CISO Challenges of 2025 and How to Overcome Them

The evolving digital landscape for cloud-first companies presents unprecedented challenges for chief information security officers (CISOs). The rapid adoption of AI-powered systems and the explosive growth of cloud-based deployments have expanded the attack surface, introducing novel risks and threats.

According to IBM's 2024 "Cost of a Data Breach Report," the average cost of a cloud data breach soared to $4.88 million - prompting a crucial question: Is your organization prepared to secure its expanding digital footprint? 

Regulatory frameworks and data privacy standards are in a constant state of flux, requiring CISOs to stay agile and proactive in their approach to compliance and risk management.

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This article explores the top six challenges facing CISOs today, illustrated by real-world incidents, and offers actionable solutions for them. By understanding these pressing concerns, organizations can stay proactive and secure their environments effectively.

Top Modern Challenges Faced by CISOs

Modern CISO concerns stem from a combination of technical complexity, workforce behavior, and external threats. Below, we explore these challenges in detail.

1. AI and Large Language Model (LLM) Data Protection Challenges

AI tools like large language models (LLMs) have become integral to modern organizations; however, they have also introduced significant risks to data security. In 2024, for example, Microsoft's AI system, Copilot, was manipulated to exfiltrate private data and automate spear-phishing attacks, revealing vulnerabilities in AI-powered systems.

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Furthermore, insider threats have increased as employees misuse AI tools to leak sensitive data. For instance, the AI malware Imprompter exploited LLMs to facilitate data exfiltration, causing data loss and reputational harm. 

Robust governance frameworks that restrict unauthorized AI system access and implementation of real-time activity monitoring are essential to mitigate such risks.

2. Unstructured Data Management

Unstructured data (e.g., text, images, audio, and video files) is increasingly stored across cloud platforms, making it difficult to secure. Take the high-profile breach in 2022 involving Turkish Pegasus Airlines. It compromised 6.5 TB of unstructured data stored in an AWS S3 bucket, ultimately leading to 23 million files being exposed. 

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This incident highlighted the dangers of poorly managed unstructured data, which can lead to severe reputational damage and potential regulatory penalties. Addressing this challenge requires automated classification and encryption tools to secure data at scale. In addition, real-time classification and encryption ensure sensitive information remains protected in diverse, dynamic environments.

3. Encryption and Data Labeling

Encryption and data labeling are vital for protecting sensitive information, yet many organizations struggle to implement them effectively. 

IBM's 2024 “Cost of a Data Breach Report” reveals that companies that have implemented security AI and automation “extensively” have saved an average of $2.2 million compared to those without these technologies. 

The EU’s General Data Protection Regulation (GDPR) highlights the importance of data labeling and classification, requiring organizations to handle personal data appropriately based on its sensitivity. These measures are essential for protecting sensitive information and complying with all relevant data protection regulations.

Companies can enforce data protection policies more effectively by adopting dynamic encryption technologies and leveraging platforms that support automated labeling.

4. Regulatory Compliance and Global Standards

The expanding intricacies of data privacy regulations, such as GDPR, CCPA, and HIPAA, pose significant challenges for CISOs. In 2024, Microsoft and Google faced lawsuits for the unauthorized use of personal data in AI training, underscoring the financial and reputational risks of non-compliance.

Companies must leverage compliance automation tools and centralized management systems to navigate these complexities and streamline regulatory adherence.

5. Explosive Data Growth

The exponential growth of data creates immense opportunities but also heightens security risks. 

As organizations generate and store more data, legacy security measures often fall short, exposing critical vulnerabilities. Advanced, cloud-native, and scalable platforms help organizations scale their data protection strategies alongside data growth, offering real-time monitoring and automated controls to mitigate risks effectively.

6. Insider Threats

Both intentional and accidental insider threats remain among the most difficult challenges for CISOs to address. 

In 2024, a North Korean IT worker, hired unknowingly by an American company, stole sensitive data and demanded a cryptocurrency ransom. This incident exposed vulnerabilities in remote hiring processes, resulting in severe operational and reputational consequences. 

Combatting insider threats requires sophisticated behavior analytics and activity monitoring tools to detect and respond to anomalies early. Security platforms should provide enhanced visibility into user activity, enabling organizations to mitigate such risks and secure their data proactively.

7. Shadow Data

In the race to adopt new cloud and AI-powered tools, users are often generating, storing, and transmitting sensitive data in services that the security team never approved or even knew existed. This includes everything from unofficial file-sharing apps to unsanctioned SaaS platforms and ad hoc API integrations.

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The result is shadow IT, shadow SaaS, and ultimately, shadow data: sensitive or regulated information that lives outside the visibility of traditional security tools. Without knowing where this data resides or how it’s being accessed, CISOs cannot protect it. These unknown data flows introduce real compliance, privacy, and security risk.

It is critical to expose and classify this hidden data in real time, in order to give security teams the visibility they need to secure what was previously invisible.

Overcoming the Challenges: A CISO's Playbook in 6 Steps

CISOs can follow a structured, data-driven, step-by-step playbook to navigate the hurdles of modern cybersecurity and data protection. However, in today's dynamic data landscape, simply checking off boxes is no longer sufficient—leaders must understand how each critical data security measure interconnects, creating a unified, forward-thinking strategy.

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Before diving into these steps, it's important to note why they matter now more than ever: Emerging data technologies, rapidly evolving data regulations, and escalating insider threats demand an adaptable, holistic, and data-centric approach to security. By integrating these core elements with robust data analytics, CISOs can build an ecosystem that addresses current vulnerabilities and anticipates future data risks.

1. First, Develop a Scalable Security Strategy 

A strategic security roadmap should integrate seamlessly with organizational goals and data governance frameworks, guaranteeing that risk management, data integrity, and business priorities align. 

Accurately classifying and continuously monitoring data assets, even as they move throughout the organization, is a must to achieve sustainable scale. This solid data foundation empowers organizations to quickly pivot in response to emerging threats, keeping them agile and resilient.

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The next step is key, as the right mindset is a must.

2. Build a Security-First Culture

Equip employees with the knowledge and tools to secure data effectively; regular data-focused training sessions and awareness initiatives help reduce human error and mitigate insider threats before they become critical risks. By fostering a culture of shared data responsibility, CISOs transform every team member into a first line of defense. 

This approach ensures that everyone is on the same page toward prioritizing data security. 

3. Leverage Advanced Tools and Automation

Utilize state-of-the-art platforms for comprehensive data discovery, real-time monitoring, automation, and visibility. By automating routine security tasks and delivering instant data-driven insights, these features empower CISOs to stay on top of new threats and make decisions based on the latest data. 

Naturally, even the best tools and automation require a strategic, data-centric approach to yield optimal results.

4. Implement Zero-Trust Principles 

Implement a zero-trust approach that verifies every user, device, and data transaction, ensuring zero implicit trust within the environment. Understand who has access to what data, and implement least privilege access. Continuous identity and device validation boosts security for both external and internal threats. 

Positioning zero trust as a core principle tightens data access controls across the entire ecosystem, but organizations must remain vigilant to the most recent threats.

5. Evaluate and Update Cybersecurity Frameworks

Regularly assess security policies, procedures, and data management tools to ensure alignment with the latest trends and regulatory requirements. Keep a current data inventory, and monitor all changes. Ongoing reviews maintain relevance and effectiveness, preventing outdated defenses from becoming liabilities.

For optimal data security, cross-functional collaboration is key.

6. Encourage Cross-Departmental Collaboration

Work closely with other teams, including IT, legal, compliance, and data governance, to ensure a unified and practical approach to data security challenges. Cooperation among stakeholders accelerates decision-making, streamlines incident response, and underscores the importance of security as a shared enterprise objective.

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By adopting this data-centric playbook, CISOs can strengthen their organization's security posture, respond to threats quickly, and reduce the likelihood and impact of breaches. Platforms such as Sentra provide robust, data-driven tools and capabilities to execute this strategy effectively, enabling CISOs to confidently handle complex cybersecurity landscapes.  When these steps intertwine, the result is a robust defense that adapts to the ever-shifting digital landscape - empowering leaders to stay one step ahead.

The Sentra Edge

Sentra is an advanced data security platform that offers the strategic insights and automated capabilities modern CISOs need to navigate evolving threats without compromising agility or compliance. Sentra integrates seamlessly with existing processes, empowering security leaders to build holistic programs that anticipate new risks, reinforce best practices, and protect data in real time.

Below are several key areas where Sentra's approach aligns with the thought leadership necessary to stay ahead of modern cybersecurity challenges.

Secure Structured Data

Structured data - in tables, databases, and other organized repositories, forms the backbone of an organization’s critical assets. 

At Sentra, we prioritize structured data management first and foremost, ensuring automation drives our security strategy. While securing structured data might seem straightforward, rapid data proliferation can quickly overwhelm manual safeguards, exposing your data. By automating data movement tracking, continuous risk and security posture assessments, and real-time alerts for policy violations, organizations can offload these burdensome yet essential tasks. 

This automation-first approach not only strengthens data security but also ensures compliance and operational efficiency in today’s fast-paced digital landscape. 

Secure Unstructured Data

Securing text, images, video, and other unstructured data is often challenging in cloud environments. Unstructured data is particularly vulnerable when organizations lack automated classification and encryption, creating blind spots that bad actors can exploit. 

In response, Sentra underscores the importance of continuous data discovery, labeling, and protection—enabling CISOs to maintain visibility over their dynamic cloud assets and reduce the risk of inadvertent exposure.

Navigate Complex Regulations

Modern data protection laws, such as GDPR and CCPA, demand rigorous compliance structures that can strain security teams. Sentra's approach highlights centralized governance and real-time reporting, helping CISOs align with ever-shifting global standards. 

By automating repetitive compliance tasks, organizations can focus more energy on strategic security initiatives, ensuring they remain nimble even as regulations evolve.

Tackle Insider Threats

Insider threats—accidental and malicious—remain one of the most challenging hurdles for CISOs. Sentra advocates a multi-layered strategy that combines behavior analytics, anomaly detection, and dynamic data labeling; this offers proactive visibility into user actions, enabling security leaders to detect and neutralize insider risks early. 

Such a holistic posture helps mitigate breaches before they escalate and preserves organizational trust.

Be Prepared for Future Risks

AI-driven attacks and large language model (LLM) vulnerabilities are no longer theoretical—they are rapidly emerging threats that demand forward-thinking responses. 

Sentra's focus on robust data control mechanisms and continuous monitoring means CISOs have the tools they need to safeguard sensitive information, whether it's accessed by human users or AI systems. 

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This outlook helps security teams adapt quickly to the next wave of challenges.

By emphasizing strategic insights, proactive measures, and ongoing adaptation, Sentra exemplifies an industry-leading approach that empowers CISOs to navigate complex data security landscapes without losing sight of broader organizational objectives.

Conclusion

As new threat vectors emerge and organizations face mounting pressures to protect their data, the role of CISO will become even more critical. Addressing modern challenges requires a proactive and strategic approach, incorporating robust security frameworks, cutting-edge tools, and a culture of vigilance.

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Sentra's platform is a comprehensive data security solution designed to empower CISOs with the tools they need to navigate this complex landscape. By addressing key hurdles such as AI risks, structured and unstructured data management, and compliance, Sentra enables companies to stay on top of evolving risks and safeguard their operations. The modern CISO role is more demanding than ever, but the right tools make all the difference. Discover how Sentra's cloud-native approach empowers you to conquer pressing security challenges.

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In today's digital world, data security in the cloud is essential. You rely on popular observability tools to track availability, performance, and usage—tools that keep your systems running smoothly. However, as your data flows continuously between systems and regions, you need a layer of security that delivers granular insights without disrupting performance.

Cloud service platforms provide the agility and efficiency you expect; however, they often lack the ability to monitor real-time data movement, access, and risk across diverse environments. 

This blog post explains how cloud data monitoring strategies protect your data while addressing issues like data sprawl, data proliferation, and unstructured data challenges. Along the way, we will share practical information to help you deepen your understanding and strengthen your overall security posture.

Why Real-Time Cloud Monitoring Matters

In the cloud, data does not remain static. It shifts between environments, services, and geographical locations. As you manage these flows, a critical question arises: "Where is my sensitive cloud data stored?" 

Knowing the exact location of your data in real-time is crucial for mitigating unauthorized access, preventing compliance issues, and effectively addressing data sprawl and proliferation. 

Risk of Data Misplacement: When Data Is Stored Outside Approved Environments

Misplaced data refers to information stored outside its approved environment. This can occur when data is in unauthorized or unverified cloud instances or shadow IT systems. Such misplacement heightens security risks and complicates compliance efforts.

A simple table can clarify the differences in risk levels and possible mitigation strategies for various data storage environments:

Risk of Insufficient Monitoring: Gaps in Real-Time Visibility of Rapid Data Movements

The high velocity of data flows in vast cloud environments makes tracking data challenging, and traditional monitoring methods may fall short. 

The rapid data movement means that data proliferation often outstrips traditional monitoring efforts. Meanwhile, the sheer volume, variety, and velocity of data require risk analysis tools that are built for scale. 

Legacy systems typically struggle with these issues, making it difficult for you to maintain up-to-date oversight and achieve a comprehensive security posture. Explore Sentra's blog on data movement risks for additional details.

Limitations of Legacy Data Security Solutions

When evaluating how to manage and monitor cloud data, it’s clear that traditional security tools fall short in today’s complex, cloud-native environments.

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Older security solutions (built for the on-prem era!) were designed for static environments, while today's dynamic cloud demands modern, more scalable approaches. Legacy data classification methods, as discussed in this Sentra analysis, also fail to manage unstructured data effectively.

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Let’s take a deeper look at their limitations:

• Inadequate data classification: Traditional data classification often relies on manual processes that fail to keep pace with real-time cloud operations. Manual classification is inefficient and prone to error, making it challenging to quickly identify and secure sensitive information.
  
  • Such outdated methods particularly struggle with unstructured data management, leaving gaps in visibility.
• ‍Scalability issues: As your enterprise grows and embraces the cloud, the volume of data you must handle also grows exponentially. When this happens, legacy systems cannot keep up. They lag behind and are slow to respond to potential risks, exposing your company to possible security breaches.
  
  • Modern requirements for cloud data management and monitoring call for solutions that scale with your business.

• High operational costs: Maintaining outdated security tools can be expensive. Legacy systems often incur high operational costs due to manual oversight, taxing cloud compute consumption, and inefficient processes. 
  
  • These costs can escalate quickly, especially compared to cloud-native solutions offering automation, efficiency, and streamlined management.

To address these risks, it's essential to have a strategy that shows you how to monitor data as it moves, ensuring that sensitive files never end up in unapproved environments.

Best Practices for Cloud Data Monitoring and Protection

In an era of rapidly evolving cloud environments, implementing a cohesive cloud data monitoring strategy that integrates actionable recommendations is essential. This approach combines automated data discovery, real-time monitoring, robust access governance, and continuous compliance validation to secure sensitive cloud data and address emerging threats effectively.

Automated Data Discovery and Classification

Implementing an agentless, cloud-native solution enables you to continuously discover and classify sensitive data without any performance drawbacks. Automation significantly reduces manual errors and delivers real-time insights for robust and efficient data monitoring.

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Benefits include:

• Continuous data discovery and classification
• Fewer manual interventions
• Real-time risk assessment
• Lower operational costs through automation
• Simplified deployment and ongoing maintenance
• Rapid response to emerging risks with minimal disruption

By adopting a cloud-native data security platform, you gain deeper visibility into your sensitive data without adding system overhead.

Real-Time Data Movement Monitoring

To prevent breaches, real-time cloud monitoring is critical. Receiving real-time alerts will empower you to take action quickly and mitigate threats in the event of unauthorized transfers or suspicious activities. 

A well-designed monitoring dashboard can visually display data flows, alert statuses, and remediation actions—all of which provide clear, actionable insights. Alerts can also flow directly to remediation platforms such as ITSM or SOAR systems.

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In addition to real-time dashboards, implement automated alerting workflows that integrate with your existing incident response tools. This ensures immediate visibility when anomalies occur for a swift and coordinated response. Continuous monitoring highlights any unusual data movement, helping security teams stay ahead of threats in an environment where data volumes and velocities are constantly expanding.

Robust Access Governance

Only authorized parties should be able to access and utilize sensitive data. Maintain strict oversight by enforcing least privilege access and performing regular reviews. This not only safeguards data but also helps you adhere to the compliance requirements of any relevant regulatory standards.

A checklist for robust governance might include:

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• Implementation of role-based and attribute-based access control
• Periodic access audits
• Integration with identity management systems

Ensuring Compliance and Data Privacy

Adhering to data privacy regulations that apply to your sector or location is a must. Continuous monitoring and proactive validation will help you identify and address compliance gaps before your organization is hit with a security breach or legal violation. Sentra offers actionable steps related to various regulations to solidify your compliance posture.

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Integrating automated compliance checks into your security processes helps you meet regulatory requirements. To learn more about scaling your security infrastructure, refer to Sentra’s guide to achieving exabyte-scale enterprise data security.

Beyond tools and processes, cultivating a security-minded culture is critical. Conduct regular training sessions and simulated breach exercises so that everyone understands how to handle sensitive data responsibly. Encouraging active participation and accountability across the organization solidifies your security posture, bridging the gap between technical controls and human vigilance.

Sentra Addresses Cloud Data Monitoring Challenges

Sentra's platform complements your current observability tools, enhancing them with robust data security capabilities. Let’s explore how Sentra addresses common challenges in cloud data monitoring.

Exabyte-Scale Mastery: Navigating Expansive Data Ecosystems

Sentra’s platform is designed to handle enormous data volumes with ease. Its distributed architecture and elastic scaling provide comprehensive oversight and ensure high performance as data proliferation intensifies. The platform's distributed architecture and elastic scaling capabilities guarantee high performance, regardless of data volume.

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Key features:

• Distributed architecture for high-volume data
• Elastic scaling for dynamic cloud environments
• Integration with primary cloud services

Seamless Automation: Transforming Manual Workflows into Continuous Security

By automating data discovery, classification, and monitoring, Sentra eliminates the need for extensive manual intervention. This streamlined approach provides uninterrupted protection and rapid threat response. 

Automation is essential for addressing the challenges of data sprawl without compromising system performance.

Deep Insights & Intelligent Validation: Harnessing Context for Proactive Risk Detection

Sentra distinguishes itself by providing deep contextual analysis of your data. Its intelligent validation process efficiently detects anomalies and prioritizes risks, enabling precise and proactive remediation. 

This capability directly addresses the primary concern of achieving continuous, real-time monitoring and ensuring precise, efficient data protection.

Unified Security: Integrating with your Existing Systems for Enhanced Protection

One of the most significant advantages of Sentra's platform is its seamless integration with your current SIEM and SOAR tools. This unified approach allows you to maintain excellent observability with your trusted systems while benefiting from enhanced security measures without any operational disruption.

Conclusion

Effective cloud data monitoring is achieved by blending the strengths of your trusted observability tools with advanced security measures. By automating data discovery and classification, establishing real-time monitoring, and enforcing robust access governance, you can safeguard your data against emerging threats. 

Elevate your operations with an extra layer of automated, cloud-native security that tackles data sprawl, proliferation, and compliance challenges. After carefully reviewing your current security and identifying any gaps, invest in modern tools that provide visibility, protection, and resilience.

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Maintaining cloud security is a continuous task that demands vigilance, innovation, and proactive decision-making. Integrating solutions like Sentra's platform into your security framework will offer robust, scalable protection that evolves with your business needs. The future of your data security is in your hands, so take decisive steps to build a safer, more secure cloud environment.

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At RSAC 2025, I had the opportunity to speak with Adrian Sanabria about one of the most pressing and complex challenges facing security teams today: data security. Since then, the urgency around the future of data security has only intensified.

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We're watching a major inflection point unfold across industries. Organizations are generating and storing more data than ever, while simultaneously adopting AI at a pace that outstrips most security programs. At the same time, regulators are enforcing data privacy with increasing sharpness. These trends all converge on one critical question:

Do you know where your sensitive data is - and who can access it?

If the answer is no, then it's time to rethink your approach.

Data is Now The Most Valuable, And Volatile Asset

For years, security tools have operated largely without visibility into the data itself. We've focused on endpoints, perimeters, and identities - all essential layers. But in 2025, that’s no longer sufficient.

Data is now the most valuable, and volatile asset most companies have. We’re seeing this in breach investigations, where the root cause often traces back to unmonitored or duplicated sensitive data left in the wrong place. We're seeing it in AI deployments, where teams rush to fine-tune models or deploy copilots without knowing what's inside the datasets they’re exposing. And we’re certainly seeing it in regulatory fines, many of which stem from nothing more than storing customer data longer than necessary, in the wrong place, or in unsecured formats.

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What all of this underscores is a simple truth: you can’t protect what you can’t see.

The Role of DSPM in the Future of Data Security

At Sentra, we’ve built our platform around a core philosophy that Data Security Posture Management (DSPM) is not just a security tool, it’s the future of data security, an enabler of responsible innovation. The foundation starts with sensitive data discovery. Most organizations are surprised by how much sensitive data exists outside expected systems- in backups, temporary stores, or SaaS apps that were never properly offboarded. From there, classification adds context. It’s not enough to label something as “PII”, we need to understand how sensitive it is, who owns it, how it is being used, and how it should be governed.

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We built Sentra as a cloud-native solution from day one. That means it works across IaaS, SaaS, PaaS, and even on-prem environments without needing agents or pulling data outside the customer’s environment. That last point is non-negotiable for us. As a security company, we believe strongly that extracting customer data for analysis creates unnecessary risk and liability.

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To support classification at scale, especially for unstructured data, we developed our own language models using open-source LLMs. This provides the deep contextual understanding needed to accurately label large volumes of data all while maintaining cost efficiency and avoiding unnecessary compute overhead.

AI, Risk, and Responsibility in Data Securityy

One of the biggest shifts we’re seeing in the market is how AI has elevated data security from a technical concern to a boardroom issue. Security teams are now being asked to approve large-scale data usage for AI training, RAG systems, copilots, and internal assistants. But very few have the tools to answer basic questions about what’s in those datasets.

I’ve worked with customers who only realized after deploying AI that they had been exposing medical records, credentials, or confidential meeting data to the model. Once it’s in, you can’t pull it back. That’s why data classification and risk detection must come before any AI integration.

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This is precisely the use case we had in mind when we built Sentra’s Data Security for AI Module. It helps teams scan, assess, and verify the contents of data before it ever touches a model. The goal isn’t to slow down innovation - it’s to make it safer, auditable, and repeatable.

Proactive Risk Management Helps Enterprises Ship Faster

One of the most exciting developments we’ve seen for the future of data security is how quickly Sentra’s data security platform becomes a strategic asset for enterprise data risk management. Time to value is fast in many cases, our customers discover major data risks just days after deployment. But beyond those early wins, the real power lies in alignment.

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When security leaders can map data to risk, compliance, and governance frameworks, and do so continuously, they’re no longer operating reactively. They’re enabling the business, helping teams ship faster with fewer unknowns, and building trust around how AI and data are managed.

At scale, this kind of maturity is the difference between organizations that can confidently embrace generative AI and those that will always be playing catch-up.

A Final Word

From my time in the Israeli Defense Forces and Unit 8200 to helping enterprises build modern security programs, I’ve seen one truth over and over again: data left behind is data exposed. The volume may grow, the threats may change, but this principle doesn’t.

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In 2025, securing data is no longer an aspiration, it’s a baseline. Whether you’re preparing for your next AI initiative, facing regulatory audits, or just trying to get visibility into sprawling cloud environments, DSPM should be your first step. At Sentra, we’re proud to help lead this change. And we believe the organizations that take control of their data today will be the ones best positioned to lead tomorrow.

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