Course Outline
Prerequisites
No technical background is required. However, a basic familiarity with AI tools such as ChatGPT or Microsoft Copilot may be beneficial but is not mandatory.
Audience
- Team Leaders and Middle Managers
- Project and Product Managers
- Heads of Functions (Operations, Customer Service, Sales)
- HR Business Partners (optional)
Introduction (Human Factors in AI Adoption)
- Why AI adoption often fails in real teams: human factors are more critical than the tools themselves.
- Trust calibration: addressing under-reliance and over-reliance (automation bias).
- Accountability: ensuring that while AI can assist, humans remain ultimately responsible for decisions and actions.
1. Calibrated Reliance (Safe Use in Daily Work)
- Defining use-case boundaries: identifying what tasks are appropriate for AI and which are not.
- Stop rules: guidelines for when to pause, verify, or escalate a task involving AI.
- Common failure patterns and early warning signs to watch for in AI-assisted work.
2. Verification Standards (Quality Without Slowdowns)
- Establishing practical verification levels: light, standard, and strict.
- Identifying red flags such as hallucinations, outdated facts, missing sources, and sensitive content.
- Basics of “second source” verification and traceability requirements (what to log).
3. Accountability and Decision Hygiene
- Clarifying ownership: determining who validates, decides, and signs off on AI-assisted tasks.
- Setting escalation triggers and decision thresholds to ensure appropriate oversight.
- Maintaining a decision log with minimum evidence and documentation standards.
4. Team Agreements Workshop (Core Deliverable)
- Structure of working agreements: trigger, action, evidence, owner, and consequence.
- Examples for common workflows such as emails, analysis, customer communications, and internal documents.
- Aligning team agreements with company policy and confidentiality rules to ensure compliance.
5. Trust and Psychological Safety
- Addressing typical fears: job replacement, loss of competence, and loss of status.
- Manager scripts for discussing AI in a balanced manner without hype or panic.
- Recognizing and addressing conflict patterns between “pro-AI” and “anti-AI” team members to de-polarize the discussion.
6. Light Incident Response (AI Mistakes and Near-Misses)
- Classifying incidents by impact level: low, medium, high.
- Procedures for containing and communicating incidents internally and with customers when necessary.
- Establishing a learning loop to update team agreements, templates, and rituals based on incident reviews.
7. 30-Day Adoption Plan
- Team rituals: weekly check-ins, prompt reviews, incident reviews, and decision reviews.
- Key metrics to monitor: adoption quality, rework rates, escalation frequency, and trust indicators.
- Next steps and a follow-up plan for continuous improvement in AI integration for government operations.
Requirements
- Basic understanding of standard workplace processes (email, documents, meetings).
- Prior experience with AI tools such as ChatGPT or Microsoft Copilot is beneficial but not required.
Audience for Government
- Team Leaders and Middle Managers
- Project and Product Managers
- Department Heads (Operations, Customer Service, Sales)
- Human Resources Business Partners
Testimonials (4)
The connection with the trainer and the people.
Cristiana Dragoescu - Ness
Course - Stress Management and Prevention
Body scan
Piotr Chwiedziewicz - Grupa OLX
Course - Mindfulness for Business Professionals
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.
Manot Sae - MVCI (Thailand) Limited
Course - Workshop: Boost your productivity with this new method!
Relevance of the training and the reflection of behaviours already observed in others and myself.
