Protecting data is the key to safe and scalable AI adoption

AYUSH MEHAN
SENIOR SALES ENGINEER, FORCEPOINT

“AI is everywhere today — everyone is talking about AI. But at its core, AI relies on the data going into it. If sensitive data is being processed, it matters immensely for the organization. The question is, how do we protect this data in an AI-driven world? The environment has shifted from traditional on-premises infrastructure to a hybrid model, where sensitive information moves to SharePoint, SaaS drives, and multi-cloud platforms. Organizations are not just adopting AI applications; they are building AI into existing systems, using public AI models, and developing their own AI on top, including LLMs and copilots. With this, challenges multiply: data sprawl, regulatory pressures such as DPDP, security fatigue from managing multiple cybersecurity tools, and insider risks. Identifying potentially risky users before breaches occur is critical, because traditional approaches to resilience and security no longer suffice.

At ForcePoint, we address this with a unified data security approach. First, we discover where sensitive data resides - on-prem, in the cloud, or on BYOD devices. Next, we classify and label it, prioritize its business value, and remediate by enforcing proper permissions. Once this data hygiene is in place, protection layers ensure that sensitive information is not misused or exfiltrated. Continuous monitoring tracks behavioural deviations over time, escalating risk scores proactively. When adopting AI, proper guardrails are essential. Enterprises must determine what data can safely be ingested, what is restricted, and how AI interacts with it responsibly. Our patented SLM models analyze datasets, generate persistent labels, and ensure data remains secure as it moves across systems. For example, we can prevent sensitive information from being uploaded to AI tools like ChatGPT, or revoke access in real time if risky prompts are detected.

By integrating discovery, classification, remediation, protection, and AI governance, enterprises can safely accelerate AI initiatives. It’s not just about visibility; it’s about control, resilience, and compliance. Organizations can leverage AI effectively while mitigating insider risks, regulatory exposure, and potential data breaches. With proper security measures and AI-specific guardrails in place, AI adoption can be fast, safe, and reliable, enabling businesses to realize real value without creating new vulnerabilities.”