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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
 7 Hours

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