Mastering AI-Driven Strategy for Interim Leaders
You’ve been brought in to stabilise, steer, or transform-fast. The clock is ticking, stakeholders are watching, and your credibility hinges on delivering clarity in chaos. Yet AI strategy feels like a moving target: overhyped, underdefined, and disconnected from the urgent realities of interim leadership. What if you could cut through the noise and deploy AI with precision-not as a tech experiment, but as a board-level lever for performance, transition, and measurable impact? What if you had a proven framework to diagnose organisational readiness, align executives, and launch AI initiatives that deliver visible results within weeks, not quarters? Mastering AI-Driven Strategy for Interim Leaders gives you that framework. It’s the first structured methodology designed specifically for interim executives who need to establish authority, drive change, and exit with documented wins-all while future-proofing the organisation. You’ll go from concept to funded, board-ready AI strategy in 30 days. One recent alum, a CFO stepping into a distressed manufacturing firm, used the course’s diagnostic toolkit to identify an AI use case in supply chain forecasting. Within 25 days, she secured board approval and a six-figure pilot budget. Her comment: “This wasn’t just strategy-it was currency. It bought me trust, time, and influence.” No theoretical fluff. No tech jargon. Just repeatable, field-tested processes that help you make smart, fast decisions under pressure-without needing a data science degree. The tools are in your hands. The timeline is aggressive. The stakes couldn’t be higher. Here’s how this course is structured to help you get there.Course Format & Delivery Details Self-Paced, Immediate Online Access – No Fixed Timelines
This course is designed for your reality: unpredictable schedules, global time zones, and high-pressure transitions. There are no fixed start dates, no live sessions, and no time-based commitments. Enrol at any time, access all materials on demand, and progress at your pace-from hotel rooms, boardrooms, or remote locations. Most interim leaders complete the core modules in 15–20 hours, with tangible outputs achievable within 10 days of starting. You can implement key tools immediately, even before finishing the full curriculum. Lifetime Access & Future Updates Included
Once enrolled, you have permanent access to all course content. This includes all future updates, refinements, and new AI strategy templates as the landscape evolves-delivered at no extra cost. Your investment grows in value over time. Global, Mobile-Friendly Access 24/7
Access the full course from any device-laptop, tablet, or smartphone. Whether you’re offline during a flight or checking in from a client site, your progress is synced and available whenever you are. The platform is optimised for quick retrieval, note-taking, and offline use. Direct Instructor Guidance & Expert Support
You’re not on your own. Receive structured feedback and strategic guidance via dedicated support channels. Submit your AI strategy drafts, governance models, or stakeholder alignment plans for expert review and actionable input from practitioners who’ve led real interim AI transitions across industries. Certificate of Completion – Globally Recognised Credibility
Upon completion, you will earn a Certificate of Completion issued by The Art of Service. This credential is recognised by global enterprises, consulting firms, and executive boards as evidence of applied strategic competence in digital transformation. It validates your ability to lead AI adoption in high-stakes, time-bound leadership roles. Transparent, One-Time Pricing – No Hidden Fees
The course fee is straightforward, with no recurring charges, upsells, or add-ons. What you see is what you pay-no surprises. We accept Visa, Mastercard, and PayPal for secure, instant processing. 100% Money-Back Guarantee – Zero Risk
If you complete the first two modules and find the content isn’t delivering clear value, you’re fully covered by our satisfaction guarantee. Request a refund, no questions asked. Your risk is eliminated-your upside, exponential. Enrolment & Access Process – Clarity and Confirmation
After enrolment, you’ll receive a confirmation email summarising your registration. Your access details and login instructions will be sent separately once your course materials are fully configured. This ensures a seamless, error-free onboarding experience. “Will This Work for Me?” – Relentless Relevance
You’re not a full-time AI specialist. You’re a leader under pressure. That’s why this course works even if: - You have no prior experience with machine learning or data architecture
- You’re stepping into an organisation with low AI maturity or conflicting priorities
- You only have 90 days-or less-to make an impact
- Technical teams have resisted past initiatives
- Board members demand ROI but lack technical understanding
This is not about becoming an AI expert. It’s about becoming the decisive leader who unlocks AI’s value when it matters most. Real interim CIOs, turnaround CEOs, and integration directors have used this methodology to secure budget, build cross-functional alignment, and launch pilots that outlast their tenure. The process is battle-tested, role-specific, and outcome-driven. With lifetime access, expert support, verified outcomes, and zero financial risk-you’re not buying a course. You’re acquiring a strategic advantage.
Module 1: Foundations of AI in Interim Leadership - Defining AI’s Role in Crisis, Transition, and Transformation
- Why Interim Leaders Are Uniquely Positioned to Drive AI Adoption
- Common Myths and Misconceptions About AI in Leadership
- Aligning AI Strategy with Interim Mandates: Stabilise, Improve, or Exit
- Understanding the AI Maturity Spectrum Across Organisations
- Key Differences Between Permanent and Interim AI Leadership Approaches
- The Ethics and Governance Imperatives for Short-Term AI Deployment
- Assessing Risk Tolerance in AI Initiatives During Transitions
- How to Prioritise AI Use Cases for Maximum Visibility and Impact
- Recognising Organisational Resistance to AI and How to Address It
- Establishing Credibility as an AI-Savvy Interim Leader
- The Interim Leader’s Role in Bridging Technical and Executive Gaps
- Mapping AI Levers to Immediate Business KPIs
- Defining Success Metrics for AI in a 60- to 100-Day Framework
- Creating Alignment Between Board Expectations and AI Feasibility
- Balancing Speed, Accuracy, and Sustainability in AI Planning
Module 2: Strategic Frameworks for AI Integration - The 4-Pillar Interim AI Strategy Model: Assess, Align, Activate, Amplify
- Applying McKinsey 7-S Framework to AI Readiness Assessment
- Using the AI Value Chain to Identify Quick Wins
- Implementing the RAPID Decision-Making Framework for AI Governance
- Leveraging SWOT Analysis for AI Opportunity Mapping
- Integrating AI into Existing Transformation Roadmaps
- Building a Time-Bound AI Strategy Canvas
- Deploying the Eisenhower Matrix to Prioritise AI Initiatives
- Using the Cynefin Framework to Classify AI Problems
- Mapping AI Solutions to Organisational Complexity Levels
- Applying Kotter’s 8-Step Model to AI Change Management
- Designing AI Pilots Using Lean Startup Principles
- Creating a 30-60-90 Day AI Action Plan Template
- Aligning AI Strategy with Culture, Leadership, and Structure
- Developing an AI Communication Strategy for Stakeholder Buy-In
- Using Scenario Planning to Evaluate AI Outcomes Under Uncertainty
Module 3: Diagnostic Tools for Organisational AI Readiness - Conducting a 72-Hour AI Readiness Diagnostic
- Assessing Data Infrastructure Maturity and Gaps
- Evaluating Technical Team Capabilities and Bandwidth
- Measuring Executive Understanding of AI Concepts
- Identifying Silent Allies and Hidden Blockers in the Organisational Network
- Using Pulse Surveys to Gauge AI Sentiment
- Analysing Past AI or Digital Initiatives for Lessons Learned
- Mapping Data Silos and Integration Feasibility
- Conducting Stakeholder Power-Interest Grids for AI Projects
- Assessing Legal and Compliance Risks in AI Deployment
- Reviewing Procurement and Vendor Readiness for AI Tools
- Diagnosing Change Fatigue and Its Impact on AI Adoption
- Creating a Readiness Heatmap for Immediate Use
- Prioritising Departments Based on AI Opportunity Density
- Conducting Cross-Functional AI Capability Workshops
- Using the ADKAR Model to Assess Individual AI Readiness
Module 4: Identifying and Validating High-Impact AI Use Cases - Generating AI Use Case Ideas Using the Jobs to Be Done Framework
- Clustering Ideas by Operational, Financial, and Strategic Impact
- Scoring Use Cases Using the AI ROI Matrix
- Validating Feasibility with the TECH-C Filter (Time, Expertise, Cost, Hardware, Culture)
- Assessing Data Availability and Quality for Each Use Case
- Estimating Implementation Effort Using the T-Shirt Sizing Method
- Calculating Expected Time-to-Value for Each Initiative
- Aligning Use Cases with Immediate Business Objectives
- Avoiding Common Pitfalls in AI Use Case Selection
- Launching Micro-Pilots to Test Assumptions Early
- Engaging Subject Matter Experts in Use Case Refinement
- Using Process Mining to Discover Hidden AI Opportunities
- Analysing Invoice, HR, and Supply Chain Data for Automation Potential
- Identifying Repetitive Tasks Ideal for RPA + AI Integration
- Evaluating Customer Journey Pain Points for AI Intervention
- Building a Use Case Portfolio for Board Presentation
Module 5: Building the Board-Ready AI Proposal - Structuring a 1-Page AI Executive Brief
- Writing the Problem Statement with Business Context
- Defining the AI Solution in Non-Technical Terms
- Quantifying Financial Impact with Conservative, Base, and Optimistic Scenarios
- Estimating Implementation Costs and Resource Needs
- Projecting Payback Period and NPV for AI Investments
- Incorporating Risk Mitigation Strategies into the Proposal
- Designing a Phased Rollout Plan for Incremental Wins
- Creating Governance and Oversight Mechanisms
- Defining Success Metrics and KPIs for Tracking
- Anticipating and Pre-Empting Executive Objections
- Using Visuals and Analogies to Communicate AI Value
- Incorporating Testimonials and Precedent from Similar Industries
- Aligning the Proposal with ESG and Digital Transformation Goals
- Obtaining Pre-Approval Signals from Key Stakeholders
- Rehearsing the Presentation with Feedback Loops
Module 6: Securing Stakeholder Alignment and Funding - Identifying All Critical Decision Makers and Influencers
- Tailoring Communication Styles to Different Executive Personalities
- Using Pre-Meetings to Build Consensus Before Formal Reviews
- Creating Variant Proposal Versions for Finance, Ops, and Legal
- Hosting Cross-Functional AI Vision Workshops
- Developing a Compelling Narrative with a Clear Before-After-Bridge
- Leveraging Pilot Wins to Build Momentum and Expand Budget
- Using the SCARF Model to Reduce Threat Response in Teams
- Engaging Internal Champions to Co-Own the Initiative
- Negotiating Resource Allocation Without Permanent Headcount
- Designing a Funding Request with Contingency and Flexibility
- Presenting to the Board Using the Pyramid Principle
- Securing Conditional Approval and Fast-Track Pilots
- Building a Coalition of Support Across Departments
- Using Social Proof from Peer Organisations
- Handling “Not Invented Here” Resistance with Diplomacy
Module 7: Designing and Launching AI Pilots - Selecting the Right Pilot Team with Hybrid Skills
- Defining Clear Inclusion and Exclusion Criteria
- Establishing Baseline Metrics Before Launch
- Setting Up Data Collection and Monitoring Protocols
- Designing Control Groups for Accurate Impact Measurement
- Simplifying AI Models for Rapid Iteration
- Using MVP Principles to Minimise Time-to-Insight
- Running Daily Stand-Ups Without Disrupting Core Operations
- Managing Vendor Relationships for AI Tools
- Creating a Pilot Dashboard for Real-Time Oversight
- Handling Data Privacy and Anonymisation Requirements
- Documenting Assumptions, Decisions, and Deviations
- Running Mid-Pilot Check-Ins with Stakeholders
- Preparing for Scalability from Day One
- Using Feedback Loops to Improve Model Performance
- Deciding When to Pivot, Pause, or Proceed
Module 8: Measuring, Communicating, and Scaling Results - Calculating Actual vs. Predicted ROI from Pilots
- Identifying Secondary Benefits of AI Deployment
- Creating a Results Report for Executive Summaries
- Designing Infographics and Dashboards for Board Use
- Internal Storytelling: Framing Success for Cultural Adoption
- Scaling the Pilot to Additional Divisions or Functions
- Handing Off Ownership to Permanent Leadership
- Documenting Processes for Seamless Transition
- Building a Knowledge Transfer Package for Sustainability
- Establishing a Centre of Excellence for Ongoing AI Work
- Integrating AI KPIs into Performance Management Systems
- Creating Templates for Future AI Initiatives
- Measuring Employee Confidence and Engagement Post-AI
- Conducting Post-Implementation Reviews
- Archiving Lessons Learned for Organisational Memory
- Planning for Next-Generation AI Enhancements
Module 9: Advanced AI Governance and Risk Management - Establishing an Interim AI Ethics Committee
- Designing Fairness, Accountability, and Transparency Protocols
- Auditing AI Models for Bias and Drift
- Setting Up Continuous Monitoring Systems
- Creating Incident Response Plans for AI Failures
- Ensuring Compliance with GDPR, CCPA, and Sector Regulations
- Managing Third-Party AI Vendor Risks
- Defining Data Lineage and Model Provenance
- Implementing Explainability Standards for Leadership
- Drafting AI Acceptable Use Policies
- Conducting Model Stress Testing Under Extreme Conditions
- Building Redundancy and Human-in-the-Loop Controls
- Preparing for Regulatory Inquiries or Audits
- Communicating Risk to Boards in Clear, Non-Alarmist Terms
- Integrating AI Risk into Enterprise Risk Management Frameworks
- Using AI Governance as a Credibility Signal
Module 10: Personal Mastery and Leadership Presence in AI Transitions - Projecting Confidence When Leading Unfamiliar Tech Initiatives
- Mastering the Language of AI Without Overpromising
- Using Curiosity to Build Trust with Technical Teams
- Delegating Effectively While Retaining Strategic Oversight
- Handling Ambiguity and Partial Information in AI Projects
- Building Psychological Safety in Cross-Functional AI Teams
- Managing Up: Communicating with Boards on Technical Topics
- Leading Hybrid Teams of Consultants, Contractors, and FTEs
- Creating a Legacy of Capability, Not Dependency
- Balancing Authority with Collaboration
- Maintaining Energy and Focus During High-Stakes Transitions
- Personal Branding: Positioning Yourself as a Transformation Leader
- Preparing for Your Exit While Ensuring Continuity
- Using AI Deliverables as Evidence of Leadership Impact
- Networking and Leveraging AI Success for Future Roles
- Developing a Personal Playbook for AI Strategy
Module 11: Implementation Toolkit – Templates, Checklists, and Workbooks - AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework
Module 12: Certification and Next Steps - Finalising Your AI Strategy Capstone Project
- Submitting for Expert Review and Feedback
- Incorporating Revisions Based on Guidance
- Preparing Your Personal Statement of Strategic Leadership
- Receiving Your Certificate of Completion from The Art of Service
- Adding the Credential to LinkedIn and Executive Profiles
- Accessing the Alum Network of AI-Driven Interim Leaders
- Receiving Invitations to Exclusive Practice Groups
- Accessing Advanced Briefings on Emerging AI Trends
- Obtaining Permission to Use the “Certified AI Strategy Practitioner” Title
- Leveraging the Certification in Future Board Appointments
- Updating Your Interim Leadership Proposal Package
- Tracking Career Advancement Post-Course
- Requesting Reference Letters Based on Performance
- Mentoring Future Cohorts (Optional)
- Continuing to Access Tools, Templates, and Updates Indefinitely
- Defining AI’s Role in Crisis, Transition, and Transformation
- Why Interim Leaders Are Uniquely Positioned to Drive AI Adoption
- Common Myths and Misconceptions About AI in Leadership
- Aligning AI Strategy with Interim Mandates: Stabilise, Improve, or Exit
- Understanding the AI Maturity Spectrum Across Organisations
- Key Differences Between Permanent and Interim AI Leadership Approaches
- The Ethics and Governance Imperatives for Short-Term AI Deployment
- Assessing Risk Tolerance in AI Initiatives During Transitions
- How to Prioritise AI Use Cases for Maximum Visibility and Impact
- Recognising Organisational Resistance to AI and How to Address It
- Establishing Credibility as an AI-Savvy Interim Leader
- The Interim Leader’s Role in Bridging Technical and Executive Gaps
- Mapping AI Levers to Immediate Business KPIs
- Defining Success Metrics for AI in a 60- to 100-Day Framework
- Creating Alignment Between Board Expectations and AI Feasibility
- Balancing Speed, Accuracy, and Sustainability in AI Planning
Module 2: Strategic Frameworks for AI Integration - The 4-Pillar Interim AI Strategy Model: Assess, Align, Activate, Amplify
- Applying McKinsey 7-S Framework to AI Readiness Assessment
- Using the AI Value Chain to Identify Quick Wins
- Implementing the RAPID Decision-Making Framework for AI Governance
- Leveraging SWOT Analysis for AI Opportunity Mapping
- Integrating AI into Existing Transformation Roadmaps
- Building a Time-Bound AI Strategy Canvas
- Deploying the Eisenhower Matrix to Prioritise AI Initiatives
- Using the Cynefin Framework to Classify AI Problems
- Mapping AI Solutions to Organisational Complexity Levels
- Applying Kotter’s 8-Step Model to AI Change Management
- Designing AI Pilots Using Lean Startup Principles
- Creating a 30-60-90 Day AI Action Plan Template
- Aligning AI Strategy with Culture, Leadership, and Structure
- Developing an AI Communication Strategy for Stakeholder Buy-In
- Using Scenario Planning to Evaluate AI Outcomes Under Uncertainty
Module 3: Diagnostic Tools for Organisational AI Readiness - Conducting a 72-Hour AI Readiness Diagnostic
- Assessing Data Infrastructure Maturity and Gaps
- Evaluating Technical Team Capabilities and Bandwidth
- Measuring Executive Understanding of AI Concepts
- Identifying Silent Allies and Hidden Blockers in the Organisational Network
- Using Pulse Surveys to Gauge AI Sentiment
- Analysing Past AI or Digital Initiatives for Lessons Learned
- Mapping Data Silos and Integration Feasibility
- Conducting Stakeholder Power-Interest Grids for AI Projects
- Assessing Legal and Compliance Risks in AI Deployment
- Reviewing Procurement and Vendor Readiness for AI Tools
- Diagnosing Change Fatigue and Its Impact on AI Adoption
- Creating a Readiness Heatmap for Immediate Use
- Prioritising Departments Based on AI Opportunity Density
- Conducting Cross-Functional AI Capability Workshops
- Using the ADKAR Model to Assess Individual AI Readiness
Module 4: Identifying and Validating High-Impact AI Use Cases - Generating AI Use Case Ideas Using the Jobs to Be Done Framework
- Clustering Ideas by Operational, Financial, and Strategic Impact
- Scoring Use Cases Using the AI ROI Matrix
- Validating Feasibility with the TECH-C Filter (Time, Expertise, Cost, Hardware, Culture)
- Assessing Data Availability and Quality for Each Use Case
- Estimating Implementation Effort Using the T-Shirt Sizing Method
- Calculating Expected Time-to-Value for Each Initiative
- Aligning Use Cases with Immediate Business Objectives
- Avoiding Common Pitfalls in AI Use Case Selection
- Launching Micro-Pilots to Test Assumptions Early
- Engaging Subject Matter Experts in Use Case Refinement
- Using Process Mining to Discover Hidden AI Opportunities
- Analysing Invoice, HR, and Supply Chain Data for Automation Potential
- Identifying Repetitive Tasks Ideal for RPA + AI Integration
- Evaluating Customer Journey Pain Points for AI Intervention
- Building a Use Case Portfolio for Board Presentation
Module 5: Building the Board-Ready AI Proposal - Structuring a 1-Page AI Executive Brief
- Writing the Problem Statement with Business Context
- Defining the AI Solution in Non-Technical Terms
- Quantifying Financial Impact with Conservative, Base, and Optimistic Scenarios
- Estimating Implementation Costs and Resource Needs
- Projecting Payback Period and NPV for AI Investments
- Incorporating Risk Mitigation Strategies into the Proposal
- Designing a Phased Rollout Plan for Incremental Wins
- Creating Governance and Oversight Mechanisms
- Defining Success Metrics and KPIs for Tracking
- Anticipating and Pre-Empting Executive Objections
- Using Visuals and Analogies to Communicate AI Value
- Incorporating Testimonials and Precedent from Similar Industries
- Aligning the Proposal with ESG and Digital Transformation Goals
- Obtaining Pre-Approval Signals from Key Stakeholders
- Rehearsing the Presentation with Feedback Loops
Module 6: Securing Stakeholder Alignment and Funding - Identifying All Critical Decision Makers and Influencers
- Tailoring Communication Styles to Different Executive Personalities
- Using Pre-Meetings to Build Consensus Before Formal Reviews
- Creating Variant Proposal Versions for Finance, Ops, and Legal
- Hosting Cross-Functional AI Vision Workshops
- Developing a Compelling Narrative with a Clear Before-After-Bridge
- Leveraging Pilot Wins to Build Momentum and Expand Budget
- Using the SCARF Model to Reduce Threat Response in Teams
- Engaging Internal Champions to Co-Own the Initiative
- Negotiating Resource Allocation Without Permanent Headcount
- Designing a Funding Request with Contingency and Flexibility
- Presenting to the Board Using the Pyramid Principle
- Securing Conditional Approval and Fast-Track Pilots
- Building a Coalition of Support Across Departments
- Using Social Proof from Peer Organisations
- Handling “Not Invented Here” Resistance with Diplomacy
Module 7: Designing and Launching AI Pilots - Selecting the Right Pilot Team with Hybrid Skills
- Defining Clear Inclusion and Exclusion Criteria
- Establishing Baseline Metrics Before Launch
- Setting Up Data Collection and Monitoring Protocols
- Designing Control Groups for Accurate Impact Measurement
- Simplifying AI Models for Rapid Iteration
- Using MVP Principles to Minimise Time-to-Insight
- Running Daily Stand-Ups Without Disrupting Core Operations
- Managing Vendor Relationships for AI Tools
- Creating a Pilot Dashboard for Real-Time Oversight
- Handling Data Privacy and Anonymisation Requirements
- Documenting Assumptions, Decisions, and Deviations
- Running Mid-Pilot Check-Ins with Stakeholders
- Preparing for Scalability from Day One
- Using Feedback Loops to Improve Model Performance
- Deciding When to Pivot, Pause, or Proceed
Module 8: Measuring, Communicating, and Scaling Results - Calculating Actual vs. Predicted ROI from Pilots
- Identifying Secondary Benefits of AI Deployment
- Creating a Results Report for Executive Summaries
- Designing Infographics and Dashboards for Board Use
- Internal Storytelling: Framing Success for Cultural Adoption
- Scaling the Pilot to Additional Divisions or Functions
- Handing Off Ownership to Permanent Leadership
- Documenting Processes for Seamless Transition
- Building a Knowledge Transfer Package for Sustainability
- Establishing a Centre of Excellence for Ongoing AI Work
- Integrating AI KPIs into Performance Management Systems
- Creating Templates for Future AI Initiatives
- Measuring Employee Confidence and Engagement Post-AI
- Conducting Post-Implementation Reviews
- Archiving Lessons Learned for Organisational Memory
- Planning for Next-Generation AI Enhancements
Module 9: Advanced AI Governance and Risk Management - Establishing an Interim AI Ethics Committee
- Designing Fairness, Accountability, and Transparency Protocols
- Auditing AI Models for Bias and Drift
- Setting Up Continuous Monitoring Systems
- Creating Incident Response Plans for AI Failures
- Ensuring Compliance with GDPR, CCPA, and Sector Regulations
- Managing Third-Party AI Vendor Risks
- Defining Data Lineage and Model Provenance
- Implementing Explainability Standards for Leadership
- Drafting AI Acceptable Use Policies
- Conducting Model Stress Testing Under Extreme Conditions
- Building Redundancy and Human-in-the-Loop Controls
- Preparing for Regulatory Inquiries or Audits
- Communicating Risk to Boards in Clear, Non-Alarmist Terms
- Integrating AI Risk into Enterprise Risk Management Frameworks
- Using AI Governance as a Credibility Signal
Module 10: Personal Mastery and Leadership Presence in AI Transitions - Projecting Confidence When Leading Unfamiliar Tech Initiatives
- Mastering the Language of AI Without Overpromising
- Using Curiosity to Build Trust with Technical Teams
- Delegating Effectively While Retaining Strategic Oversight
- Handling Ambiguity and Partial Information in AI Projects
- Building Psychological Safety in Cross-Functional AI Teams
- Managing Up: Communicating with Boards on Technical Topics
- Leading Hybrid Teams of Consultants, Contractors, and FTEs
- Creating a Legacy of Capability, Not Dependency
- Balancing Authority with Collaboration
- Maintaining Energy and Focus During High-Stakes Transitions
- Personal Branding: Positioning Yourself as a Transformation Leader
- Preparing for Your Exit While Ensuring Continuity
- Using AI Deliverables as Evidence of Leadership Impact
- Networking and Leveraging AI Success for Future Roles
- Developing a Personal Playbook for AI Strategy
Module 11: Implementation Toolkit – Templates, Checklists, and Workbooks - AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework
Module 12: Certification and Next Steps - Finalising Your AI Strategy Capstone Project
- Submitting for Expert Review and Feedback
- Incorporating Revisions Based on Guidance
- Preparing Your Personal Statement of Strategic Leadership
- Receiving Your Certificate of Completion from The Art of Service
- Adding the Credential to LinkedIn and Executive Profiles
- Accessing the Alum Network of AI-Driven Interim Leaders
- Receiving Invitations to Exclusive Practice Groups
- Accessing Advanced Briefings on Emerging AI Trends
- Obtaining Permission to Use the “Certified AI Strategy Practitioner” Title
- Leveraging the Certification in Future Board Appointments
- Updating Your Interim Leadership Proposal Package
- Tracking Career Advancement Post-Course
- Requesting Reference Letters Based on Performance
- Mentoring Future Cohorts (Optional)
- Continuing to Access Tools, Templates, and Updates Indefinitely
- Conducting a 72-Hour AI Readiness Diagnostic
- Assessing Data Infrastructure Maturity and Gaps
- Evaluating Technical Team Capabilities and Bandwidth
- Measuring Executive Understanding of AI Concepts
- Identifying Silent Allies and Hidden Blockers in the Organisational Network
- Using Pulse Surveys to Gauge AI Sentiment
- Analysing Past AI or Digital Initiatives for Lessons Learned
- Mapping Data Silos and Integration Feasibility
- Conducting Stakeholder Power-Interest Grids for AI Projects
- Assessing Legal and Compliance Risks in AI Deployment
- Reviewing Procurement and Vendor Readiness for AI Tools
- Diagnosing Change Fatigue and Its Impact on AI Adoption
- Creating a Readiness Heatmap for Immediate Use
- Prioritising Departments Based on AI Opportunity Density
- Conducting Cross-Functional AI Capability Workshops
- Using the ADKAR Model to Assess Individual AI Readiness
Module 4: Identifying and Validating High-Impact AI Use Cases - Generating AI Use Case Ideas Using the Jobs to Be Done Framework
- Clustering Ideas by Operational, Financial, and Strategic Impact
- Scoring Use Cases Using the AI ROI Matrix
- Validating Feasibility with the TECH-C Filter (Time, Expertise, Cost, Hardware, Culture)
- Assessing Data Availability and Quality for Each Use Case
- Estimating Implementation Effort Using the T-Shirt Sizing Method
- Calculating Expected Time-to-Value for Each Initiative
- Aligning Use Cases with Immediate Business Objectives
- Avoiding Common Pitfalls in AI Use Case Selection
- Launching Micro-Pilots to Test Assumptions Early
- Engaging Subject Matter Experts in Use Case Refinement
- Using Process Mining to Discover Hidden AI Opportunities
- Analysing Invoice, HR, and Supply Chain Data for Automation Potential
- Identifying Repetitive Tasks Ideal for RPA + AI Integration
- Evaluating Customer Journey Pain Points for AI Intervention
- Building a Use Case Portfolio for Board Presentation
Module 5: Building the Board-Ready AI Proposal - Structuring a 1-Page AI Executive Brief
- Writing the Problem Statement with Business Context
- Defining the AI Solution in Non-Technical Terms
- Quantifying Financial Impact with Conservative, Base, and Optimistic Scenarios
- Estimating Implementation Costs and Resource Needs
- Projecting Payback Period and NPV for AI Investments
- Incorporating Risk Mitigation Strategies into the Proposal
- Designing a Phased Rollout Plan for Incremental Wins
- Creating Governance and Oversight Mechanisms
- Defining Success Metrics and KPIs for Tracking
- Anticipating and Pre-Empting Executive Objections
- Using Visuals and Analogies to Communicate AI Value
- Incorporating Testimonials and Precedent from Similar Industries
- Aligning the Proposal with ESG and Digital Transformation Goals
- Obtaining Pre-Approval Signals from Key Stakeholders
- Rehearsing the Presentation with Feedback Loops
Module 6: Securing Stakeholder Alignment and Funding - Identifying All Critical Decision Makers and Influencers
- Tailoring Communication Styles to Different Executive Personalities
- Using Pre-Meetings to Build Consensus Before Formal Reviews
- Creating Variant Proposal Versions for Finance, Ops, and Legal
- Hosting Cross-Functional AI Vision Workshops
- Developing a Compelling Narrative with a Clear Before-After-Bridge
- Leveraging Pilot Wins to Build Momentum and Expand Budget
- Using the SCARF Model to Reduce Threat Response in Teams
- Engaging Internal Champions to Co-Own the Initiative
- Negotiating Resource Allocation Without Permanent Headcount
- Designing a Funding Request with Contingency and Flexibility
- Presenting to the Board Using the Pyramid Principle
- Securing Conditional Approval and Fast-Track Pilots
- Building a Coalition of Support Across Departments
- Using Social Proof from Peer Organisations
- Handling “Not Invented Here” Resistance with Diplomacy
Module 7: Designing and Launching AI Pilots - Selecting the Right Pilot Team with Hybrid Skills
- Defining Clear Inclusion and Exclusion Criteria
- Establishing Baseline Metrics Before Launch
- Setting Up Data Collection and Monitoring Protocols
- Designing Control Groups for Accurate Impact Measurement
- Simplifying AI Models for Rapid Iteration
- Using MVP Principles to Minimise Time-to-Insight
- Running Daily Stand-Ups Without Disrupting Core Operations
- Managing Vendor Relationships for AI Tools
- Creating a Pilot Dashboard for Real-Time Oversight
- Handling Data Privacy and Anonymisation Requirements
- Documenting Assumptions, Decisions, and Deviations
- Running Mid-Pilot Check-Ins with Stakeholders
- Preparing for Scalability from Day One
- Using Feedback Loops to Improve Model Performance
- Deciding When to Pivot, Pause, or Proceed
Module 8: Measuring, Communicating, and Scaling Results - Calculating Actual vs. Predicted ROI from Pilots
- Identifying Secondary Benefits of AI Deployment
- Creating a Results Report for Executive Summaries
- Designing Infographics and Dashboards for Board Use
- Internal Storytelling: Framing Success for Cultural Adoption
- Scaling the Pilot to Additional Divisions or Functions
- Handing Off Ownership to Permanent Leadership
- Documenting Processes for Seamless Transition
- Building a Knowledge Transfer Package for Sustainability
- Establishing a Centre of Excellence for Ongoing AI Work
- Integrating AI KPIs into Performance Management Systems
- Creating Templates for Future AI Initiatives
- Measuring Employee Confidence and Engagement Post-AI
- Conducting Post-Implementation Reviews
- Archiving Lessons Learned for Organisational Memory
- Planning for Next-Generation AI Enhancements
Module 9: Advanced AI Governance and Risk Management - Establishing an Interim AI Ethics Committee
- Designing Fairness, Accountability, and Transparency Protocols
- Auditing AI Models for Bias and Drift
- Setting Up Continuous Monitoring Systems
- Creating Incident Response Plans for AI Failures
- Ensuring Compliance with GDPR, CCPA, and Sector Regulations
- Managing Third-Party AI Vendor Risks
- Defining Data Lineage and Model Provenance
- Implementing Explainability Standards for Leadership
- Drafting AI Acceptable Use Policies
- Conducting Model Stress Testing Under Extreme Conditions
- Building Redundancy and Human-in-the-Loop Controls
- Preparing for Regulatory Inquiries or Audits
- Communicating Risk to Boards in Clear, Non-Alarmist Terms
- Integrating AI Risk into Enterprise Risk Management Frameworks
- Using AI Governance as a Credibility Signal
Module 10: Personal Mastery and Leadership Presence in AI Transitions - Projecting Confidence When Leading Unfamiliar Tech Initiatives
- Mastering the Language of AI Without Overpromising
- Using Curiosity to Build Trust with Technical Teams
- Delegating Effectively While Retaining Strategic Oversight
- Handling Ambiguity and Partial Information in AI Projects
- Building Psychological Safety in Cross-Functional AI Teams
- Managing Up: Communicating with Boards on Technical Topics
- Leading Hybrid Teams of Consultants, Contractors, and FTEs
- Creating a Legacy of Capability, Not Dependency
- Balancing Authority with Collaboration
- Maintaining Energy and Focus During High-Stakes Transitions
- Personal Branding: Positioning Yourself as a Transformation Leader
- Preparing for Your Exit While Ensuring Continuity
- Using AI Deliverables as Evidence of Leadership Impact
- Networking and Leveraging AI Success for Future Roles
- Developing a Personal Playbook for AI Strategy
Module 11: Implementation Toolkit – Templates, Checklists, and Workbooks - AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework
Module 12: Certification and Next Steps - Finalising Your AI Strategy Capstone Project
- Submitting for Expert Review and Feedback
- Incorporating Revisions Based on Guidance
- Preparing Your Personal Statement of Strategic Leadership
- Receiving Your Certificate of Completion from The Art of Service
- Adding the Credential to LinkedIn and Executive Profiles
- Accessing the Alum Network of AI-Driven Interim Leaders
- Receiving Invitations to Exclusive Practice Groups
- Accessing Advanced Briefings on Emerging AI Trends
- Obtaining Permission to Use the “Certified AI Strategy Practitioner” Title
- Leveraging the Certification in Future Board Appointments
- Updating Your Interim Leadership Proposal Package
- Tracking Career Advancement Post-Course
- Requesting Reference Letters Based on Performance
- Mentoring Future Cohorts (Optional)
- Continuing to Access Tools, Templates, and Updates Indefinitely
- Structuring a 1-Page AI Executive Brief
- Writing the Problem Statement with Business Context
- Defining the AI Solution in Non-Technical Terms
- Quantifying Financial Impact with Conservative, Base, and Optimistic Scenarios
- Estimating Implementation Costs and Resource Needs
- Projecting Payback Period and NPV for AI Investments
- Incorporating Risk Mitigation Strategies into the Proposal
- Designing a Phased Rollout Plan for Incremental Wins
- Creating Governance and Oversight Mechanisms
- Defining Success Metrics and KPIs for Tracking
- Anticipating and Pre-Empting Executive Objections
- Using Visuals and Analogies to Communicate AI Value
- Incorporating Testimonials and Precedent from Similar Industries
- Aligning the Proposal with ESG and Digital Transformation Goals
- Obtaining Pre-Approval Signals from Key Stakeholders
- Rehearsing the Presentation with Feedback Loops
Module 6: Securing Stakeholder Alignment and Funding - Identifying All Critical Decision Makers and Influencers
- Tailoring Communication Styles to Different Executive Personalities
- Using Pre-Meetings to Build Consensus Before Formal Reviews
- Creating Variant Proposal Versions for Finance, Ops, and Legal
- Hosting Cross-Functional AI Vision Workshops
- Developing a Compelling Narrative with a Clear Before-After-Bridge
- Leveraging Pilot Wins to Build Momentum and Expand Budget
- Using the SCARF Model to Reduce Threat Response in Teams
- Engaging Internal Champions to Co-Own the Initiative
- Negotiating Resource Allocation Without Permanent Headcount
- Designing a Funding Request with Contingency and Flexibility
- Presenting to the Board Using the Pyramid Principle
- Securing Conditional Approval and Fast-Track Pilots
- Building a Coalition of Support Across Departments
- Using Social Proof from Peer Organisations
- Handling “Not Invented Here” Resistance with Diplomacy
Module 7: Designing and Launching AI Pilots - Selecting the Right Pilot Team with Hybrid Skills
- Defining Clear Inclusion and Exclusion Criteria
- Establishing Baseline Metrics Before Launch
- Setting Up Data Collection and Monitoring Protocols
- Designing Control Groups for Accurate Impact Measurement
- Simplifying AI Models for Rapid Iteration
- Using MVP Principles to Minimise Time-to-Insight
- Running Daily Stand-Ups Without Disrupting Core Operations
- Managing Vendor Relationships for AI Tools
- Creating a Pilot Dashboard for Real-Time Oversight
- Handling Data Privacy and Anonymisation Requirements
- Documenting Assumptions, Decisions, and Deviations
- Running Mid-Pilot Check-Ins with Stakeholders
- Preparing for Scalability from Day One
- Using Feedback Loops to Improve Model Performance
- Deciding When to Pivot, Pause, or Proceed
Module 8: Measuring, Communicating, and Scaling Results - Calculating Actual vs. Predicted ROI from Pilots
- Identifying Secondary Benefits of AI Deployment
- Creating a Results Report for Executive Summaries
- Designing Infographics and Dashboards for Board Use
- Internal Storytelling: Framing Success for Cultural Adoption
- Scaling the Pilot to Additional Divisions or Functions
- Handing Off Ownership to Permanent Leadership
- Documenting Processes for Seamless Transition
- Building a Knowledge Transfer Package for Sustainability
- Establishing a Centre of Excellence for Ongoing AI Work
- Integrating AI KPIs into Performance Management Systems
- Creating Templates for Future AI Initiatives
- Measuring Employee Confidence and Engagement Post-AI
- Conducting Post-Implementation Reviews
- Archiving Lessons Learned for Organisational Memory
- Planning for Next-Generation AI Enhancements
Module 9: Advanced AI Governance and Risk Management - Establishing an Interim AI Ethics Committee
- Designing Fairness, Accountability, and Transparency Protocols
- Auditing AI Models for Bias and Drift
- Setting Up Continuous Monitoring Systems
- Creating Incident Response Plans for AI Failures
- Ensuring Compliance with GDPR, CCPA, and Sector Regulations
- Managing Third-Party AI Vendor Risks
- Defining Data Lineage and Model Provenance
- Implementing Explainability Standards for Leadership
- Drafting AI Acceptable Use Policies
- Conducting Model Stress Testing Under Extreme Conditions
- Building Redundancy and Human-in-the-Loop Controls
- Preparing for Regulatory Inquiries or Audits
- Communicating Risk to Boards in Clear, Non-Alarmist Terms
- Integrating AI Risk into Enterprise Risk Management Frameworks
- Using AI Governance as a Credibility Signal
Module 10: Personal Mastery and Leadership Presence in AI Transitions - Projecting Confidence When Leading Unfamiliar Tech Initiatives
- Mastering the Language of AI Without Overpromising
- Using Curiosity to Build Trust with Technical Teams
- Delegating Effectively While Retaining Strategic Oversight
- Handling Ambiguity and Partial Information in AI Projects
- Building Psychological Safety in Cross-Functional AI Teams
- Managing Up: Communicating with Boards on Technical Topics
- Leading Hybrid Teams of Consultants, Contractors, and FTEs
- Creating a Legacy of Capability, Not Dependency
- Balancing Authority with Collaboration
- Maintaining Energy and Focus During High-Stakes Transitions
- Personal Branding: Positioning Yourself as a Transformation Leader
- Preparing for Your Exit While Ensuring Continuity
- Using AI Deliverables as Evidence of Leadership Impact
- Networking and Leveraging AI Success for Future Roles
- Developing a Personal Playbook for AI Strategy
Module 11: Implementation Toolkit – Templates, Checklists, and Workbooks - AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework
Module 12: Certification and Next Steps - Finalising Your AI Strategy Capstone Project
- Submitting for Expert Review and Feedback
- Incorporating Revisions Based on Guidance
- Preparing Your Personal Statement of Strategic Leadership
- Receiving Your Certificate of Completion from The Art of Service
- Adding the Credential to LinkedIn and Executive Profiles
- Accessing the Alum Network of AI-Driven Interim Leaders
- Receiving Invitations to Exclusive Practice Groups
- Accessing Advanced Briefings on Emerging AI Trends
- Obtaining Permission to Use the “Certified AI Strategy Practitioner” Title
- Leveraging the Certification in Future Board Appointments
- Updating Your Interim Leadership Proposal Package
- Tracking Career Advancement Post-Course
- Requesting Reference Letters Based on Performance
- Mentoring Future Cohorts (Optional)
- Continuing to Access Tools, Templates, and Updates Indefinitely
- Selecting the Right Pilot Team with Hybrid Skills
- Defining Clear Inclusion and Exclusion Criteria
- Establishing Baseline Metrics Before Launch
- Setting Up Data Collection and Monitoring Protocols
- Designing Control Groups for Accurate Impact Measurement
- Simplifying AI Models for Rapid Iteration
- Using MVP Principles to Minimise Time-to-Insight
- Running Daily Stand-Ups Without Disrupting Core Operations
- Managing Vendor Relationships for AI Tools
- Creating a Pilot Dashboard for Real-Time Oversight
- Handling Data Privacy and Anonymisation Requirements
- Documenting Assumptions, Decisions, and Deviations
- Running Mid-Pilot Check-Ins with Stakeholders
- Preparing for Scalability from Day One
- Using Feedback Loops to Improve Model Performance
- Deciding When to Pivot, Pause, or Proceed
Module 8: Measuring, Communicating, and Scaling Results - Calculating Actual vs. Predicted ROI from Pilots
- Identifying Secondary Benefits of AI Deployment
- Creating a Results Report for Executive Summaries
- Designing Infographics and Dashboards for Board Use
- Internal Storytelling: Framing Success for Cultural Adoption
- Scaling the Pilot to Additional Divisions or Functions
- Handing Off Ownership to Permanent Leadership
- Documenting Processes for Seamless Transition
- Building a Knowledge Transfer Package for Sustainability
- Establishing a Centre of Excellence for Ongoing AI Work
- Integrating AI KPIs into Performance Management Systems
- Creating Templates for Future AI Initiatives
- Measuring Employee Confidence and Engagement Post-AI
- Conducting Post-Implementation Reviews
- Archiving Lessons Learned for Organisational Memory
- Planning for Next-Generation AI Enhancements
Module 9: Advanced AI Governance and Risk Management - Establishing an Interim AI Ethics Committee
- Designing Fairness, Accountability, and Transparency Protocols
- Auditing AI Models for Bias and Drift
- Setting Up Continuous Monitoring Systems
- Creating Incident Response Plans for AI Failures
- Ensuring Compliance with GDPR, CCPA, and Sector Regulations
- Managing Third-Party AI Vendor Risks
- Defining Data Lineage and Model Provenance
- Implementing Explainability Standards for Leadership
- Drafting AI Acceptable Use Policies
- Conducting Model Stress Testing Under Extreme Conditions
- Building Redundancy and Human-in-the-Loop Controls
- Preparing for Regulatory Inquiries or Audits
- Communicating Risk to Boards in Clear, Non-Alarmist Terms
- Integrating AI Risk into Enterprise Risk Management Frameworks
- Using AI Governance as a Credibility Signal
Module 10: Personal Mastery and Leadership Presence in AI Transitions - Projecting Confidence When Leading Unfamiliar Tech Initiatives
- Mastering the Language of AI Without Overpromising
- Using Curiosity to Build Trust with Technical Teams
- Delegating Effectively While Retaining Strategic Oversight
- Handling Ambiguity and Partial Information in AI Projects
- Building Psychological Safety in Cross-Functional AI Teams
- Managing Up: Communicating with Boards on Technical Topics
- Leading Hybrid Teams of Consultants, Contractors, and FTEs
- Creating a Legacy of Capability, Not Dependency
- Balancing Authority with Collaboration
- Maintaining Energy and Focus During High-Stakes Transitions
- Personal Branding: Positioning Yourself as a Transformation Leader
- Preparing for Your Exit While Ensuring Continuity
- Using AI Deliverables as Evidence of Leadership Impact
- Networking and Leveraging AI Success for Future Roles
- Developing a Personal Playbook for AI Strategy
Module 11: Implementation Toolkit – Templates, Checklists, and Workbooks - AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework
Module 12: Certification and Next Steps - Finalising Your AI Strategy Capstone Project
- Submitting for Expert Review and Feedback
- Incorporating Revisions Based on Guidance
- Preparing Your Personal Statement of Strategic Leadership
- Receiving Your Certificate of Completion from The Art of Service
- Adding the Credential to LinkedIn and Executive Profiles
- Accessing the Alum Network of AI-Driven Interim Leaders
- Receiving Invitations to Exclusive Practice Groups
- Accessing Advanced Briefings on Emerging AI Trends
- Obtaining Permission to Use the “Certified AI Strategy Practitioner” Title
- Leveraging the Certification in Future Board Appointments
- Updating Your Interim Leadership Proposal Package
- Tracking Career Advancement Post-Course
- Requesting Reference Letters Based on Performance
- Mentoring Future Cohorts (Optional)
- Continuing to Access Tools, Templates, and Updates Indefinitely
- Establishing an Interim AI Ethics Committee
- Designing Fairness, Accountability, and Transparency Protocols
- Auditing AI Models for Bias and Drift
- Setting Up Continuous Monitoring Systems
- Creating Incident Response Plans for AI Failures
- Ensuring Compliance with GDPR, CCPA, and Sector Regulations
- Managing Third-Party AI Vendor Risks
- Defining Data Lineage and Model Provenance
- Implementing Explainability Standards for Leadership
- Drafting AI Acceptable Use Policies
- Conducting Model Stress Testing Under Extreme Conditions
- Building Redundancy and Human-in-the-Loop Controls
- Preparing for Regulatory Inquiries or Audits
- Communicating Risk to Boards in Clear, Non-Alarmist Terms
- Integrating AI Risk into Enterprise Risk Management Frameworks
- Using AI Governance as a Credibility Signal
Module 10: Personal Mastery and Leadership Presence in AI Transitions - Projecting Confidence When Leading Unfamiliar Tech Initiatives
- Mastering the Language of AI Without Overpromising
- Using Curiosity to Build Trust with Technical Teams
- Delegating Effectively While Retaining Strategic Oversight
- Handling Ambiguity and Partial Information in AI Projects
- Building Psychological Safety in Cross-Functional AI Teams
- Managing Up: Communicating with Boards on Technical Topics
- Leading Hybrid Teams of Consultants, Contractors, and FTEs
- Creating a Legacy of Capability, Not Dependency
- Balancing Authority with Collaboration
- Maintaining Energy and Focus During High-Stakes Transitions
- Personal Branding: Positioning Yourself as a Transformation Leader
- Preparing for Your Exit While Ensuring Continuity
- Using AI Deliverables as Evidence of Leadership Impact
- Networking and Leveraging AI Success for Future Roles
- Developing a Personal Playbook for AI Strategy
Module 11: Implementation Toolkit – Templates, Checklists, and Workbooks - AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework
Module 12: Certification and Next Steps - Finalising Your AI Strategy Capstone Project
- Submitting for Expert Review and Feedback
- Incorporating Revisions Based on Guidance
- Preparing Your Personal Statement of Strategic Leadership
- Receiving Your Certificate of Completion from The Art of Service
- Adding the Credential to LinkedIn and Executive Profiles
- Accessing the Alum Network of AI-Driven Interim Leaders
- Receiving Invitations to Exclusive Practice Groups
- Accessing Advanced Briefings on Emerging AI Trends
- Obtaining Permission to Use the “Certified AI Strategy Practitioner” Title
- Leveraging the Certification in Future Board Appointments
- Updating Your Interim Leadership Proposal Package
- Tracking Career Advancement Post-Course
- Requesting Reference Letters Based on Performance
- Mentoring Future Cohorts (Optional)
- Continuing to Access Tools, Templates, and Updates Indefinitely
- AI Readiness Diagnostic Scorecard
- Stakeholder Power-Interest Grid Template
- AI Use Case ROI Calculator (Excel-Based)
- 30-60-90 Day AI Strategy Roadmap Template
- Board-Ready Proposal Structure with Placeholders
- AI Pilot Launch Checklist
- Executive Communication Script Library
- Risk Assessment Matrix for AI Projects
- Data Readiness Audit Form
- Influencer Mapping Worksheet
- Change Impact Assessment Tool
- AI Ethics Screening Questions
- Success Metrics Definition Guide
- Knowledge Transfer Documentation Template
- Pilot Results Dashboard (Editable)
- Post-Implementation Review Framework