Course Outline
Prerequisites
No prior technical expertise is mandatory. Familiarity with AI interfaces, such as ChatGPT or Microsoft Copilot, is advantageous but not a requirement.
Target Audience
- Supervisors and Mid-level Management
- Project and Product Managers
- Department Heads (Operations, Client Services, Sales)
- HR Business Partners (Recommended)
Introduction: Human Elements in AI Integration
- Reasons for implementation failure in operational teams: Behavioral dynamics outweigh tool limitations
- Trust Management: Balancing under-utilization against over-reliance (automation bias)
- Responsibility Framework: AI serves as an aid; human accountability remains absolute
1. Calibrated Dependence (Secure Daily Operations)
- Scope of Application: Determining appropriate and prohibited uses for AI
- Control Measures: Protocols for pausing, validating, or escalating tasks
- Identification of common operational failures and early indicators
2. Validation Standards (Ensuring Quality without Efficiency Loss)
- Operational Verification Tiers (Basic, Standard, Rigorous)
- Indicators of Risk: Hallucinations, obsolete data, lack of citation, and sensitive data exposure
- Source Verification and Traceability: Fundamental documentation practices
3. Accountability and Decision Integrity
- Responsibility Assignment: Defining roles for validation, decision-making, and final approval
- Escalation Criteria and Decision Thresholds
- Decision Record: Minimum requirements for evidence and documentation
4. Team Consensus Workshop (Primary Output)
- Structure of Operational Agreements: Trigger, Response, Evidence, Responsible Party, Consequence
- Application to Standard Workflows (Correspondence, Analysis, Client Communications, Internal Records)
- Alignment with organizational policies and confidentiality standards
5. Trust and Psychological Security
- Addressing Core Concerns: Job displacement, competence erosion, and status changes
- Managerial Communication Strategies: Discussing AI with balance and clarity
- Mitigating Polarization: Resolving tensions between AI proponents and skeptics
6. Basic Incident Management (AI Errors and Near-Misses)
- Impact Classification: Low, Moderate, High
- Mitigation and Communication: Internal procedures and external client notifications
- Continuous Improvement: Refining agreements, templates, and standard practices
7. 30-Day Implementation Plan
- Operational Rhythms: Weekly status reviews, prompt auditing, incident analysis, and decision checks
- Key Performance Indicators: Adoption quality, rework rates, escalation frequency, and trust metrics
- Follow-up Strategy and Next Steps
Requirements
- Basic familiarity with standard workplace workflows (email, documentation, meetings).
- Advantageous (not required): Prior exposure to AI tools such as ChatGPT or Microsoft Copilot
Target Audience
- Supervisors and Mid-level Management
- Project and Product Managers
- Department Heads (Operations, Client Services, 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
the exercises and the way the trainer was explaining
Sorana Haiduc - Ness
Course - Stress Management and Prevention
1. Methodology 2. Its structure and usability 3. Real, practical examples and excercises