How AI will Impact Data Security in 2025

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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.

For example, one major challenge organizations are sure to face in 2025 will be securing generative AI agents and chatbots. As companies increasingly rely on these tools to streamline customer service and internal operations, the associated risks multiply. There have been several examples of AI agents giving bad advice or disclosing private information that was never intended for distribution. Chatbots allow businesses to quickly answer customers’ questions without the need to employ a large customer service staff. However, bad actors are finding ways to exploit this automation and its data query functions through what is called a prompt injection attack. Prompt injection attacks are a relatively new attack vector aimed at bypassing safety guardrails, which will only grow in frequency and sophistication in the new year.

Another concern for the upcoming year and beyond is that autonomous AI agents are becoming very sophisticated and it is possible for those agents to carry out entirely automated attacks. The potential for automated and highly scalable attacks by these agents means enterprises must rethink their defensive strategies. Automated adversaries will target weaker organizations with unprecedented speed, so it’s crucial to focus on real-time defense capabilities and take a proactive approach to identifying risks before they become breaches.

To counter these threats, security vendors, AI vendors, and enterprises must work collaboratively. A multi-pronged approach is crucial to address these issues, and should involve preventive measures, effective data security governance, and rigorous user training.

For an effective security posture, companies need a shift in organizational mindset. They should prioritize comprehensive security strategies that apply to their cloud environments, application landscapes, and most crucially, sensitive data which resides across all of it.

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.

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