AI Integration: How to Implement Generative AI in Your Company and Team
Course Objective
To teach managers and teams how to systematically implement generative AI into work processes, rather than just using isolated AI tools.
Participants will go from identifying business tasks where AI can create the most value, to developing an AI strategy, selecting tools, preparing the team, implementing AI use cases, and evaluating the business impact.
The course is built from the perspective of business consulting and change management, rather than technical training on a specific AI service.
Who is this course for?
The program will be useful for:
- business owners and top managers;
- heads of departments and functional areas;
- HR and L&D managers;
- heads of IT and Digital departments;
- Product, Project, and Operations Managers;
- AI Champions and internal agents of AI transformation;
- teams that are already experimenting with GenAI and want to move to systematic use.
What will you get from the course?
Program
- What is Generative AI and how is it changing business models and workflows
- AI as a productivity, automation and decision-making tool
- Where AI really creates business value, and where its implementation does not make sense
- The main scenarios of using GenAI in modern companies
- AI Adoption vs AI Transformation
- Typical mistakes of companies at the start of AI transformation
- How to determine a company's AI-readiness
Practice: initial assessment of AI-maturity of the company / team.
- How to find processes and tasks worth enhancing with AI
- Map of processes and AI opportunities
- Identification of repetitive, knowledge-intensive and decision-making tasks
- Use cases for HR, marketing, sales, finance, IT, operations and management
- How to assess the potential value of AI initiatives
- Matrix Impact × Effort
- Selection of priority AI Use Cases
Practice: creating a portfolio of AI Use Cases for the company.
- How to form an AI Vision
- AI implementation goals
- AI Roadmap
- Priorities: quick wins and strategic initiatives
- Build / Buy / Integrate: how to choose an approach
- Identifying those responsible for AI initiatives
- Formation of AI Center of Excellence / AI Champions
- How to connect AI initiatives with business goals
Practice: creation of the company's AI Roadmap.
- An overview of the current Generative AI ecosystem
- ChatGPT, Claude, Gemini and other AI platforms
- AI for text, data analysis, presentations, research and content
- AI Agents and Automation
- AI in enterprise systems
- How to choose an AI tool for a specific business case
- Free vs corporate solutions
- Evaluation criteria for AI solutions: quality, security, integration, cost, scalability
Practice: choosing an AI stack for a specific business case.
- How to redesign workflows with AI in mind
- AI-augmented employee: how the role of a specialist is changing
- AI for communication, analysis, document preparation and decision making
- AI Copilot approach
- Prompting as a basic skill for working with AI
- Creation of corporate AI assistants
- How to move from single experiments to standard AI practices
Practice: redesign of one workflow in principle Human + AI.
- What are AI Agents?
- How AI Agent differs from a regular chatbot
- What processes should be automated
- Agentic workflows
- AI + automation
- Examples of automation of business processes
- When automation creates value and when it creates unnecessary complexity
- Human-in-the-loop
Practice: designing an AI-enabled workflow for your own business process.
- What data can and cannot be shared with AI
- Confidential Data and corporate information
- Privacy та data protection
- Hallucinations and quality control
- Copyright and intellectual property
- AI Bias
- Shadow AI: risks of uncontrolled use of AI by employees
- AI Governance
- Creation of Corporate AI Policy
Practice: development of basic rules for the safe use of AI in the company.
- Why do employees resist the introduction of AI
- Implementation of artificial intelligence as change management
- Fear of changing jobs
- How to communicate AI transformation to the team
- Formation of AI culture
- AI Champions in the company
- Training and upskilling of employees
- How to create an environment for experiments
- How to scale successful AI practices
Practice: AI Adoption plan for teams.
- How to run AI Pilot
- MVP for AI initiatives
- Determination of success criteria
- Pilot → evaluation → scaling
- What to do with failed AI experiments
- Change management
- Communication of results
- Scaling AI solutions across teams and departments
Practice: development of AI Pilot for own company.
- How to prove the value of AI to management
- AI Metrics also KPIs
- Saving time
- Reduction of operating costs
- Productivity growth
- Quality and speed of decision-making
- Revenue impact
- Cost of AI adoption
- Calculating the ROI of AI initiatives
- Dashboard AI-Metric
Practice: calculation of potential ROI of own AI Use Case.
- Determination of priority AI initiatives
- Quick Wins
- Pilot projects
- Team training
- Responsible and resources
- Metrics
- Risks
- Communication plan
- 30/60/90-day AI Adoption Plan
Practice: creating a personal 90-Day AI Adoption Plan.
Education provides
