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Proofpoint 2025 Predictions: Tackling Data and AI Risks with Human-Centric Security - A roadmap for 2025

vmblog-predictions-2025 

Industry executives and experts share their predictions for 2025.  Read them in this 17th annual VMblog.com series exclusive.

By Ravi Ithal, GVP and CTO of Proofpoint DSPM

If I had a dollar for every prediction that starts with "AI is going to be big," I'd have enough to fund my own AI startup. Let's face it, the buzzwords are endless, and most predictions stop short of saying anything truly surprising. But here's the deal: predictions that matter should take you out on a limb, making you think about risks and opportunities you haven't considered yet. With that in mind, let's dive into what might be coming in 2025-and why getting human-centric data defenses right will make or break the next wave of innovation.

The Chaos of Multi-Cloud Environments

The shift to multi-cloud strategies is fundamentally reshaping IT infrastructure. On the surface, cloud adoption offers unparalleled flexibility and resilience. However, it also introduces unprecedented complexity in managing and securing data. Imagine sensitive files replicated across multiple clouds, each governed by inconsistent security policies and configurations. This fragmented approach creates fertile ground for shadow data-untracked or unmanaged data-and accidental exposure.

The challenge intensifies with the introduction of AI. These systems consume vast amounts of data to operate effectively but lack the ability to distinguish between sensitive and non-sensitive information. In a multi-cloud environment, even a single poorly managed data input can inadvertently lead to the leakage of critical information across interconnected systems.

To address these challenges, organizations must move beyond basic security protocols. They need comprehensive, real-time visibility into their data: understanding where it resides, how it is classified, and who has access to it. This enhanced approach to data security acts as the anchor that keeps organizations steady amid the complexity of multi-cloud and AI-powered operations.

AI as the Developer's Apprentice-and Its Unintended Risks

By 2025, AI tools will have evolved into the ultimate developer's apprentice, automating routine tasks, catching bugs, and even suggesting code optimizations. The promise of faster, more efficient software development is real. However, there's a hidden risk: what happens when these tools have access to sensitive data?

Consider a scenario where an AI-powered tool is tasked with reviewing a codebase and unknowingly flags data containing sensitive information. If that data is stored or processed improperly, it could lead to compliance violations or worse, data breaches. While AI can speed development cycles, it can also amplify security blind spots if not monitored carefully.

Developers and security teams must work hand in hand, treating AI as both a tool and a potential threat. Building security into the development pipeline, from the first line of code to deployment, will be critical in avoiding the unintended consequences of AI integration.

DevOps Transformed: The Predictive Production Line

AI's impact won't stop at development-it'll revolutionize DevOps, turning it into what I call a "predictive production line." By analyzing data in real time, AI can predict deployment bottlenecks, spot potential vulnerabilities, and recommend fixes before issues arise. This proactive approach will reduce downtime and accelerate software delivery.

But here's the catch: these predictive systems require access to massive datasets-many of which are sensitive or proprietary. If that data isn't properly managed, AI's insights could become a liability instead of an asset. Worse, attackers could exploit these systems to gain access to highly valuable information.

To stay ahead, DevOps teams will need robust data security frameworks that ensure sensitive data remains protected at every stage. Real-time monitoring and anomaly detection will become essential components of the DevOps toolkit.

The Security Challenges of Serverless Computing

Serverless computing is gaining traction as a way to simplify application deployment. By abstracting infrastructure management, developers can focus entirely on writing code. But this convenience comes at a cost: security responsibilities shift from organizations to cloud providers, leaving gaps that are easy to overlook.

For example, in serverless architectures, businesses often lose visibility into how data is processed and stored. Without proper oversight, they risk misconfigurations that expose sensitive information. As serverless computing becomes mainstream, organizations will need tools that provide visibility and control over these environments, ensuring that security isn't sacrificed for scalability.

The Road Ahead: Preparing for 2025

As AI reshapes everything from software development to infrastructure management, one thing remains constant: the critical importance of data security. In 2025, organizations that succeed will be those that embrace a data-first approach to cybersecurity.

What does that look like in practice? First, it means understanding where your sensitive data resides and ensuring it's properly classified and monitored. Second, it requires integrating security into every layer of your operations-from development pipelines to cloud environments. Finally, it means recognizing that AI isn't just a tool for innovation; it's also a potential threat vector that must be managed carefully.

And let's not forget the external factors. With the new political regime in the U.S., we can expect curveballs like changing tariffs, regulatory shifts, and AI-related policy chaos. These political moves may not seem immediately relevant to cybersecurity, but they create ripple effects that directly impact it. Here's how:

  1. Supply Chain Disruptions: Tariffs can increase costs or disrupt the availability of key components in IT infrastructure. This can force organizations to make rapid changes in vendors or suppliers, introducing unknown variables into their systems. Unvetted or hastily integrated components can open vulnerabilities, creating new attack surfaces for cyber threats.
  2. Regulatory Overlap and Compliance Challenges: As new policies emerge-particularly in sectors like AI-organizations must navigate complex compliance requirements that vary by jurisdiction. This heightened complexity often leaves gaps in security policies, making it harder to maintain a consistent and secure posture across multi-cloud or global operations.
  3. Increased Threat Activity: Political and economic changes, including tariffs, often heighten geopolitical tensions. Cyber actors-whether state-sponsored or opportunistic-can exploit this uncertainty, targeting industries or regions perceived as vulnerable.

To stay resilient in this evolving landscape, organizations must adopt proactive cybersecurity measures, ensuring real-time visibility and adaptive protection that can weather these external shifts. By tying political and economic unpredictability to the need for agile cybersecurity strategies, we underscore the interconnectedness of these dynamics.

The opportunities in 2025 are immense, but so are the risks. By prioritizing data security now, organizations can confidently leverage AI's transformative potential without falling victim to its unintended consequences. It's time to stop seeing data security as a checkbox and start treating it as the foundation for everything else. The future demands it.

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ABOUT THE AUTHOR

Ravi-Ithal 

With a career steeped in enterprise and cloud security, Ravi Ithal is the group vice president and chief technology officer for Proofpoint's Data Security Posture Management (DSPM) team. Mr. Ithal is responsible for advancing innovative technologies that help organizations discover, classify, and protect their data at scale-transforming how businesses safeguard what matters most.

Before joining Proofpoint through the acquisition of Normalyze, a leading DSPM company he co-founded, Mr. Ithal built a reputation as a trailblazer in the security industry. As the co-founder and chief architect of Netskope, he helped develop cloud-native solutions to defend businesses against modern threats while protecting critical data. Mr. Ithal was one of the founding engineers at Palo Alto Networks, shaping the architecture behind one its security platform.. His earlier career saw him holding impactful engineering roles at Juniper Networks and Cisco, where he honed his skills in building secure, scalable systems.

Published Friday, January 31, 2025 7:34 AM by David Marshall
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