Course: Digital Management and AI
A course on management dashboards, data quality, BI, 1C, CRM, task management, integrations and executive use of AI.
The exact duration and depth of review depend on the selected plan and participant group.Every program includes practical assignments, a capstone project and an implementation plan.
PRACTICAL FORMAT
Participants build an implementation-ready management solution for their own company
Each topic follows the same cycle: assessment, concise lessons, a case study, a template, an assignment, review, and an implementation action.
WHEN THIS COURSE IS NEEDED
Common problems in “Digital Management and AI”
The course is suitable when the relevant management constraint has been identified and the company needs to build a specific management capability.
Systems are not connected
Data is duplicated across 1C, CRM, spreadsheets, and the task-management system.
Dashboards show incorrect figures
There are no shared master-data definitions, calculation rules, or accountable data owners.
Chaos is automated
A digital tool is implemented before the management logic is defined.
Executives compile reports manually
Time is spent preparing information rather than making decisions.
AI is used through isolated experiments
There are no prioritized AI use cases, data-governance rules, or methods for measuring impact.
No one is accountable for the digital management environment
No designated owner is responsible for integrations and data quality.
PROGRAM
Core topics of the “Digital Management and AI” course
Each topic includes a current-state assessment, the underlying methodology, a practical template, and an assignment using the participant’s company as the case.
Management data map
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
Data quality
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
Management dashboards
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
BI tools
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
1C and accounting systems
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
CRM and task management
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
Integrations
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
Executive AI use cases
How the management tool works, common mistakes to avoid, and how to apply it in your company.
- topic assessment
- practical template
- implementation action
CAPSTONE PROJECT
Choose a plan →Deliverables for “Digital Management and AI”
Participants do not create a classroom exercise; they produce a set of documents ready for implementation in their own company.
Data source map
Systems, metrics, owners and quality requirements.
Systems architecture
Defined roles for 1C, CRM, task management, BI, and integration services.
AI use cases
Priority challenges, data, constraints and success criteria.
Digitalization plan
Implementation sequence and milestones.
HOW THE LEARNING PROCESS WORKS
The same structure for every module
The module structure turns each topic into an implementation-ready document that contributes directly to the capstone project.
Current-state assessment
How the area operates today, what is already in place, and what outcome is required.
checklist · starting point
Core theory
Three to five concise lessons covering the logic, common mistakes, recommended sequence, and an example.
lessons · methodology
Practical case study
A comparison of effective and ineffective approaches using a real or representative company case.
case study · management logic
Practical template
A practical template such as a goal map, KPI framework, cash-flow statement, RACI matrix, procedure, task, or process map.
template · completed example
Practical assignment
Participants apply the material to their own company and submit the completed work.
practice · company document
Self-assessment
A self-check covering terminology, the underlying logic, and the correct sequence of actions.
test · comprehension check
Implementation action
A specific next step required to implement the solution in the company.
implementation · next step
Link to the capstone project
Each module deliverable becomes part of the company’s management-system project.
summary · capstone projectPARTICIPATION FORMATS
One course, five levels of support
The educational core is the same. The format is selected according to the complexity of the challenge and the amount of feedback required.
WHAT PARTICIPANTS RECEIVE
Course deliverables can be applied in the company
The project scope depends on the starting situation and selected plan.
Data source map
Systems, metrics, owners and quality requirements.
Systems architecture
Defined roles for 1C, CRM, task management, BI, and integration services.
AI use cases
Priority challenges, data, constraints and success criteria.
Digitalization plan
Implementation sequence and milestones.
Review and refinement
On supported plans, participants receive feedback on assignments and refine their documents.
Implementation plan
The capstone project is converted into actions, deadlines, owners and milestones.
LEARNING PATH
From assessment to implementation
Five stages connect the learning process to the company’s practical challenge.
1
Current-state assessment
We document the current state, key problems, and required outcome.
2
Understand the management logic
Concise lessons, common mistakes, sequence of actions and case studies.
3
Develop implementation-ready documents
Participants complete the templates using their company’s data.
4
Review and refinement
Self-assessment, program coordinator feedback or expert review, depending on the selected plan.
5
Project and implementation plan
The materials are consolidated into an integrated solution and a 90-day roadmap.
COURSE DELIVERABLE
“Digital Management and AI” project
Data source map
Systems, metrics, owners and quality requirements.
Systems architecture
Defined roles for 1C, CRM, task management, BI, and integration services.
AI use cases
Priority challenges, data, constraints and success criteria.
Digitalization plan
Implementation sequence and milestones.
NEXT STEP
Choose a format for the “Digital Management and AI” course
The curriculum is the same across formats. The differences lie in the schedule, depth of review, mentor involvement, individual support, and team implementation support.
- self-paced learning
- guided course
- mentor-led group
Start a business assessment
The format is selected based on the management challenge, the required depth of support, and the participants involved.