AI Is Becoming the Primary Driver of Enterprise Data Security Investment

New research from Enterprise Management Associates suggests that artificial intelligence is fundamentally reshaping enterprise data security priorities.

The study, based on a survey of 225 IT leaders, security practitioners, and business executives across North America, found that 64.4% of organizations now cite securing AI-related data flows as the primary driver for investing in Data Security Posture Management (DSPM) — overtaking data exfiltration prevention for the first time.

The report also highlights growing governance challenges as AI adoption accelerates. Responsibility for AI-related data risks remains fragmented across IT, security, data governance, and executive leadership, with no single function emerging as the clear owner.

Meanwhile, multi-cloud environments continue to complicate security. Nearly 45% of respondents identified maintaining consistent security policies across cloud providers as their greatest governance challenge, citing differences in encryption, data residency, and security architectures.

Despite the growing complexity, organizations remain optimistic about automation. More than 85% expect automated remediation capabilities to reduce operational workloads, with roughly one-third anticipating workload reductions of more than 50%.

The report concludes that organizations treating DSPM as a foundational component of AI adoption, rather than an afterthought, will be better positioned to maintain control over increasingly distributed data environments.

TheMarketAI Take

As AI adoption accelerates, the conversation is shifting from building models to governing data.

Every AI initiative increases the amount of data being collected, connected, processed, and exposed. That makes data security no longer just a cybersecurity issue, but an AI infrastructure issue.

What's particularly interesting is that AI is creating a second-order market. Beyond the models themselves, we're seeing growing demand for technologies that secure, govern, audit, and manage AI deployments.

This mirrors a broader trend we've covered repeatedly on TheMarketAI: every major wave of AI adoption creates entirely new infrastructure layers. First came GPUs, then data centers, then orchestration platforms. Increasingly, AI governance and data security appear to be joining that list.

As enterprises move from experimentation to production, securing AI may become almost as important as building it.