Introduction
As the cyber threat landscape continues to evolve, organizations face unprecedented challenges in securing their digital assets. With 49% of workloads already in the cloud and the rise of AI-driven threats, organizations are increasingly vulnerable to data breaches, compliance failures, and malicious actions. Data Security Posture Management (DSPM) is emerging as a critical component of modern cybersecurity, helping businesses continuously discover, classify, and secure sensitive data across both on-premises and cloud environments.
This article explores the rising significance of DSPM in today’s security ecosystem, particularly in the context of AI adoption, cloud migration, and the growing complexity of data security. This blog highlights how organizations can enhance their data security maturity and proactively address emerging threats by examining key findings from the 2025 Cybersecurity Trends Report and incorporating insights from recent field experience.
Cloud security challenges
As organizations increasingly move to the cloud, they find that traditional security tools and processes are no longer sufficient to meet the needs of modern IT infrastructures. With nearly half (49%) of workloads in the cloud, businesses face difficulties maintaining consistent security practices across hybrid environments and ensuring compliance with industry regulations. The fragmentation of data across SaaS apps, cloud stores, and unmanaged repositories—often called “shadow data”—has made visibility more elusive. Many organizations only realize the scope of the issue when preparing for compliance audits, launching AI initiatives, or facing security assessments.
Key Findings from the 2025 Cybersecurity Trends Report
The 2025 Cybersecurity Trends Report highlighted multiple challenges organizations face in managing hybrid infrastructures. 26% of businesses report struggling with inconsistent tools and processes—a signal that today’s data security architecture often lacks the agility required for a hybrid, multi-cloud world. While only 23% of organizations cited a lack of visibility into sensitive data as a challenge—slightly down from 24% in 2023—this still represents a significant concern, especially as environments grow more complex.
Cloud Adoption and DSPM: A Natural Pairing
The trend of cloud migration is accelerating, with businesses embracing cloud services to enhance scalability, improve agility, and reduce costs. However, this shift also presents significant security challenges. As the survey shows, 73% of organizations identified data security as their top priority in 2025, reflecting heightened urgency around protecting sensitive information in increasingly decentralized environments.
With data migration to the cloud, organizations must shift from traditional perimeter security to a data-centric security model. DSPM plays a pivotal role in this transition by helping organizations:
- Continuously locate and classify both structured and unstructured sensitive data, regardless of where it resides
- Analyze access controls to detect over-permissioned users and exposed content
- Prioritize remediation efforts based on sensitivity, exposure, and business impact
By offering real-time visibility, access governance, and continuous posture assessment, DSPM empowers teams to secure hybrid environments without compromising operational efficiency.
The Impact of Artificial Intelligence on Data Security Posture Management
Artificial intelligence (AI) is fundamentally transforming the cybersecurity landscape. As the survey reveals, AI is creating new security threats and reshaping how organizations detect and respond to attacks.
AI-powered attacks such as phishing, adaptive malware, and data poisoning now exploit machine-learning models to evade defenses and amplify damage. For example, AI can craft highly targeted phishing emails or continuously morph malware to bypass detection. These threats are evolving faster than traditional defenses can keep up.
To respond, security strategies must evolve. DSPM offers organizations a dynamic view of risk exposure by continuously identifying where sensitive data lives and how it is accessed and used, even as AI-driven tools introduce new behavioral patterns. This proactive visibility allows teams to adapt their defenses in real-time and reduce the window of opportunity for attackers.
The Future of DSPM in the Age of AI and Cloud
As organizations continue to adopt AI and cloud technologies, the role of DSPM will only grow more critical. With 37% of survey respondents citing AI-driven threats as a challenge that requires changes to their security posture, businesses must prioritize integrating data-centric security solutions that can scale with complexity.
DSPM is not a replacement for security investments like Data Access Governance (DAG), IAM, or PAM—it complements them by adding crucial context and visibility. For instance, DAG may show who has access to a file, but DSPM reveals whether that file contains sensitive data if access is appropriate, and what risk that creates.
Organizations that take a phased approach to DSPM—from visibility to continuous risk assessment—can significantly improve their security maturity in as little as 90 days.
Netwrix’s continued investment in AI-powered DSPM capabilities ensures that organizations can adapt and stay ahead of attackers while safeguarding their most valuable data assets.
Conclusion
The increasing adoption of AI and cloud technologies presents opportunities and challenges for organizations striving to protect sensitive data. With the growing complexity of cyber threats and the rising demand for data-centric security, businesses must embrace modern approaches like DSPM.
By leveraging DSPM solutions, organizations can enhance their security posture, address compliance gaps, and gain real-time visibility into evolving data risks. Netwrix’s leadership empowers organizations to take control of their data across cloud and on-prem before issues escalate into breaches.
Netwrix DSPM enables organizations to discover and classify shadow data, assess, prioritize, and mitigate risks to sensitive data, prevent data loss, and detect threats in time to avoid a data breach.
