Conference Description
Key Takeaways
- One-day conference addressing security challenges introduced by enterprise AI adoption
- Focus areas include AI application security, Retrieval-Augmented Generation (RAG), and agentic AI systems
- Designed for CISOs, security practitioners, IAM professionals, and compliance teams
- Emphasises governance frameworks, data protection, and cross-functional collaboration
- Offers 7 CPE credits for CISSP holders, 0.7 CEUs, and 7 PDUs
Introduction
The AI Security Strategies conference is a one-day, in-person event designed for security leaders and practitioners navigating the complexities of artificial intelligence adoption in enterprise environments. As organisations accelerate their deployment of generative AI, Retrieval-Augmented Generation systems, and autonomous agents, security teams face an expanding threat surface that traditional frameworks were not built to address. This conference brings together technical experts and industry peers to examine practical approaches for securing AI applications while maintaining the pace of innovation that business units demand.
About This Event
The conference combines technical presentations, panel discussions, and structured networking opportunities to deliver actionable guidance rather than theoretical concepts. Sessions are designed at both executive and practitioner levels, recognising that effective AI security requires alignment between strategic decision-makers and the engineers implementing controls. Attendees receive a certificate providing 7 CPE credits applicable to CISSP certification, along with 0.7 CEUs and 7 PDUs for broader professional development requirements.
The event maintains a clear separation between educational content and commercial activity. Technical sessions exclude product presentations, with sponsor engagement reserved for breaks. This structure allows attendees to evaluate solutions informally while ensuring that conference content remains focused on independent, practical insights.
Securing AI Applications Across the Development Lifecycle
A central theme of the conference is the integration of security throughout the AI application lifecycle, from initial model selection and training data governance through deployment and ongoing operation. Unlike traditional software, AI systems introduce risks that evolve as models learn and adapt. Security teams must account for prompt injection vulnerabilities, training data poisoning, model extraction attacks, and the potential for AI systems to expose sensitive enterprise data through their outputs.
Retrieval-Augmented Generation architectures present particular challenges because they connect large language models to enterprise knowledge bases. While RAG improves response accuracy and reduces hallucination, it also creates pathways through which sensitive documents may be inadvertently surfaced. The conference addresses how organisations can implement appropriate access controls and data classification within RAG pipelines without undermining their utility.
Identity and Access Management for Autonomous Agents
The emergence of agentic AI systems—autonomous software agents capable of executing multi-step tasks, invoking APIs, and making decisions without continuous human oversight—demands a fundamental rethinking of identity and access management strategies. Traditional IAM models assume human users with predictable behaviour patterns and session-based interactions. Autonomous agents operate continuously, may spawn sub-agents, and require dynamic permissions that adjust based on task context.
Conference sessions explore how IAM professionals can extend existing frameworks to accommodate non-human identities while maintaining the principle of least privilege. This includes examining credential management for agents, audit logging requirements, and the governance implications of systems that can autonomously escalate their own access when task requirements change.
Governance Frameworks and Cross-Functional Collaboration
Effective AI governance requires collaboration across security, legal, compliance, and business teams—groups that often operate with different priorities and risk tolerances. The conference emphasises practical approaches for building governance structures that enable innovation while satisfying regulatory requirements and managing operational risk. This is particularly relevant for organisations in regulated industries where AI deployment intersects with data protection obligations, sector-specific compliance mandates, and emerging AI-specific regulations.
Rather than presenting governance as a barrier to AI adoption, sessions focus on frameworks that provide clear decision-making pathways and accountability structures. The goal is to help organisations move from ad-hoc AI experimentation to systematic, secure deployment at scale.
Who Should Attend
The conference is designed for CISOs, directors of security, and security architects responsible for enterprise AI strategy. Security engineers and practitioners implementing AI-related controls will benefit from technical sessions addressing specific threat vectors and mitigation approaches. IAM professionals facing the challenge of non-human identity management, along with compliance and risk management teams developing AI governance policies, will find relevant content throughout the programme. The event is particularly valuable for organisations currently adopting or planning to adopt AI technologies in enterprise or regulated environments.