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SECTION 1: Why AI Governance is Critical and the Tool Spectrum

Three Signals Managers Must Not Ignore

Managerial Perspective: Four Types of Systems in Depth

Decision Tree for Selecting System Type

SECTION 2: Regulatory Framework for Managers (EU AI Act and GDPR)

EU AI Act: EU Regulation and Risk Categories

GDPR and AI Agents in the Czech Environment

GDPR and AI Agents in the Czech Environment File: AI_Agent_Governance_Managers_MASTER_v1.pdf Chapter: GDPR and AI Agents: When it comes to personal data processing

Czech Specifics: UOOU, NUKIB, and COI File: AI_Agent_Governance_Managers_MASTER_v1.pdf Chapter: Czech Specifics: UOOU and NUKIB

SECTION 3: Four Pillars of Secure AI Governance

Pillar 1: Scope Rules — How to Define Agent Boundaries

Pillars 2 and 3: Audit Log and Human-in-the-Loop

Pillar 4: Escalation — When the Agent Must Stop

SECTION 4: Data Protection, Liability, and Cost Management

Data Protection and Responsibility Matrix (RACI)

Token Spiraling and Cost Limits

SECTION 5: Data Protection, Accountability, and Cost Management. Principle of Data Minimization and AI Agent Permission Matrix. File: AI_Agent_Governance_Managers_MASTER_v1.pdf Chapter: Principle of Data Minimization for AI Agents. Role and Responsibility Matrix (RACI for AI Governance). File: AI_Agent_Governance_Managers_MASTER_v1.pdf Chapter: Role and Responsibility Matrix (RACI for AI Governance). Token Spiraling and Cost Limits. File: AI_Agent_Governance_Managers_MASTER_v1.pdf Chapter: Token Spiraling: How an Agent Can Exhaust a Monthly Budget in an Hour

SECTION 6: Implementation: Risks, Code of Conduct, and Pilot Plan

Risk Register and Warning Signals

AI Code of Conduct for the Organization

30-Day Pilot Plan for Safe AI Agent Implementation

Glossary of Key Terms

SECTION 7: Scenario Quizzes (Knowledge Verification)

SECTION 7S: Practical Governance Scenarios in Real Situations Scenario 1: NGO implements an AI agent for beneficiary support Scenario 2: Small business deploys an AI agent for email processing Scenario 3: Consulting team implements a multi-agent system for research reports

Quiz 1: Selecting a Suitable AI System

Quiz 2: Risk Assessment and the EU AI Act

Quiz 3: Defining Scope Rules

Quiz 4: Correct Use of Human-in-the-Loop

Quiz 5: Handling Crisis Escalation

Quiz 6: Data Minimization in Practice

Quiz 7: Protection Against Token Spiraling

Quiz 8: Managing a 30-Day Pilot

SECTION 8: Final Feedback and Survey

Survey 1: Assessing Your Organization's Readiness

Survey 2: Course Feedback and Implementation Plans

AI Habits and Skills Summary

AI Development

Summary

Enter a new era of management where you no longer manage only people, but also autonomous AI agents. The course "Safe Management of AI Agents and Autonomous Workflows for Managers" is designed specifically for executives, project managers, and innovators who want to safely and effectively integrate artificial intelligence into corporate processes.

Enter a new era of management where you no longer manage only people, but also autonomous AI agents. The course "Safe Management of AI Agents and Autonomous Workflows for Managers" is designed specifically for executives, project managers, and innovators who want to safely and effectively integrate artificial intelligence into corporate processes. With the rapid rise of AI agents comes huge potential for automation and productivity gains, but also entirely new risks. From unintentional leaks of sensitive data to "Token Spiraling" (uncontrolled generation of massive costs) to violations of strict regulations such as GDPR or the newly introduced EU AI Act. In this comprehensive and practically oriented course, you will learn how to actively prevent these threats. You will gain proven tools for AI governance, understand the key differences between common chatbots, RPA automation, and advanced multi-agent systems. You will learn how to apply the four pillars of safe AI in practice: Scope Rules, Audit Log, Human-in-the-Loop, and Escalation Rules. The course will guide you in detail through creating a Responsibility Assignment Matrix (RACI) for AI, setting strict cost limits, and preparing a 30-day pilot plan for the safe deployment of an AI agent in your organization. Gain confidence in managing modern hybrid teams, minimize risks, and become a confident leader in the safe implementation of artificial intelligence!

Copy of Secure Management of AI Agents and Autonomous Workflows for Managers

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            <p>V éře rychlého technologického pokroku se role manažera zásadně transformuje z vedení čistě lidských týmů na řízení hybridních struktur, kde klíčovou roli hrají autonomní AI agenti a komplexní workflow. Tento přechod přináší nejen zvýšení efektivity, ale i zcela nové typy rizik, které vyžadují systematický přístup k AI governance. Porozumění rozdílům mezi chatboty, RPA automatizací a multi-agentními systémy je nezbytným předpokladem pro každého vedoucího pracovníka, který nese odpovědnost za výstupy těchto systémů. Bezpečné nasazení umělé inteligence v organizaci již není pouze technickou otázkou, ale kritickou manažerskou kompetencí, která spojuje strategické rozhodování s etickou a právní odpovědností za autonomní jednání strojů.</p>

<p>Tento kurz poskytuje ucelený rámec pro bezpečné řízení AI agentů, přičemž klade důraz na soulad s aktuální legislativou, jako je EU AI Act a GDPR, a zohledňuje specifika českého regulatorního prostředí reprezentovaného úřady ÚOOÚ či NÚKIB. Účastníci se seznámí se čtyřmi pilíři bezpečné governance – od definování pravidel rozsahu (Scope Rules) a implementace mechanismů Human-in-the-Loop až po efektivní krizovou eskalaci a kontrolu nákladů spojených s rizikem takzvaného „token spiralingu“. Cílem je vybavit manažery, ředitele neziskových organizací i majitele firem praktickými nástroji, jako je matice RACI pro AI nebo strukturovaný 30denní pilotní plán, které umožní transformovat teoretické znalosti v bezpečný a ekonomicky udržitelný provoz autonomních systémů bez nutnosti hlubokých programátorských znalostí.</p>
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