World Congress 2026 Europe - Virtual Stage Jul 2, 2026 Session details

From Shadow AI to Secure Intelligence: Safe AI Usage in the Enterprise

Péter Farkas

Is shadow AI quietly exposing your sensitive enterprise data through innocent-looking prompts? Learn how to implement a dynamic control plane to secure complex agentic workflows.

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#1 about 2 min

Balancing rapid AI adoption with enterprise governance

Unregulated productivity tools create security and compliance challenges in sensitive enterprise workflows.

#2 about 3 min

Risks of invisible shadow AI usage in development

Unapproved AI tools lead to data leaks and a lack of organizational visibility.

#3 about 3 min

Why traditional security fails against large language models

AI systems interpret intent and context instead of static patterns, exposing new prompt injection surfaces.

#4 about 2 min

Designing an AI control plane for enterprise interactions

A centralized gateway connects security, policy, and runtime behavior to evaluate AI requests.

#5 about 7 min

Implementing core components of an AI control plane

Applying programmatic identity, dynamic enforcement, and semantic logging makes workflows auditable and secure.

#6 about 2 min

Shifting security models from passive chatbots to active agents

Autonomous agents that call tools and execute decisions transform AI into a critical infrastructure risk.

#7 about 4 min

Securing agent tool access against authorization failures

Giving models access to internal APIs turns prompt injections from content safety into action vulnerabilities.

#8 about 2 min

Defining action-level authorization boundaries for AI agents

Security systems must evaluate specific agent operations rather than just granting blanket tool access.

#9 about 3 min

Enforcing runtime boundaries during agent execution workflows

Separating model reasoning from security decisions ensures agents only perform explicitly permitted actions.

#10 about 2 min

Implementing risk-based human approvals in agent workflows

High-risk autonomous actions require targeted human oversight without creating excessive execution friction.

#11 about 4 min

Reconstructing agent behaviors through execution traceability

Semantic logging and chain-of-action auditing transform autonomous decisions into observable enterprise artifacts.

#12 about 3 min

Controlling enterprise knowledge access in retrieval-augmented workflows

RAG architectures must enforce document-level permissions and metadata controls to prevent sensitive data leakage.

#13 about 3 min

Choosing between managed AI platforms and custom governance

Deciding whether to adopt hyperscaler controls or build proprietary layers depends deeply on specific compliance needs.

#14 about 2 min

Establishing runtime governance for scalable enterprise AI systems

Shifting from static policies to dynamic runtime enforcement ensures models safely integrate into operational architecture.

Matching moments

3:33 min

Managing shadow ai adoption and enterprise data leakage

Kai Grunwitz Kai Grunwitz +2 · WWC 2025

2:43 min

Setting effective guardrails for enterprise agentic AI adoption

Julia Kordick Julia Kordick · Coffee With Developers

2:42 min

Managing the spread and security risks of shadow AI

Maish Saidel-Keesing Maish Saidel-Keesing · WWC 2025

3:08 min

Understanding the landscape of AI capabilities and risks

Balázs Kiss · WWC 2023

4:15 min

Security integration and AI skepticism in developer tooling

Chris Heilmann +2 · LIVE

44 sec

Addressing corporate compliance challenges with secure enterprise AI

Hissan Usmani Hissan Usmani · WWC 2025

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