agreements, templates, and team rituals based on incidents.
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.
- Defining next steps and the follow-up plan.
Requirements
- Fundamental familiarity with daily workplace workflows (such as email, documentation, and meetings).
- Beneficial (but not mandatory): previous experience with AI tools like 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.
Testimonials (3)
Provided and explained very clearly a lot of foundational concepts, which fit well with the team's level of learning. The exercises were very engaging and I believe my team were comfortable and participated very well. Coordinating with the trainer as well was very seamless.
Christlan Tolentino - Canadian Blood Services
Course - Critical Thinking
the exercises and the way the trainer was explaining
Sorana Haiduc - Ness
Course - Stress Management and Prevention
SMART Goal session was the most enjoyable part of the training that helped me manage my time properly. it helps me set my goal clearer and i could really see that setting SMART Goal can relate to almost everything such as Finance, Social Life, Career and Personal Growth.
