Impact of AI on Data Security in 2025

The speed at which cyber attackers are moving presents some massive challenges that organizations must be prepared for in the coming year, especially as innovations like generative AI continue to proliferate.
It’s no surprise as generative AI matures and is adopted by more enterprises that threats against data security will continue to grow. We already see it happening. For example, Microsoft Copilot rollouts, while incredibly powerful in helping users find information more easily, introduce a new opportunity for inappropriate access and sharing if sensitive information isn’t properly secured before, during, and after the rollout. This trend is accelerating, with AI innovations coming online faster than enterprises can adapt their security controls.
AI has been a beneficial game-changer for adversaries. As generative AI costs decline, the scale of attacks utilizing this technology will only grow. I expect bad actors to continue leveraging new AI innovations in 2025 to exploit new and often overlooked vulnerabilities.
An AI-powered data security governance platform can discover and categorize records, identify sensitive data, assign classifications, and enforce access governance policies. Knowing what sensitive data an organization has in its possession, where it’s located, and having controls over how it is shared will greatly reduce the risk of unauthorized access and data loss. For vendors, continuous innovation will be key in helping organizations address these threats.
While 2025 is sure to bring about considerable risks, we remain cautiously optimistic about improving the threat landscape. Security posture management—whether it’s in the cloud, on-premises, or for applications or data—is now recognized as a key component in managing enterprise risk. The industry is increasingly aware of these needs, and there is exciting innovation taking place, driven by both established players and promising startups.
We can expect to see advances in the efficacy and capabilities of technologies across the spectrum. Assessing, monitoring and mitigating risk holistically – not in isolated silos but rather bringing together users, permissions, activity and data to provide an integrated view – will be critical. Startups are innovating in this space for effective data security governance, and we remain encouraged about the future.
2025 will be a year of adaptation—for both defenders and attackers. With generative AI continuing to influence every aspect of how businesses operate, attack risks will expand, as will the sophistication of threats.
Quote from Author:
“When we started Concentric AI five years ago, it was obvious that enterprises had a massive data security problem. On one hand, data volumes were growing, data was sprawled across their environments – both cloud and on-premises – and the nature of business-critical data spanned the gamut from IP to financial data to business confidential data to PII/PCI/PHI. And on the other hand, customers were still relying on age old techniques – from cumbersome rule writing to pattern matching to complex policies just to answer basic questions on where their sensitive data might be. It also meant that if you don’t know what you have, you can’t protect it.“
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