Webinar Description
Key Takeaways
- Live demonstration of securing Claude AI agents accessing enterprise systems
- Focus on just-in-time credential issuance and runtime policy enforcement
- Addresses risks of AI agents connecting to production databases and cloud services
- Designed for security engineers, platform engineers, and DevOps professionals
- Covers auditability requirements and intent-aware access control
Introduction
Securing AI Agents in Claude with Akeyless is a technical webinar examining how organisations can govern AI agent access to enterprise infrastructure. The session targets security professionals, platform engineers, and DevOps teams grappling with the operational risks that emerge when autonomous AI systems interact with production environments. As enterprises increasingly deploy AI agents to automate workflows across databases, cloud platforms, and SaaS applications, the question of how to enforce appropriate access controls has become pressing. Traditional authentication mechanisms were not designed for non-human actors that make dynamic, context-dependent requests.
About This Event
This virtual demonstration showcases Akeyless Agentic Runtime Authority, a platform designed to broker secure access for AI agents operating within Claude Chat, Cowork, and Claude Code environments. The session is led by platform and solutions engineers who walk through practical implementation scenarios. Rather than theoretical discussion, the webinar provides hands-on examples of how credential management and policy enforcement function in real-world deployments.
Runtime Security for Autonomous AI Systems
The core technical challenge addressed in this session is the inadequacy of static credentials when AI agents require access to sensitive systems. Long-lived secrets present significant risk when embedded in agent configurations or, worse, exposed within prompt contexts where they might be logged or inadvertently disclosed. The demonstration illustrates how just-in-time credential issuance eliminates persistent secrets by generating short-lived, scoped credentials only when an agent requires them.
Runtime policy enforcement adds another layer of governance. Rather than granting broad permissions that an agent might misuse, policies evaluate each access request against defined constraints at the moment of action. This approach enables what Akeyless describes as intent-aware access control, where the system assesses whether a requested operation aligns with the agent’s authorised purpose before permitting execution.
Auditability and Compliance Considerations
Enterprises operating in regulated industries face particular scrutiny regarding automated system access. The webinar addresses how organisations can maintain comprehensive audit trails of AI agent activities, documenting which credentials were issued, what actions were performed, and whether policy constraints were applied. This traceability becomes essential when demonstrating compliance or investigating security incidents involving automated processes.
Keeping credentials outside the large language model context represents a specific architectural consideration. When secrets appear in prompts or conversation histories, they may persist in logs, training data, or model memory in ways that create unintended exposure. The demonstrated approach isolates credential handling from the AI interaction layer entirely.
Who Should Attend
The session is structured for technical practitioners responsible for securing AI deployments within enterprise environments. Security engineers evaluating governance frameworks for AI-driven automation will find relevant implementation guidance. Platform engineers and solutions architects designing infrastructure that incorporates Claude AI agents can assess how secrets management integrates with their existing toolchains. DevOps teams and IT managers concerned with maintaining operational controls as AI adoption accelerates will benefit from understanding the policy enforcement mechanisms demonstrated.
Organisations with sensitive data, complex infrastructure, or regulatory obligations represent the primary audience. Industries where credential exposure or unauthorised system access carries significant consequences will find the security model particularly relevant.
The Broader Challenge of AI Agent Governance
As AI agents transition from experimental tools to production systems performing consequential operations, the security implications extend beyond traditional application boundaries. An agent authorised to query a database might, without proper constraints, execute modifications it was never intended to perform. The shift from human-initiated to agent-initiated access requires rethinking how permissions are scoped, monitored, and revoked. This webinar provides one perspective on addressing these challenges through runtime controls and ephemeral credentials, offering enterprise teams a framework for evaluating their own AI security posture.