Training objectives
· Understanding the fundamentals of Artificial Intelligence (AI) – introducing participants to key concepts, algorithms and AI tools (machine learning, natural language processing, deep learning).
· Exploring areas of AI application within the company – identifying specific processes and departments (sales, marketing, logistics, HR, customer service) where AI can deliver measurable business outcomes.
- · Acquiring practical project skills – learning how to plan, prepare and implement an AI project in an organization (from needs and data analysis, through prototyping to measuring results).
- · Raising awareness of challenges and risks – familiarizing with core issues such as AI ethics, risk management, legal and regulatory aspects and implementation barriers.
- · Inspiring further development – presenting current trends and innovations in AI to help participants continue their growth and effectively apply the acquired knowledge in practice.
- · After the training, participants will be able to:
- - Introduce concrete AI-based solutions.
- - Use cloud platforms and AI tools consciously.
- - Collaborate more effectively between business and IT/data science teams.
- - Avoid common implementation mistakes and barriers.
Estimated contribution of the practical part: 55%
Duration: 2 days for 8 h
Programme and exercises:
Day 1: Foundations of AI and Business Applications
- Introduction to AI in Business
- Common Types of AI in Business Context
- Main Areas of AI Application in Companies
- Case Studies: AI Use Across Industries
- Workshop: AI Opportunity Mapping in Your Organization
Day 2: Managing AI Projects, Challenges, and Competence Development
- From Business Needs to AI Projects
- AI Project Lifecycle in Business
- Managing Risks and Implementation Challenges
- Ethics, Regulations and Responsibility in AI Projects
- Tools and Platforms Supporting AI Deployment
- Overview of no-code/low-code solutions for business.
- Intro to cloud platforms facilitating AI deployment.
- When to build custom solutions vs to use off-the-shelf services?
- Trends and the Future of AI in Business
- Growth of Generative AI and its impact on business processes.
- Multimodal models and AI using multiple data types (text, image, video).
- Rising importance of Edge and Operational AI.
- How AI is transforming business models and workforce competencies.
- Final Workshop: Creating Your Company’s AI Development Map
- Drafting an initial AI strategy for your organization.
- Identifying required competencies and first steps.
- Planning personal and team development paths in AI.
Exercises Include:
- AI project simulation – designing an AI-based project concept.
- Case study: chatbot implementation analysis.
- Risk and barrier analysis for AI deployment.
Methodology:
Interactive lecture, hands-on workshops, case studies, Q&A sessions, moderated discussions, group work.
Oferees:
- Managers and executives – responsible for strategic decisions and technology investments.
- Business development and innovation specialists – defining and implementing innovative projects, including AI.
- IT project leaders and data analysts – managing technical aspects and deploying AI models.
- Operational, marketing and sales staff – seeking ways to improve efficiency and optimize processes using AI.
- Anyone interested in AI – including those without programming experience, looking to expand their knowledge of emerging technologies.
Application:
Application:
AI-based solutions can bring many benefits to organizations, such as:
- Process automation and cost reduction.
- Personalized sales offers and increased revenue.
- Better data analysis and decision-making support.
- Optimization of logistics and production processes.
- Improved customer service (chatbots, recommendation systems).
Through this training, organizations gain the knowledge to effectively plan, implement, and evaluate AI-related projects – creating real competitive advantage.
