AI didn't ask permission — and it permanently changed what data risk looks like. Forcepoint CEO Ryan Windham opens AWARE with a clear call to action: stop locking AI down and start securing it where the risk actually lives, in the data itself. Learn why securing data and governing AI must become one job, how the world's leading enterprises are ending the false choice between AI innovation and data safety and get a first look at what Forcepoint is bringing to market next.

Here's the uncomfortable truth about agentic AI: there's no best practice yet. Every enterprise is running the same experiment on the same frontier, inspired by what these systems can do and accountable for everything that goes wrong. Futurist Ian Beacraft, one of the most sought-after voices on AI and the future of work, and Forcepoint's David Giambruno cut through the fog together. They unpack what actually changes when agents stop being tools and start being teammates — a modern workforce that moves data at machine speed and behaves in ways that would trip every alert you have if a human did the same. From sanctioned copilots to shadow tools to autonomous agents, they get to the insight most teams are missing: the risk isn't confined to any one tool, it follows the data across all of them. Expect a candid, tech-forward conversation and a way to read the signals of change before the risk arrives.

What you'll gain

• A clear picture of why the pre-agentic security model breaks when non-human actors do the work at machine speed.
• A prioritization checklist that makes clear why the agent or model is the commodity and your data is the real threat surface, including the organizational data most enterprises have never secured.
• A mindset for leading where there's no playbook: treating AI as adaptive R&D, so your team moves with curiosity and realistic goals instead of panic.

AI governance and data security as one continuous, adaptive motion, from the data layer on up. Bakshi Kohli, Salah Nassar and Saritha Chadalavada walk through the latest advances on discovery of unsanctioned AI and sanctioned AI across apps, browser extensions and endpoint agents. See real-time prompt and response inspection that protects sensitive data as it moves through AI interactions. Meet ARIA, the Adaptive Risk Intelligence Assistant that turns natural-language intent into machine-ready governance and protection policy, across channels. And see single-console AI oversight across ChatGPT Enterprise, Claude for Enterprise and Microsoft Copilot, plus AI-powered classification across structured and unstructured data, all from one platform with one policy framework for every AI interaction.

Enterprises have spent decades moving data to the cloud. They are now spending days connecting AI to it — and the pace of that second shift is nothing like the first. Recent Cloud Security Alliance figures put non-human identities at 144 for every human, a signal of just how quickly autonomous agents are embedding themselves into everyday business workflows. In this fireside chat, Forcepoint President of Go-to-Market Rick Hanson sits down with AWS to unpack what AWS is seeing across its customer base: where cloud and data consumption is heading, the dichotomy between moving fast or standing still when it comes to AI adoption and what happens to security models when agents act at machine speed with limited human oversight. The conversation also covers the new risk surface created by shadow AI, agent-to-application data flows and controls designed for human users. As well as perspective for organizations already running AI or scaling it up, including where Amazon Bedrock fits, how the shared responsibility model extends into agentic AI and what AWS observes about the question every enterprise eventually faces: who gets to decide when an agent goes to production.

What you'll gain

• Cloud data gravity is now AI gravity. Understand why customers are accelerating cloud consumption and what changes when that data becomes the fuel for models and agents rather than applications and analytics.
• Non-human identities are the new perimeter. Learn what these agents are actually doing inside customer environments, why volume alone breaks identity-centric controls and how organizations are weighing the opportunity against the exposure.
• Shared responsibility extends into the agentic layer. AWS secures the cloud and the customer secures what they put in it — hear how that model maps onto agents, and where guardrails, data controls and services such as Bedrock fit into a defensible architecture.

AI security and data security aren't two problems. They're a package deal. Most organizations are still funded, staffed and governed as though they aren't. Assurance is where it shows first. In July 2026 Oracle shipped 1,449 patches in a single quarterly update, nearly triple its record, most of them found by AI. As a result of patch overload, it then moved to monthly updates, because quarterly couldn't keep up. The certifications your customers rely on were built for a slower cycle. Roland Cloutier and Ronan Murphy discuss running an AI security program when the frameworks and guardrails it was built on keep changing. How did you red team your own code? What has AI touched, and can you prove it stayed protected? Your customers and constituents are already asking. A trust program is how you answer with evidence, not assurances.

What you'll gain

• Why AI security and data security can no longer be funded, staffed or governed as separate programs.
• What to stand up now: AI scorecards, assurance programs and agentic review.
• How to answer "how did you red team your own code?" before a customer asks it.
• Achievable steps a security or compliance leader can start on right away.