Top 5 Takeaways from Forcepoint AWARE 2025

Forcepoint AWARE 2025 brought together global CISOs, technologists and international policy leaders to discuss and define the industry’s need for self-aware data security.  

Many discussions focused on the urgent reality that AI-driven data risk is expanding faster than most organizations can control it.

This means visibility alone is no longer enough. To protect data and AI systems at scale, modern-day approaches need to understand the context of data interactions to adapt in real time and take corrective action when necessary.

Here are the five most important takeaways from Forcepoint AWARE 2025 that every security professional needs to understand. 

1- The Visibility-Control Gap Is the New Risk Perimeter

Today, data moves faster than ever before. That creates challenges when it comes to securing it. AI amplifies that speed, risking and sometimes even creating sensitive data that traditional tools can’t track or protect. The result is a widening visibility-control gap.  

Ryan Windham, CEO of Forcepoint, outlined the problem this way: 

The visibility control gap is the dangerous space between what you can see, what you can act on, and what you may not even know exists in today's AI-driven distributed data environments.

Forcepoint’s Self-Aware Data Security approach is designed to close that gap by connecting visibility directly to control. It enables security teams to detect, assess and remediate risk automatically.  

2- Context Is the Core of Self-Aware Data Security

Naveen Palavalli, Chief Product & Marketing Officer of Forcepoint:  

The system really needs to understand context, intent, behavior, posture and risk… and it needs to happen in the moment that the data is actually being used.

Think of self-aware data security as protection that adapts in real time based on who is using data, where they are using it and why. Legacy security tools rely on static rules and patterns. That outdated approach simply can’t keep pace with AI agents, SaaS platforms and automated workflows.

Forcepoint’s approach replaces static enforcement with context-aware controls. By continuously correlating user behavior, device posture, data sensitivity and application risk, it can adjust policies dynamically—coaching users, encrypting transfers, or blocking uploads when context changes.

For security professionals, this marks a fundamental shift. Precision and speed are no longer tradeoffs; both depend on understanding context while data is in motion. 

Watch Forcepoint AWARE 2025 On-Demand 

3- AI Mesh Turns Intelligence into Actionable Control

Bakshi Kohli, CTO of Forcepoint:  

If you cannot classify, you cannot protect. AI Mesh brings multiple layers of intelligence together for explainable, highly accurate classification across clouds, networks and AI apps.

Accurate classification remains the foundation of modern data controls. Traditional methods like regex, keyword matching or static fingerprints can’t scale to the complexity of AI-driven, hybrid data environments.

Forcepoint’s AI Mesh architecture solves this by combining multiple lightweight, explainable AI models into a distributed intelligence layer. It enables unified, real-time classification across structured and unstructured data. And it works wherever data resides, whether that is a database, email, endpoint, SaaS app, or generative AI tool.

This explainable, adaptive approach allows security teams to act on insight instantly, and compliance teams to verify why data was categorized a certain way. 

4- Responsible AI Begins with Explainability and Trust

In his discussion with former CISA Director Jen Easterly, Forcepoint Chief Data Strategy Officer Ronan Murphy explored how global data regulations and software accountability are converging around a single principle: trust.  

Achieving and maintaining that trust means compliance can no longer be bolted on after deployment; it must be designed into software and AI systems from the start.

Their conversation underscored why explainability is now a requirement for responsible AI adoption. Security leaders must ensure that every system handling sensitive data can show how and why it made a decision. This level of transparency builds credibility not just with regulators, but also with customers, investors and internal stakeholders.

5- Adapt Fast or Fall Behind as AI Risk Accelerates

Darwish Azad, CISO Emirates NBD explains why adapting fast is so important: 

Traditional controls can’t keep pace with AI threats. We use adversarial AI to test our own posture, reduce false positives and cut detection time.

Darwish’s team’s proactive mindset reflects a broader truth: AI attacks are iterative, automated and fast, and enterprise security must be equally dynamic. Since AI risk now spans across tools, data, users and infrastructure, modern threats are no longer static; they evolve as quickly as the AI models behind them.  

That means the only sustainable defense is continuous adaptation. Organizations that can know, adapt and protect data in the moment will not only stay ahead of AI-driven threats while also building lasting confidence in their ability to safeguard data everywhere it moves.

The Leadership Imperative

The visibility-control gap defines today’s risk landscape. Self-aware data security is how organizations close it.  

Across every session at AWARE 2025, the consensus was unmistakable: awareness must become action. Leaders shaping cybersecurity’s future are building systems that can sense, decide and act at the speed of AI. They recognize that closing the visibility-control gap is not just a technical goal – it’s a leadership responsibility.

Forcepoint’s vision of context-aware, adaptive data protection demonstrates the future. It’s a future where security tools move with data, understand the intent behind it and that continually builds trust through visibility and precision. 

Watch all the Forcepoint AWARE 2025 sessions on demand to hear these insights directly from global security leaders and see how self-aware data security is shaping the future.

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