Initiate AI - United States

*NOTE - This class is taught in-person

The Challenge

Leaders are being asked to fund, govern, and accelerate AI initiatives—but often without the clarity or fluency to make confident, high‑stakes decisions. At the same time, organizations look to these same leaders to set direction, establish guardrails, and guide the enterprise through the shift to AI‑driven ways of working.

Most leaders aren’t struggling with the technology itself—they’re struggling with how to lead their organization effectively in the age of AI:

• How to prioritize what’s strategically meaningful versus hype
• How to set budgets and governance that don’t slow progress or invite risk
• How to shape a culture that embraces AI rather than fears it
• How to build a realistic path toward an AI‑Native operating model—across strategy, workforce, data, technology, and governance—without chaos or waste

This course is a structured working session where senior leaders use a shared framework to align on priorities, make decisions, and commit to next steps, with their organizational context driving the discussion, not a training or PPT presentation focused on knowledge transfer.

The session doesn't aim to produce a complete AI strategy in a day. The goal is clarity, ownership, and momentum.

Who It’s For

• For senior leaders with P&L responsibility at the enterprise level where AI initiatives are stalling between vision & execution.
• Business unit leaders, PMOs, and transformation sponsors seeking to align AI initiatives with strategy and P&L impact
• Anyone who must evaluate, approve, or manage AI initiatives across the enterprise

What You’ll Learn

1. The Landscape, Lexicon & AI‑Native Opportunity to move beyond the hype to focus on business logic and P&L impact. You will build a shared executive AI lexicon (LLMs, GenAI, RAG, agents) and diagnose your organization’s AI‑Native maturity—across strategy, workforce, governance, data, platforms, culture, and agility—to establish an honest baseline for transformation.
2. Governance & Ethics to define how the organization ensures AI is used responsibly and stays aligned with its legal obligations, risk tolerance, and values as it scales.
3. The Human Factor, Workforce & Leadership to learn how to pivot your workforce from passive “users” of tools to active “creators” of value. You will define who must become AI‑Native first, shape a workforce upskilling plan (including AI‑Native Foundations and AI‑Native Change Agents), and explore how to model human‑centric AI leadership and culture while identifying agility barriers in your current planning and funding practices.
4. Infrastructure, Data & Enabling Capabilities to shift the technology discussion from features to capital allocation. You will evaluate the critical trade‑offs between “Walled Gardens” (buy) and “Open Frontiers” (build), align on “good enough to start” platforms, and understand why Curated Data and Operational AI Technology are the primary ceiling on your AI‑Native performance.
5. The AI Money Map a prioritized list of investments and measurable outcomes. It is a value-led view of the AI initiative roadmap that connects every dollar of investment to a specific return, helping leaders see past the hype and focus on measurable ROI. The AI Money Map equips leaders to turn AI ambition into a manageable portfolio, aligning investment, ownership, and expected return before execution begins.

Key Outcomes

• Confidently fund and govern AI programs, grounded in a shared AI lexicon for leaders, and aligned with a clear AI Strategic Intent
• See your business through an AI‑Native Organization heatmap, exposing the most critical gaps in strategy, workforce, governance, data, technology, culture, and agility
• Align AI investments with measurable business outcomes using an AI Money Map, a pragmatic Responsible AI Governance & Risk Plan, and prioritized data/platform investments