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DESCRIPTION:AI adoption is accelerating across every industry, bringing unprecedented opportunity — and unprecedented uncertainty. As organizations race to deploy AI applications, models, and agentic systems, many are discovering that traditional security frameworks weren’t designed for this new frontier. The emerging risks are unlike anything seen in cloud, application, or data security, and the speed of change continues to outpace most governance and protection strategies.\nIn this session, industry experts from Presidio and Palo Alto Networks will explore the rapidly evolving AI threat landscape and share what enterprises must understand to safely enable innovation. We’ll cover the blind spots introduced by modern AI architectures, how adversaries are exploiting new attack surfaces, and the critical foundations every organization needs to build in order to secure AI at scale.\nDuring this webinar, you’ll get insight into:\n- The most common (and most overlooked) risks introduced by LLMs, custom models, and autonomous agents\n- Why traditional point solutions and legacy controls fail to address AI‑specific vulnerabilities\n- How to implement practical guardrails that protect sensitive data, ensure model integrity, and reduce exposure across the AI lifecycle\n- Real‑world examples of AI misuse, misconfiguration, and model manipulation seen across industries\nWe’ll also discuss the organizational, cultural, and architectural considerations that leaders must address as AI becomes embedded in products, workflows, and decision-making systems.\nThis webinar is designed for CIOs, CISOs, AI/ML owners, cloud and application leaders, and anyone responsible for enabling AI safely across the enterprise. It is not a product pitch — it’s a strategic look at what’s happening in the world of AI security, and how organizations can prepare for what comes next.\n
DTSTART:20260212T180000
DTEND:20260212T190000
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SUMMARY;LANGUAGE=es-es:Tecnowebinars.com - :: Securing the Next Era of AI: Risks, Realities & What Organizations Must Prepare For
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