Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI agents are operating inside your enterprise; querying databases, triggering workflows, and taking action through APIs. As AI agents are adopted, organizations cannot see, track, or control what these agents are actually doing. In this session, Roey Eliyahu, Co-Founder and CEO of Salt Security, challenges the industry’s narrow focus on LLM safety and exposes the much larger, invisible attack surface created by agentic systems.

Sisense powers analytics experiences inside the applications businesses rely on every day. As an API-first platform, securing those connections is critical, especially as AI agents increasingly operate through APIs to access data and trigger workflows. In this conversation, Sangram, CISO and VP of IT at Sisense, and Michael Callahan, CMO at Salt Security, discuss how Sisense approached API security strategically to protect their platform, maintain customer trust, and support innovation in the Agentic AI era.

As AI adoption accelerates, a new security risk is emerging from inside organizations, driven not by attackers, but by well-intentioned employees. Across the business, teams are rapidly building AI-powered applications, workflows, and automations using low-code/no-code platforms, custom scripts, and MCP servers.

After four sessions covering the technical realities, business imperatives, and security challenges of agentic AI, Salt Security’s Co-Founder and CEO Roey Eliyahu, and Salt's CMO Michael Callahan, come together for an unfiltered conversation about where the industry actually stands and where it's headed. The gap between AI ambition and operational readiness has never been wider.

See your Blind Spots in Minutes, not Months: How Salt Security & AWS Simplify API Security AI agents and cloud-native architectures have unleashed a wave of APIs and with them, new attack surfaces. Most security teams are struggling to keep up, especially in dynamic AWS environments where shadow and zombie APIs can easily go undetected. This Salt Security and AWS webinar explores a better approach to API discovery and security in AWS without the burden of in-line traffic collection or sensor deployments.

No Fluff, Just Real-World Threats This isn’t your typical marketing webinar. We cover what Agentic AI actually looks like in production, how MCP servers work to broker instructions, and what kind of new threats are emerging. Agentic AI isn’t coming. It’s already here. Autonomous agents are now operating in production environments, reasoning, remembering, and taking real actions across your systems. They’re not just generating content. They’re triggering workflows, modifying records, and making decisions. And they’re doing it over APIs.

AI agents aren’t just talking, they’re taking actions. They’re booking transactions, pulling sensitive data, and chaining tools together to get work done. As enterprises embrace these agents, protocols like the Model Context Protocol (MCP) and Agent-to-Agent (A2A) are enabling powerful new capabilities, but also creating invisible ecosystems of API-driven agent activity that traditional security tools can’t see or control.

For most leadership teams, the question is no longer if they’ll use AI, but how to turn it into measurable business value. Success hinges on the APIs that feed, govern, and scale AI initiatives — and whether your strategy is built for speed, security, and cost efficiency. From accelerating product development to delivering real-time customer experiences, the business case for AI is clear. But without the right API strategy, AI initiatives risk falling short — driving up costs, creating compliance gaps, and limiting ROI.

AI agents are transforming how leading companies operate, delivering 24/7 customer service, processing thousands of transactions, and driving unprecedented operational efficiency. 53% of organizations are already deploying AI agents for customer-facing tasks, with market leaders running hundreds or thousands of agents to gain a competitive advantage. These agents handle sensitive data, trigger transactions, and make autonomous decisions at machine speed. But the APIs that power them are becoming a vast, overlooked attack surface.

As organizations accelerate adoption of AI agents, autonomous workflows powered by LLMs and MCP servers are rapidly proliferating across internal systems, partner networks, cloud environments, and API gateways. The result? A sprawling, often invisible attack surface: shadow APIs, duplicate endpoints, context drift, unmanaged agent access, inconsistent policies, and risk of data exposure or compliance failures.