Opinion
The double-edged sword of AI: Why strong data management is essential
"Organizations that invest in solutions to map, classify, and secure their data are the ones that will thrive in the AI era," writes Amit Shaked, VP of DSPM at Rubrik & GM of Rubrik Israel.
The world is in the midst of a race, in which organizations large and small are scrambling to integrate AI solutions into their business hoping to gain a competitive edge. But here's the catch: moving too fast without preparation can put organizations at serious risk. While employees may be inputting sensitive information into public tools like ChatGPT— what’s also concerning is AI systems within the organization that have unprecedented access to an organization's most sensitive data yet might lack the safeguards to protect it properly.
The Internal Threat: How AI Systems Can Go Wrong
Consider this: an internal AI tool might inadvertently allow an employee (who shouldn’t have access) access to executive-level financial reports or expose payroll data to someone outside HR. It’s not always malicious - but it doesn’t have to be. Without careful data management, AI can make it even harder to control who sees what - turning restricted access into unintended visibility of sensitive information. Data leaks outside an organization can fall into malicious hands - whether through a cyberattack, accidental sharing, or unprotected systems.
One of my clients once asked, "How can I be sure sensitive data isn't being accessed by the wrong people when I have tens of thousands of servers and I don't even know where all this data sits?"
That's a real concern - and one many companies are ill-equipped to handle.
The Importance of Successful Data Management
At the heart of all these issues is data. AI systems are only as good as the data they interact with—and for many organizations, their data may live in silos across legacy systems, personal drives, and cloud environments. Without knowing where sensitive data resides, who has access to it, and how it’s being used, organizations are at a loss.
And here lies the irony: the more advanced AI systems become, the greater the risks of mismanaged data. If your data isn't properly mapped, classified, and secured, AI tools can do more harm than good.
The Solution: Prepare Your Data Before Deploying AI
Organizations that want to responsibly implement AI need to take a step back. The first priority is preparing your data is for AI:
- Mapping and Identifying Sensitive Data: Know exactly where your critical data resides—from old servers to cloud folders. For example, redundant files or forgotten employee records can still pose serious risks.
- Automatic Labeling and Classification: Leverage tools that can automatically scan your entire organization, tagging files based on their sensitivity—whether it’s financial, personal, or strategic data. This ensures that access controls can be applied accurately.
- Access Control and Monitoring: Set clear policies on who can access specific data and under what conditions. Implement tools that alert you when unauthorized access occurs.
Better managed data reduces risks, safeguards privacy, and ensures AI delivers on its promise without unintended consequences.
From Chaos to Control: Introducing Technological Solutions every Organization Must Consider
Organizations across industries are already addressing this challenge with Data Security Posture Management (DSPM) - a proactive approach to identifying, classifying, and securing sensitive information across an organization’s data landscape. Instead of relying on manual processes, which are nearly impossible to scale, DSPM solutions automatically map where data is stored, assess who has access to it, and apply security measures to prevent unauthorized exposure.
The benefits are clear: better data management paves the way for safer AI adoption, reducing risks of data leaks, legal exposure, and trust erosion among employees and customers.
AI Success Depends on Data Responsibility
AI isn’t the enemy. In fact, AI represents one of the most exciting opportunities for innovation we’ve seen in decades. But it also requires a higher level of responsibility. Organizations that overlook data management today risk facing catastrophic consequences tomorrow - from internal leaks to regulatory fines to eroded trust among employees and customers.
The question is no longer "Can we adopt AI?" but "How do we do it safely and responsibly?" The answer begins with data.
Organizations that invest in solutions to map, classify, and secure their data are the ones that will thrive in the AI era. By combining innovation with responsibility, they’ll unlock the full potential of AI while safeguarding their most valuable asset: their data.
Amit Shaked is VP of DSPM at Rubrik & GM of Rubrik Israel.
