Veeam Software plans to expand the scope of its offerings into the realm of data security posture management (DSPM) following the closing of a $1.725 billion acquisition of Securiti AI.

Securiti AI developed a DSPM platform based on a knowledge graph that makes it possible to track the relationships between various data sets and then apply policies based on the level of value that data represents for the organization.

Shiva Pillay, senior vice president of the Americas for Veeam Software, said that the Data Command Graph developed by Securiti AI will be extended across the entire data protection portfolio that Veeam currently provides. The capability will then make it simpler for organizations building artificial intelligence (AI) applications to leverage data that has already been classified as part of an existing backup and recovery workflow, he added.

The acquisition of Securiti AI is expected to close this quarter, which should result in graph technologies being more deeply embedded across the Veeam portfolio beginning in 2026.

The overall goal is to make data more easily accessible to AI applications in a way that can be centrally governed more easily, said Pillay.

Additionally, graph technologies should also make it easier to recover faster from ransomware attacks because IT teams will be able to better prioritize which data sets to recover first to ensure higher levels of overall resiliency, noted Pillay.

It’s not clear how widely graph technologies are being employed across the enterprise but as cybersecurity teams focus more on securing specific data sets versus perimeters, the way cybersecurity is managed will fundamentally change. Rather than trying to protect all data, cybersecurity teams will apply different levels of security rigor based on the value of a data set. After all, not all data is of equal value, so there should be more focus applied to securing data based on its actual business value.

The challenge is that, historically, IT organizations have tended to treat all data pretty much the same. As the volume of data being created continues to exponentially increase, that approach is no longer feasible. Instead, organizations will need to spend more time and effort determining what level of security and governance should be applied to any data set based on its actual value. That risk-based approach to cybersecurity should make it possible for cybersecurity teams to allocate limited resources much more effectively.

It may, of course, take a while to achieve that goal but the rise of artificial intelligence (AI) is already forcing the issue. Cybersecurity teams will need to more closely align with business units to better understand the value of various data sets, which in turn will require organizations to invest in more data management capabilities to ensure, for example, there are not multiple copies of the same sensitive data strewn across the enterprise.

In fact, an arguably long overdue convergence of data protection, management and security may soon finally be at hand.

In the meantime, however, cybersecurity teams would be well advised to become better acquainted with their IT colleagues that already have a lot of the data management expertise many of them will now require.