How to deploy DSPM and improve your security posture

In today’s digital and cloud-first business environment, understanding the who, what, and where of your data is critical. With data scattered across on-premises and cloud environments and increasingly integrated with generative AI systems, securing sensitive data has become a massive challenge.   

That’s why Data Security Posture Management (DSPM) has come a long way since Gartner introduced the term in 2022.  

But what does DSPM really mean? I’ll walk through my personal connotation and definition, as well as my experience executing DSPM programs for Fortune 200 businesses.

What is DSPM? 

DSPM stands for Data Security Posture Management, but to me, it’s much more than just a buzzword. It’s a comprehensive approach to providing visibility into your data, understanding its context, identifying risks, and, most importantly, automating the remediation of those risks.  

Gartner and the broader marketplace may define it as a way to manage your data’s security posture, but I see it evolving into something much greater: a centralized platform that can categorize and catalog data while also enforcing governance, compliance, and privacy protections.  

DSPM is becoming a key tool for managing the data lifecycle and ensuring identity and access management — all in a unified system. 

How has data protection changed over the years?  

In the past ten years, my work has been devoted to building data governance programs for Fortune 200 companies. Yet, despite the effort, most of these programs couldn’t stop data breaches on a large scale.  

Why? It boiled down to a lack of visibility.   

Because there was no technology or enough resources to fully grasp how much data an organization owned, most of these programs were not successful at stopping data exfiltration on a large scale. This means organizations didn’t fully understand what data they owned, where it resided, or who had access to it. The traditional tools that were supposed to discover and classify data relied on outdated methods like regular expressions and keyword searches.  

This would lead to operational processes breaking when companies enabled blocking controls, and therefore most companies would hesitate to implement effective data controls, and simply remain in a monitoring mode to not disrupt business operations.  

But now, things have changed. With the rise of AI, we no longer have to depend on end users to classify data manually — a process prone to human error and intentional misuse. This shift in technology allows companies to prevent insider threats and better protect their sensitive information. 

Why is DSPM so important today? 

The security landscape has undoubtedly shifted. Data no longer resides neatly within corporate perimeters that can be easily controlled. With data volumes growing exponentially, along with the skyrocketing use of generative AI tools like ChatGPT and Microsoft Copilot, accidental data loss has become a significant risk. Employees may (and are very likely to) unintentionally input sensitive company data into public AI systems, which could lead to data exposure or leakage.  

At the same time, data privacy and protection regulations are evolving and proliferating everywhere. To stay compliant, organizations must adopt DSPM as an essential part of their data security strategy. Remember, DSPM helps companies understand what privacy/sensitive/IP data they have, where it is, who has access to it, and how it’s being used — which gives it a pretty indispensable role in a company’s security toolset.   

How does DSPM work?  

Before discussing some important takeaways, let’s get into the weeds a little and explain how DSPM works.  

With Cloud, every file or data element can be easily shared with anyone around the globe. But this data can also be easily copied, duplicated, modified and shared. Imagine 100 variations of a redlined sensitive contract that needs to be protected, with each version containing different access privileges.  

I know from firsthand experience that this presents some rather unique (to put it mildly) security challenges, which DSPM can effortlessly address with the right tools. 

Here, briefly, are the three steps DSPM uses to improve an organization’s data security posture: 

1. Identify all the sensitive cloud data, from intellectual property to financial to PII/PCI/PHI.

2. Gather all the information about what data is being shared with whom, and track data lineage as it moves across the environment. Identifying where the data may be at risk is a crucial step, as it provides visibility into which data is being shared in accordance with corporate security guidelines and where violations are happening. Typically, the DSPM will alert SOC analysts to provide actionable insights.

3. Remediate security issues as they are happening. For example, it might fix access control issues or permissions, or it may disable sharing a sensitive file with a third party that should not be shared.

Lessons I’ve learned from implementing DSPM for organizations 

One of the biggest lessons I’ve learned from setting up DSPM systems for organizations is the incredible efficiency it brings to the table. In the past, we’d spend endless hours interviewing business leaders, trying to map out what data their departments were creating and how it was being shared. Now, thanks to tools like Concentric AI, we can show up to those meetings with a full inventory of data categories and know where data is located and how it’s being used.  

This shift has seriously changed how we approach data governance. The focus is no longer on discovering data but on remediating the risks we find. And the best part? It can be done without causing operational disruptions, allowing businesses to continue functioning smoothly while improving their security posture. 

Companies that adopt DSPM are reaping huge benefits: they’re seeing faster times to value, less operational overhead, and, most importantly, significant risk reduction. Some are even saving on cyber insurance costs because they can demonstrate to insurance firms that they’ve done due diligence to reduced risk. 

How to improve your data security posture 

So, how can your company improve its data security posture?  

Here are three steps you can use to get started. 

1. Establish a data security steering committee.  

Form a cross-functional team that includes representatives from legal, HR, compliance, and cybersecurity. This team should have executive buy-in to make strategic decisions over reducing data risk and define key performance indicators (KPIs) for your program. 

2. Know your data.

Understand what data your company owns, where it’s stored, who has access to it, and how it’s being used. This crucial step allows you to apply effective policies and controls to protect your most sensitive information at a granular level. 

3. Leverage Concentric AI’s patented technology.

Use Concentric AI’s advanced data categorization as the foundation of your data security strategy. From classification to governance and lifecycle management, Concentric AI helps enforce access controls, remediate risks, and ensure compliance across ALL corporate data. 

In today’s fast-paced, data-driven environment, adopting DSPM is no longer optional.  

When companies leverage AI-driven tools like Concentric AI, they can: 

• Gain complete visibility into their data 

• Mitigate risks 

• Implement proactive security measures without disrupting business operations  

And ultimately, with more sensitive data to manage than ever before, the ability to understand and protect it is becoming a huge competitive advantage.