Data Security Posture Management (DSPM) has come from nowhere to achieve one-fifth market penetration within the past two years alone. Its unique ability to find sensitive data across disparate environments, classify it, and track its movements has made it an especially useful tool in complex digital enterprises.

While all modern security tools leverage automation and (now) AI to accomplish their purposes, what really sets any one solution apart from the rest is how it uses those technologies. AI could be wasted in the wrong context, and automation is only as good as the task you assign it.

See how DSPM has used both artificial intelligence and automation to ‘think’ differently about data security over the past 24 months and how these unique uses have led to its success.

Data Discovery

DSPM solutions automatically (and continuously) scan for data assets across an organization’s environment, whether on-premises, in the cloud, hybrid, multi-cloud, or remote. These automated scans probe into data flows and data storage locations, looking for structured and unstructured data, and can search across various cloud providers (AWS, Google Cloud, Azure).

Without automation, chasing data down these avenues would be a nearly impossible task, especially in complex environments. Today, 98% of organizations either use or plan to use a multi-cloud strategy, per a study by Oracle, and possibly for good reason. According to the AI & Information Management Report, 64% of organizations manage as much as a petabyte of data, with 41% wrangling at least 500 petabytes. Looking for extra storage (at a cheap cost), teams store their data in cloud environments and hope cloud service providers (CSPs) can help keep it safe. The good news is that they can help. Under the shared responsibility model (which all CSPs observe), the customer is responsible for any additional security needs not provided by the service provider out-of-the-box. You may or may not be surprised to find out what those are (and are not).

DSPM’s automated scans help customers bear the weight of cloud data security by automatically discovering both known and unknown instances of data (including shadow data, shadow APIs, and shadow SaaS) and helping teams account for them. Without automation, discovering a petabyte or more of information – even if you already know where much of it is – is too daunting a task for even the best-staffed teams. And that’s if they had the time.

Data Classification and Prioritization

Now that your data is discovered, the real work begins. You want to reduce friction and improve the flow of data throughout your enterprise, so applying a proverbial padlock to all information, as a matter of course, is impractical and sure to backfire. You need specific security protocols assigned based on various levels of data sensitivity and risk, which is where DSPM’s AI-based classification comes into play.

Using artificial intelligence and, more particularly, machine learning (ML) algorithms, data security posture management tools pick out instances of personally identifiable information (PII), personal health information (PHI), intellectual property (IP), financial information, and more. Then, it can help create security-appropriate policies and apply them across the board to the data at hand, even performing basic security tasks to help enforce those policies automatically.

Remediation and Prevention

Another strength of AI-infused DSPM platforms is the ability to spot threats and anticipate vulnerabilities proactively. Using AI-based pattern recognition, DSPM tools can spot threats to data that other solutions would miss, and machine learning functionalities can help draw from historical data to predict best which scenarios will be most likely to mean danger for the enterprise in the future.

As data security firm Cyberhaven states, “DSPM tools…support incident response through root cause analyses, and facilitate real-time remediation.” Using the force-multiplying power of automation and AI combined, they “continuously monitor and update security measures, preventing future data breaches,” which is ultimately the point. In terms of remediating threats once they’ve appeared, DSPM:

• Automates the detection of data threats through continuous multi-environment scanning.
• Automatically alerts the organization when threats appear.
• Automatically encrypt sensitive systems.
• Automatically remediate simple security problems.
• Automatically revoke unnecessary user access privileges.

Machine learning can also be used to improve with time (and more information), improving its ability to correctly predict areas of weakness and data vulnerability in the future.

Conclusion

Gartner predicted that “By 2026, more than 20% of organizations will deploy DSPM technology due to the urgent requirements to identify and locate previously unknown data repositories and to mitigate associated security and privacy risks.”

In a digital landscape fighting for budget, fighting for skilled security specialists, and fighting for the tools to put out data-driven fires at scale, the automation and AI-based capabilities that DSPM brings to the table are pushing it to the forefront as a tool increasingly capable of handling today’s most pressing data problems.