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T1: Executive

Track: Executive
Agentic stack planes: Control
Enterprise planes: People & Leadership, Culture & Change, Governance & Risk, Strategy & Portfolio, Economics & ROI
Target Audience: Decision-makers and executives
Badge: Applied AI Executive
Meaning: Trusted AI decision-maker

Agentic plane colors match the AI Capabilities Stack (round dots on track cards).

Control

Enterprise plane colors match the same diagram (square markers on track cards).

People & LeadershipCulture & ChangeGovernance & RiskStrategy & PortfolioEconomics & ROI

Who This Is For

  • C-level executives and senior leaders
  • Board members making AI investment decisions
  • Public sector policy makers
  • Procurement and risk management leaders

What You'll Learn

Core Capabilities

  • AI Maturity Assessment - Understand where your organization stands
  • Strategic Decision-Making - When to invest in AI, when to avoid it
  • Risk & Governance - Navigate AI risks and regulatory requirements
  • Value Realization - Connect AI investments to business outcomes

Key Focus Areas

  • Policy and procurement frameworks
  • Risk assessment and mitigation
  • Public value and trust (for public sector)
  • AI investment prioritization

Schedule

Duration: 4 weeks
Weeks: 1-4
Focus: Control plane - governance, procurement, and investment framing

Week 1: AI Reality Check

Bloom Level: Remember & Understand (primary), Apply (secondary)
Knowledge Dimension: Factual & Conceptual
Tool Mediation: Maturity and landscape assessment tools

  • Ground truth on AI capabilities and limits in 2026 [Remember]
  • Organizational readiness and hype vs production gap [Understand]
  • When AI is and is not the right lever [Apply]
  • Framing decisions for executives and boards [Apply]

Cognitive Integration: Establishes a shared reality baseline before strategy work - foundation for Judgment on where to invest attention.

Week 2: Trust & Governance

Bloom Level: Analyze (primary), Evaluate (secondary), Apply (foundation)
Knowledge Dimension: Conceptual & Procedural
Tool Mediation: Policy templates and risk frameworks

  • Trust as a product of systems, not slogans [Understand]
  • Governance outside the agent loop (control plane framing) [Analyze]
  • Regulatory and reputational risk landscape [Evaluate]
  • Accountability structures that scale [Apply]

Cognitive Integration: Connects governance to Governance and Judgment scoring dimensions explicitly.

Week 3: Build vs Buy

Bloom Level: Apply (primary), Analyze (secondary), Evaluate (foundation)
Knowledge Dimension: Procedural & Conceptual
Tool Mediation: Vendor evaluation and TCO models

  • Build vs buy vs partner decision criteria [Analyze]
  • Evaluating vendors and managed AI services [Apply]
  • Data, lock-in, and exit strategy [Evaluate]
  • Procurement patterns for enterprises and public sector [Apply]

Cognitive Integration: Applies frameworks to real sourcing decisions - Transfer across industries.

Week 4: Investment Strategy

Bloom Level: Create (primary), Evaluate (secondary), Analyze (foundation)
Knowledge Dimension: Procedural & Metacognitive
Tool Mediation: Portfolio and roadmap communication tools

  • Portfolio prioritization and sequencing [Create]
  • Investment thesis tied to measurable outcomes [Create]
  • Stakeholder alignment and board narrative [Evaluate]
  • Capstone: AI Investment Decision Framework [Create]

Cognitive Integration: Synthesizes the track into a single credentialed artifact demonstrating Judgment and Rigor.

Assessment: AI Investment Decision Framework

Track Learning Outcomes

Upon completing this track, you will be able to:

  • Assess AI maturity - Evaluate your organization's current AI capabilities and identify gaps
  • Make strategic decisions - Determine when AI investments are appropriate and when to avoid them
  • Navigate regulatory landscape - Understand and comply with AI governance frameworks, PDPA, GDPR, and sector-specific regulations
  • Prioritize AI investments - Connect AI initiatives to business value and strategic objectives
  • Establish governance frameworks - Design policies, risk management processes, and accountability structures for AI initiatives
  • Evaluate AI vendors and solutions - Assess technical capabilities, risks, and value propositions
  • Communicate AI strategy - Articulate AI vision, risks, and value to stakeholders and board members
  • Balance innovation with risk - Make informed tradeoffs between AI opportunities and organizational risk tolerance

Transfer & Judgment Capabilities

This track explicitly develops two critical capabilities:

Transfer Capability

Apply learning to novel situations and contexts

  • Adapt AI maturity frameworks to different organizational contexts
  • Transfer governance principles across industries and regulatory environments
  • Generalize strategic decision-making frameworks to new scenarios
  • Apply investment prioritization methods to diverse use cases

How it's developed: Through case studies, scenario exercises, and applying frameworks to your own organization's unique context.

Judgment Capability

Make sound decisions under uncertainty

  • Exercise restraint in AI investment decisions
  • Identify and defer unsuitable AI use cases
  • Make principled tradeoffs between opportunity and risk
  • Balance innovation with organizational risk tolerance

How it's developed: Through decision-making scenarios, "when NOT to use AI" exercises, risk-benefit analysis, and tradeoff evaluation frameworks.

Track Structure

This track contains multiple levels, each with specific learning outcomes. Progress through levels to build your capability as an AI decision-maker.

Level 1: Foundation (Weeks 1-4) Bloom Focus: Remember & Understand (primary), Apply (secondary)
Knowledge Dimensions: Factual & Conceptual
Capability Target: Master core concepts and frameworks, understand relationships and principles

  • AI maturity frameworks [Remember & Understand]
  • Decision-making under uncertainty [Understand]
  • Value and roadmap design [Apply]
  • Governance foundations [Understand]

Learning Outcomes:

  • Recalls relevant AI maturity frameworks and concepts
  • Explains relationships between AI strategy, governance, and value
  • Applies frameworks to assess organizational readiness
  • Demonstrates foundational understanding of AI decision-making

Level 2: Application (Future) Bloom Focus: Apply & Analyze (primary), Evaluate (secondary)
Knowledge Dimensions: Procedural & Conceptual
Capability Target: Apply knowledge systematically, analyze complex situations

  • Advanced strategic analysis
  • Complex decision-making scenarios
  • Multi-stakeholder governance
  • Risk-benefit evaluation

Level 3: Mastery (Future) Bloom Focus: Evaluate & Create (primary), Analyze (foundation)
Knowledge Dimensions: Metacognitive & Procedural
Capability Target: Make expert judgments, create comprehensive frameworks

  • Expert-level strategic judgment
  • Creating custom governance frameworks
  • Advanced tradeoff analysis
  • Board-level communication and defense

Assessment

  • Artifact: AI Investment Decision Framework
  • Focus: Judgment, rigor, and governance dimensions
  • Outcome: Ability to make informed AI investment decisions

Public Sector Emphasis

For public sector participants, this track emphasizes:

  • Policy alignment
  • Risk management
  • Procurement transparency
  • Public trust and accountability

Credential

Upon completion, earn the Applied AI Executive badge - demonstrating your capability as a trusted AI decision-maker.


Ready to get started? Get in touch to learn more or apply.

Next: T2: AI Product