How to implement AI in an organization without chaos, unnecessary costs, and security risks
AI Opportunities, Roadmap, and Real-World Examples from Mid-Sized and Large Companies
Why participate?
Our webinar will show you how to practically implement AI in mid-sized and large companies. Gain a clear roadmap, answers to key questions regarding security and costs, and real-world examples of successful implementations.
What will you take away?
You will learn how to build an effective AI strategy, how to address security and data governance, and how to optimize costs — including where hidden costs may arise. We will also focus on how and where to use internal AI agents. In addition, we will present real projects we have delivered for our clients.Speakers
ROBERT ŠROTÝŘ
Chief Business Officer
EMARK
Pavol Hajastek
Chief Technology Officer
EMARK
Tomáš Janotík
Cloud Data Architect
EMARK
What Will We Cover in One Hour?
- An overview of AI trends and the opportunities they bring.
- A guide to building a realistic and effective AI roadmap.
- Answers to questions about security and data governance.
- How and Why to Build Internal AI Agents.
- Practical demonstrations of EMARK project implementations.
- Estimated costs for your specific use cases.
Who Is the Webinar Intended For?
- For business leaders of mid-sized and large companies.
- For CIOs, CTOs, CDOs, and managers who want to use AI to increase their teams’ efficiency and gain a competitive advantage.
Webinar program
The Old World vs. the World of AI
- How artificial intelligence is changing the rules of the game.
- Trends and predictions for 2025 and beyond.
- Tools that until recently were available only to large corporations or “supercomputers” are now accessible to all of us.
How to Build an AI Strategy
- Security and data governance – How to protect sensitive information when working with AI. A comparison of the Snowflake, BigQuery, and Azure platforms. Security differences between GPT-4.0 and Gemini 2.5 Pro.
- Costs – How much it costs to scale AI solutions. The advantages of the cloud model vs. local infrastructure and transitioning between them. How to optimize costs when using LLM APIs.
- Internal AI agents – How to choose the right platform and architecture for your needs.
AI in Action – Experiences from Our AI Projects
Case studies from mid-sized and large companies.
- How to address security and data governance challenges.
- Selecting the most suitable cloud platform for specific scenarios.
- Examples of working with LLMs and deploying them in practice.
- Estimated costs for various usage scenarios.
Discussion and Q&A
Space for your questions and our answers