AIPTDEst. 1995
Workshop · AI for Managers

Practical AI For Managers And Team Leaders

Where strategy meets execution. The conceptual foundation, practical frameworks, and operational vocabulary working managers need to lead AI adoption at the team level: tool evaluation, workflow redesign, change management, and measuring return.


Managers are the layer of the organization where AI strategy meets execution. Whether you are evaluating a new AI-enabled tool, redesigning a workflow, retraining a team, or interviewing a candidate whose résumé reads differently than it would have two years ago, your ability to make sound decisions about AI shapes your team's effectiveness and your organization's pace of adoption.

This workshop equips working managers with the conceptual foundation, practical frameworks, and operational vocabulary needed to lead AI adoption at the team level. Through a combination of interactive instruction, AI-powered exercises, and case discussions with fellow participants, participants build skills they can apply immediately to their team's workflows, hiring, and planning.

Choosing a tool is the smallest part of AI adoption. The durable skills are design, change management, and judgment, and they benefit from structured practice.


Participants will learn AI management techniques to:

  • Identify high-leverage AI applications in your function or workflow
  • Evaluate AI vendor claims and product roadmaps with technical and economic literacy
  • Design AI-augmented workflows that integrate cleanly with existing processes
  • Lead change management for AI adoption, including hiring, training, and team structure
  • Implement appropriate guardrails for safety, audit, and accountability
  • Measure the return on AI investments using metrics meaningful to your function

Topic Outline

Six Modules

Delivered as a two-day workshop · three modules per day

Module 01Foundations

Foundations: AI for the Working Manager

  • What AI is, and how this wave differs from prior automation
  • Algorithms, compute, and data: the three necessary conditions
  • A framework for evaluating any AI application
  • Reading the AI news and separating signal from noise
Module 02How AI Works

How AI Works: Intuition Without the Jargon

  • Neural networks, transformers, and the attention mechanism
  • The training pipeline: pre-training, fine-tuning, and reinforcement learning from human feedback
  • Where AI models reliably succeed and where they predictably fail
Module 03The Stack

The Modern AI Stack: What to Deploy and When

  • Prompts, retrieval-augmented generation, fine-tuning, and agents
  • Build versus buy at the team level
  • When AI scales economically and when it does not
Module 04Workflow Redesign

Agentic AI and Workflow Redesign

  • The transition from copilots to agents
  • Mapping team workflows for AI augmentation
  • Tool use, the Model Context Protocol, and integration with existing systems
Module 05Adoption

Adoption, Change Management, and Team Upskilling

  • Why most AI pilots stall, and what successful ones share
  • Building an AI-fluent team: hiring, training, and role design
  • Measuring AI return on investment in practice
Module 06Governance

Governance, Risk, and What Comes Next

  • Practical governance for AI-augmented teams
  • Audit trails, traceability, and human-in-the-loop design
  • A capstone exercise building an AI adoption plan for your team

Upcoming Sessions

Cohort 01Live online

October 13 & 14, 2026

Schedule
9:00 AM – 4:00 PM PST
Tuition
US$1,950
Instructors
Adam Keppler
Cohort 02Live online

February 9 & 10, 2027

Schedule
9:00 AM – 4:00 PM PST
Tuition
US$1,950
Instructors
Adam Keppler

Programs can be customized for your organization. Delivered on-site, in-person, live-online, or asynchronously as a course library.
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