Courses with lecturer
You bought the licences, sent employees a link to Copilot and expected AI adoption to take off on its own. A few weeks later, the initial enthusiasm fades, half the team goes back to their old ways of working, and you are left wondering whether the problem is the tool, the people, or simply the lack of a clear plan. This course addresses exactly that — not how to configure AI technically, but how to introduce it so that people actually use it.
AI Change Manager is a three-day course for managers, team leaders and specialists responsible for AI implementation. It teaches you how to approach AI adoption as a managed organisational change — with clear rules, communication and measurable results, rather than simply deploying a new tool.
The course is built around a real situation you may already be facing — AI tools are available, management expects results, but there is no consistent approach:
Find out why people are not using AI even when they have access to it — recognise whether the issue is lack of trust, fear of monitoring or simply unclear expectations, and choose the right response.
Map the people in your organisation — who will support the change, who may resist it and who is likely to ignore it — and prepare communication tailored to each group.
Establish basic rules for AI use — how to handle data, when outputs must be checked and who is accountable — so that the rules are clear to employees and defensible from a security and compliance perspective.
Learn how to measure whether adoption is actually working — not simply how many people opened the tool, but whether the way they work has genuinely changed.
Deal with challenging situations after deployment — concerns about data, incorrect AI outputs or resistance from managers — and defend your adoption plan in a final simulation in front of a model leadership team.
You will not leave the course with just notes. You will build a practical toolkit — an adoption plan, stakeholder map, communication scenarios and success metrics — ready to use for a scenario from your own organisation.
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 is a certified Prosci Advanced Instructor in change management — the very discipline where AI adoption initiatives most often struggle — as well as an ISO/IEC 42001 auditor for AI management systems. This allows him to connect the people side of AI adoption with governance and responsible AI management. Before moving into AI, he managed investment planning in a company with more than one billion dollars in revenue, giving him practical experience in presenting and defending major initiatives to senior management.
The course goes beyond the surface. The three days follow a clear logic: why AI changes the way people work → how to establish trust and clear rules → how to manage adoption and measure its impact. The course concludes with a practical simulation under pressure rather than a paper-based test.
The course complements the Copilot training series — Basic, Advanced Features, Copilot Studio and Microsoft 365 Copilot. If your team already knows how to use Copilot from a technical perspective, AI Change Manager adds the management and change-management layer that is often missing from successful adoption.
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. More information about this course can be found here.
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.
The course is designed for managers, team leaders, HR and L&D professionals, AI ambassadors, and specialists in IT, security or compliance who influence whether AI is successfully adopted across the organization.
Yes. The course does not focus on technical skills. Instead, it focuses on change management, communication and the practical adoption of AI within an organization.
Participants will create their own practical toolkit for managing AI adoption – including an adoption plan, stakeholder map, communication scenarios and success metrics for a selected scenario from their own organization.
Usually not because of the technology itself, but because of an unclear purpose, insufficient communication, employee concerns and weak ownership of the change.
The course teaches participants to distinguish user activity from genuine behavioral change and to define adoption, quality and impact metrics that can be clearly demonstrated to management.
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.
