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- Identifying red flags: hallucinations, outdated facts, missing sources, and sensitive content.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
Testimonials (4)
Meeting efficiency is something that's fairly "basic", but not thought about a lot and with really large implications on people/company time. Understanding these best practices and keeping them top-of-mind will be of immediate help.
Dan Moffatt - Chris Courtemanche
Course - Personal Efficiency and Managing Meetings
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
I especially appreciated the instructor’s ability to give thorough, well-explained answers to questions specific to my personal situation.
HASAN TAHA URLU - Huber Turkiye
Course - Assertiveness
the exercises and the way the trainer was explaining