Key Takeaways Black Hat 2026 put AI security front and center. In just a few years, the conversation has shifted from whether to use AI to how to control it. Agentic AI is expanding the attack surface. Agents can now reach credentials, code, data, browsers, and business systems. One big takeaway from the event: Attackers
Key Takeaways Integrating humans into automated AI processes helps avoid costly errors. Reserving humans for high-impact decision-making can create new challenges. By positioning AI tools as assistants rather than replacements, organizations can increase internal tool adoption and maximize the value of AI. The rapid adoption of AI tools and agents in the workplace has caused
Key Takeaways The autonomous nature of agentic AI introduces new security and operational risks. Agents thrive on connectivity to enterprise systems, but making it happen securely requires strong identity, permission, and auditing controls. Agentic AI initiatives should prioritize ongoing monitoring and oversight rather than one-time governance policies. It’s easy to think of agentic AI as
Key Takeaways Traditional cybersecurity often fails to cover the gaps that exist when we deploy AI tools. While cybersecurity is never one size fits all, there are six actions CISOs can take to bolster AI security: take an AI asset inventory, layer prompt and input defense, classify data, use least-privilege and human review, use a
Key Takeaways AI security and governance are a must-have for any organization using AI tools. AI security includes protecting AI tools and outputs as well as safeguarding the data and systems AI interacts with. Six critical AI security areas leaders must address are shadow AI, prompt injection and adversarial manipulation, sensitive data leakage, agentic AI,
Key Takeaways Teams with supervisors who embrace AI use AI-based tools at much greater rates—regardless of how good the tools are, how effective the training was, or how great the incentives to utilize the new capabilities are. Incorporating employees into the design process around how AI will be integrated into daily operations has consistently been
Key Takeaways AI scalability is now constrained by energy availability, not only compute. AI costs are increasingly tied to electricity markets, grid stress, and regional demands. Vendors can win over customers by offering predictable, energy-efficient, and flexible AI. When a Virginia data center went offline for 90 minutes last summer amid a heatwave, it wasn’t
Key Takeaways AIOps—AI Intelligence of IT Operations—allows teams to stay a step ahead of problems by identifying them before they happen Teams can take advantage of AIOps to help them correlate and prioritize alerts, which streamlines operations and reduces noise Data is critical to AIOps implementations; inconsistent, disconnected, or out-of-date information can degrade system outputs
Key Takeaways AI solutions need to gain user trust to succeed; capabilities alone are not enough Manager adoption plays a key role in ensuring teams use AI tools regularly Including end users in how AI capabilities are designed and incorporated into workflows can help enhance outcomes Think about the last time a new system was
Your marketing group just signed up for an AI tool that scrapes customer data. Your sales team is feeding proprietary deal terms into ChatGPT. Your developers are using AI coding assistants that may be training on your intellectual property. And your procurement team? They just approved three new SaaS contracts with “AI-powered features” buried in
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