Courses with lecturer
AI experiments are multiplying across the organization — one team is testing a chatbot, another is automating reports, while a third has purchased its own tool independently. Nobody really knows which initiatives deliver genuine value, who owns them, or how to justify them to management or the legal department. This course shows you how to turn scattered experiments into a managed initiative with clear ownership, metrics and rules.
AI Transformation Manager is a four-day advanced course for managers who lead or coordinate AI initiatives across an organization — from identifying the right opportunities through pilots and adoption to governance and measurable impact.
The course takes you through the entire lifecycle of an AI initiative, rather than focusing on just one part of it:
Learn to identify where AI can deliver genuine value and where it is simply a fashionable experiment without a meaningful business benefit.
Decide between an off-the-shelf tool, an AI agent or custom development based on your data, its availability and sensitivity — rather than on what happens to be trending.
Define a clear objective, scope, owner and success criteria so that your pilot becomes a meaningful step towards implementation rather than an isolated experiment.
Set rules covering the EU AI Act, GDPR and NIS2 that can stand up to scrutiny from legal and security teams — explained from a management perspective without unnecessary legal jargon.
Learn to measure adoption, output quality and genuine business impact — not simply how many people have tried the tool.
A practical toolkit — including an AI opportunity map, prioritization matrix, pilot proposal, governance checklist and metrics — ready to use in your organization.
The course is led by Michal Kolomazník, Agile Coach and Principal Project Manager at Microsoft, where he leads an AI transformation portfolio with a team of more than 70 people. He combines hands-on experience deploying AI solutions into production with ISO/IEC 42001 certification in AI governance and previous experience as a financial manager who personally presented investment proposals to the leadership of a billion-dollar company. This allows him to approach AI initiatives from business, technology and risk perspectives at the same time.
The course builds on the Copilot course series (Basic, Advanced Features, Copilot Studio and Microsoft 365 Copilot) as well as the AI Change Manager course.
Both courses are taught by the same instructor and address related challenges, but their scope and focus are different.
Covers the entire lifecycle of an AI initiative — from opportunity identification and feasibility through the pilot to adoption, governance and impact measurement. Choose this course if you need to decide where your organization should use AI and how to manage the initiative as a whole.
Goes deeper into AI adoption itself — changing work habits, communication, building trust and overcoming resistance. Choose this course if you already know what you are implementing but need to ensure that people actually adopt and use the solution. More information about this course can be found here.
For managers, project and programme leaders, business owners, HR professionals and governance specialists who need to prepare, coordinate and evaluate AI initiatives.
No. Technology-related topics are explained from a management perspective and in the context of decision-making and their impact on the organisation.
This course covers the entire lifecycle of an AI initiative, including opportunity selection, feasibility and governance, while the AI Change Manager course focuses more deeply on changing working habits, building trust and driving AI adoption among people.
A practical toolkit including an AI opportunity map, prioritisation matrix, pilot proposal, governance checklist and metrics for evaluating impact within their own organisation.
Yes. Day 4 focuses on governance and key regulatory topics such as the AI Act, GDPR and NIS2, always from a practical management perspective without unnecessary legal jargon.
Michal currently works at Microsoft as an Agile Coach & Principal Project Manager & PCAI, where he leads an AI transformation portfolio with a team of over 70 people. He was at the birth of the Business Value Program and for his work he received the Microsoft SPARK Award and inclusion in the Platinum Club (reserved for the 200 most influential people within Microsoft).
Michal is not “just” a technical specialist or “just” a manager, but he can connect both levels:
HubSpot is an American software development company. It has 8,000 employees and branches in several countries around the world. Processes related to lead generation and qualification were time-consuming and not always efficient, reducing sales productivity.
AI in practice: DHL has accelerated the delivery of parcels
DHL is one of the largest logistics companies in the world. It provides transportation and delivery of parcels in many countries. However, route planning, warehouse management and demand forecasting were difficult and often inefficient.
Microsoft, a global tech giant, faced challenges with its complex financial processes, which involved extensive financial planning and analysis (FP&A). Traditional methods were time-consuming and sometimes inaccurate, leading to delayed decisions and potential financial risks.
HubSpot is an American software development company. It has 8,000 employees and branches in several countries around the world. Processes related to lead generation and qualification were time-consuming and not always efficient, reducing sales productivity.
AI in practice: DHL has accelerated the delivery of parcels
DHL is one of the largest logistics companies in the world. It provides transportation and delivery of parcels in many countries. However, route planning, warehouse management and demand forecasting were difficult and often inefficient.
Microsoft, a global tech giant, faced challenges with its complex financial processes, which involved extensive financial planning and analysis (FP&A). Traditional methods were time-consuming and sometimes inaccurate, leading to delayed decisions and potential financial risks.
