Not long ago, it was only large businesses like enterprises that were managing millions of documents and dozens of databases daily. With the unprecedented rise of cloud adoption and a more remote workforce, smaller businesses are now managing massive amounts of data.
The key challenge they face is twofold: the sheer amount of data they must process, and the fact that so much of their data is unstructured. Plus, more data than ever today contains personally identifiable information (PII) and other sensitive information that’s difficult to find and protect.
What’s more, the cost of a data breach is still on the rise: according to the 2023 IBM Cost of a Data Breach report, the global average cost of a data breach in 2023 was 4.45 million USD, an increase of 15% increase over the last three years. Records containing PII cost enterprises $164 USD per record.
Devoting resources to preventing a data breach presents a significant hurdle, but the challenges only grow with more privacy regulations like Europe’s General Data Protection Rules (GDPR) and California’s Consumer Privacy Act (CCPA). With these privacy regulations, businesses collecting data about anyone – from customers and patients to employees and website visitors – have new mandates for data transparency and protection, regardless of when it was collected or how it is being used.
The harsh reality is that data loss is the new normal. Breaches can take months to find, while compliance demands are getting harder and harder to meet.
How can businesses address these challenges? The good news is identifying, classifying and remediating sensitive data for risk can be automated. In fact, according to the IBM report, organizations that use security AI and automation extensively saved 1.76 million USD compared to those that don’t.
In the digital transformation era, data privacy has become a cornerstone for businesses around the world. Integrating Artificial Intelligence (AI) into the world of data privacy is more than just a technological advancement, it’s a necessity.
First, it’s important to discuss AI in cybersecurity in more general terms. Like any other application of AI, the goal is to enable higher productivity and reduce risk due to human errors. In cybersecurity, it could be used in a SOC environment, helping with threat hunting or incident response or day-to-day operations of the cybersecurity team. AI can add value by ingesting data, providing security teams with better context, and automating routine tasks. The key is to use AI to make experts more productive, especially when the cost of making an error is too high.
Here are the key roles AI can play in managing data protection.
Proactive Data Management: Traditional data management systems typically operate more reactively, addressing issues after they arise. AI, on the other hand, is proactive. AI-based solutions like Concentric AI’s Semantic Intelligence leverage machine learning to scan, categorize, and monitor data in real-time. This continuous surveillance ensures that PII is stored safely and actively protected.
Deep Insights and Predictive Analysis: The power of AI lies in its ability to derive deep insights from vast datasets. By analyzing patterns, AI can predict potential threats and vulnerabilities, allowing businesses to boost their defenses preemptively. What this means is AI-driven solutions like Concentric AI’s Semantic Intelligence can autonomously detect anomalies like unauthorized access, risky data sharing, inappropriate permissioning and wrong locations — ensuring immediate remediation.
Adaptive Learning: One of AI’s standout features is the ability to quickly learn and adapt. As cyber threats evolve, AI systems learn from new patterns to boost defense mechanisms and stay one step ahead of potential breaches. By leveraging sophisticated machine learning technologies, Concentric AI scans and categorizes data, learning from the patterns it observes as it goes along. Our Risk Distance analysis autonomously identifies PII, learns how it’s used, and determines whether it’s at risk. Over time, as the system encounters new data structures and usage patterns, it refines its understanding to ensure more accurate risk assessments.
Real-time Protection: As businesses transition to real-time operations, the need for real-time data protection is critical. AI, with its ability to process and analyze data instantaneously, can be a driving force for real-time protection. By autonomously scanning and categorizing data, Concentric AI provides businesses with the peace of mind that their PII is safeguarded at every moment.
Regulatory Evolution: As data privacy challenges grow, so do regulatory frameworks. AI’s adaptability ensures businesses can seamlessly align with evolving regulations, ensuring compliance with minimal operational disruptions. Concentric AI’s Semantic Intelligence can adapt monitoring and protection mechanisms to comply with numerous regulations.
A Collaborative Approach: The future will likely see a collaborative approach between AI and human expertise. While AI will handle real-time processing and threat prediction, security teams will strategize and implement long-term data protection policies. Concentric AI’s solution provides the technical element and is designed to integrate seamlessly with human-driven strategies and decision-making processes. Businesses benefit from the best of both worlds: the speed and efficiency of AI and the strategic planning of human experts.
Want to see firsthand — with your own data — how you can quickly and easily deploy Concentric AI’s solution to leverage the power of AI for data privacy protection? Book a demo today and experience the freedom of protecting your data without rules, regex, or end-user involvement.
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