Leading AI Adoption

Enterprise AI Adoption & AI Transformation Training

Lead the system — not just the tools.

Leading AI Adoption is a practical enterprise AI adoption and AI transformation training for people who must turn “everyone use AI” into a governed, measurable program. Licenses and demos are not adoption. Real AI change management means outcomes, roles, skills, processes, AI pilot projects, and guardrails that outlast the hype.

This is not a coding course. It is not “generative AI for executives” (that exists separately). This course is for people who own AI adoption: AI strategy, AI readiness, internal AI upskilling / AI literacy, redesign of work, AI governance, responsible AI, and agentic AI oversight — while the AI operating model shifts.

Sometimes project context is enough to start. Sometimes you must build a shared ontology — a clear domain structure so teams, tools, and agents mean the same things. You will learn when each path is right.

You leave with what the organization must build: training program, skills map, operating model, pilot portfolio — and how to lead generative AI adoption without burnout or shadow AI chaos.

Instructor Yevhen Musiienko (Eugene Musienko), PMP
Duration 2 days
Participants 8–16
Language English, Ukrainian, or Russian

Target Audience

For leaders and change agents who make AI in the enterprise work across teams — not only personal productivity.

  • Transformation leads, agile coaches, Scrum Masters owning AI adoption
  • PMO / delivery leaders coordinating AI initiatives (AI for PMO)
  • Heads of digital, innovation, or operations launching company-wide AI programs
  • Program and project managers connecting AI strategy with delivery
  • HR / L&D designing AI upskilling and internal AI literacy programs
  • Risk, compliance, and knowledge managers needing usable AI governance and responsible AI
  • Product and engineering managers preparing AI-augmented ways of working

No deep technical AI background required.

Knowledge and Skills Acquired

Participants will understand:

  • What enterprise AI adoption really is — and why “give everyone a license” fails
  • Personal AI vs AI at the core of the workflow
  • When project context is enough vs when you need a full ontology for the domain
  • Skills, technologies, and internal training programs the organization must build
  • New and changing roles, responsibilities, and people impact
  • Governing principles: ethics, human-in-the-loop AI, risk, data, and agent oversight
  • How to choose tools by context — not by hype
  • How AI agents and agentic workflows change delivery — and how to govern them

Participants will be able to:

  • Design an AI adoption roadmap (ambition → pilots → scale)
  • Split the portfolio: try AI / fix flow first / not yet
  • Build a skills and AI upskilling plan for teams
  • Define roles, RACI, and cadence for the AI operating model
  • Apply human-in-the-loop and ethical guardrails to real use cases
  • Structure an AI pilot portfolio with metrics and keep / pivot / stop
  • Brief sponsors on authority, steering, and funding

Main Topics

Module 1: Understanding AI Transformation (Not Tool Rollout)

  • Why “10× faster” is not a business outcome
  • Personal AI vs core AI workflows
  • Adoption vs experiments vs shadow AI
  • AI readiness — what “done” looks like in year one

Module 2: Use Cases — Good Fits and Bad Fits

  • Where AI wins: documentation, text, research, synthesis, contained workflows
  • Where AI fails early: multi-team value streams with long handovers
  • Case pattern: multi-agent documentation review + human final approval
  • How to say “not yet” without blocking the company

Module 3: Skills, Technology, Ontology, and Internal Training

  • Skills map: leaders, PMs, delivery teams, specialists
  • AI literacy first; then workflow design and data boundaries
  • Building an internal AI training curriculum and practice loops
  • Project context vs building a shared ontology for agents and teams
  • Tool landscape: chat tools vs agentic AI and automation
  • Selecting tools by context vs enterprise platform decisions

Module 4: New Roles, New Processes, People Impact

  • Role shifts under AI
  • Processes with AI in the core of delivery
  • Upskilling, redeployment, honest talk about job change
  • AI change management: sponsorship, resistance, trust

Module 5: AI Governance, Ethics, Human-in-the-Loop, Agents

  • AI governance principles you can adopt (not poster ethics)
  • Responsible AI and human-in-the-loop design
  • AI agents and multi-step agentic workflows — value and control points
  • Risk, data classes, approved tools, stop rules
  • Steering cadence (1 hour max) and decision rights

Module 6: Leading Adoption Across the Organization

  • Ambition and measurable outcomes
  • Parallel AI pilot projects vs one hero pilot
  • Transformation metrics and pilot metrics
  • From pilots to funding value streams
  • Workshop: company AI adoption one-pager + 90-day plan

Deliverables

  1. AI Adoption Roadmap Canvas
  2. Skills & Internal Training Blueprint
  3. Governance Starter Pack (principles, HITL, agent guardrails)
  4. Pilot Portfolio Template
  5. Sponsor Brief Template
  6. Certificate of Completion

Optional follow-up consultation (not included in price).

Related Trainings

Training Focus
Generative AI for Leaders & Executives Executive GenAI literacy and tools
Leading AI Adoption (this course) Enterprise AI adoption system
Leading AI Projects Deliver one AI initiative end-to-end

Booking

PMDoc.ua/Contacts · Instructor Yevhen Musiienko: +380 (67) 980-2577 · nitoiti@gmail.com · LinkedIn