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
- AI Adoption Roadmap Canvas
- Skills & Internal Training Blueprint
- Governance Starter Pack (principles, HITL, agent guardrails)
- Pilot Portfolio Template
- Sponsor Brief Template
- 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