Why Did CrowdStrike Buy SGNL? It’s all about AI

Security powerhouse CrowdStrike made headlines this week with a major acquisition in the identity space with their purchase of SGNL for a reported $740 million. If you’re wondering why did CrowdStrike buy SGNL, you’re asking the right question. And you’re probably not alone.

Over the past year, we’ve watched some of the largest security platforms in the world spend real money acquiring identity security companies. 

From the outside, it might look like platforms buying solutions in a standard consolidation story. From the inside, it looks more like preparation. Specifically, preparation for a future in which identity becomes the most critical control plane for securing cloud environments and the AI systems now operating within them.

At Apono, we see this acquisition as something to celebrate. Not because a competitor was acquired, but because it validates a reality we’ve been living in for years. Identity security has reached a scale and complexity that legacy approaches simply cannot handle. And with AI entering the picture, that gap is becoming impossible to ignore.

Consolidation of Privileged Access Is a Sign of Challenges to Come

CrowdStrike’s acquisition of SGNL is part of a much broader pattern. Over the last 18 months, security vendors have been moving aggressively to close gaps in identity, access, and cloud authorization.

A few examples stand out:

• Palo Alto Networks acquiring CyberArk $25B
• Okta acquiring Axiom for roughly $100M
• BeyondTrust acquiring Entitle for around $150M

Just to name a few.

Now the latest news to break was today’s announcement of Delinea’s acquisition of StrongDM, doubling down on the fact that the big players in the security industry are working hard to ensure that they’re not left flat-footed on identity for Agentic like they were with the advent of the cloud. 

And that’s the backdrop for why did CrowdStrike buy SGNL? It’s a recognition that Identity isn’t a feature anymore. Managing privileged access is simply foundational. But how did we get here?

Why Identity Has Become the Limiting Factor for AI

The pressure around identity and access did not appear overnight. It built up in layers as environments changed faster than access models could adapt.

Before the cloud, access management lived in a very different world:

• Infrastructure was static and long-lived, changing infrequently and predictably
  
• Identities were almost entirely human and relatively easy to enumerate
  
• Permissions were coarse-grained, often all-or-nothing access to a system
  
• Roles were created once and reused for years with minimal adjustment
  
• Access reviews happened periodically and were simply approved, causing access creep.
  
• Manual approvals and standing access were inefficient but manageable
  

In that environment, static roles and slow processes were imperfect, but they mostly worked. The problem is that the world they were built for no longer exists.

It started with the move to the cloud:

• Infrastructure adoption accelerated faster than most security programs anticipated
  
• Resources multiplied, permissions became far more granular, and change shifted from quarterly to daily
  
• Even with only human identities, static roles and periodic access reviews quickly stopped scaling
  

Then came the explosion of non-human identities:

• Service accounts, workload identities, API tokens, CI/CD pipelines, and automation spread everywhere
  
• These identities are predictable in function but exist at a massive scale
  
• The ratio of non-human identities to humans is now estimated at roughly 150:1
  
• Most sit outside traditional IdPs, with fragmented visibility, weak lifecycle controls, and permissions left overly broad to avoid breaking production
  

Now we are entering the Agentic AI era, and earlier cracks are widening:

• Agentic AI combines human-like autonomy with machine speed and scale
  
• These systems decide what to access, when to act, and how to proceed, often without direct human oversight
  
• They ingest untrusted inputs, interact across systems, and operate continuously
  

If non-human identities were already a scaling problem, Agentic AI is a multiplier.

As it stands, AI vendors will manage their models, just as cloud providers manage infrastructure. But organizations still own access. They remain responsible for what identities can reach, what actions they can perform, and where guardrails exist when things go wrong.

And this is where many organizations are running into a hard truth: they do not yet have their identities under control, human or otherwise. AI does not introduce new access failures. It accelerates the ones that already exist.

As Den Jones of 909Cyber put it in a recent Forbes article by Tony Bradley, “Most companies don’t struggle with AI because the models are bad. They struggle because their systems, identities, and data aren’t ready for it.”

This realization that they need to get their privileged access in order has led both customer organizations and big security vendors to seek out Privileged Access Management tools to reduce their access risk.

Why Dynamic Authorization Is the Real Shift

What SGNL got right, and what we have been building toward at Apono, is that access decisions cannot be static. They need to be continuous, contextual, and risk-driven. That applies equally to human users, non-human identities, and now AI-driven ones.

This is exactly what CrowdStrike’s President Michael Sentonas pointed to in his announcement blog. Managing access across all identity types requires decisions that adapt in real time, not policies that are frozen at creation and cleaned up later.

What we see from Sentonas’ post is that the real value of managing access in the cloud is not in turning access on and off. It is about continuously aligning access decisions with risk as identities, resources, and usage patterns change.

That is what dynamic authorization actually means, and why we believe that Apono is well placed to lead the identity security industry into the Agentic AI age. 

How We Think About This at Apono

At Apono, we start from a simple position: access decisions cannot be static in constantly changing environments. In the cloud, defining access once and reviewing it later is disconnected from how work actually happens.

Resources change, teams shift, and usage patterns evolve continuously. Access controls have to keep pace with that reality.

Our approach is built around a few core principles:

• Access decisions should be driven by risk and real-time context, not pre-defined roles
  
• Privileges should exist only for the duration and scope of a specific task
  
• The same governance model must apply across humans, non-human identities, and AI
  

Instead of managing large catalogs of static roles, we provide tightly scoped permissions on demand and remove them automatically when the task is complete. This eliminates standing access, reduces privilege sprawl, and keeps least privilege aligned with how systems are actually used.

Because our Just-in-Time model is based on context and risk rather than identity type, it extends naturally to Agentic AI without introducing a separate control framework.

Why This Acquisition Validates the Direction

If you don’t have human and machine identities under control today, you won’t be ready for AI tomorrow. Period.

The SGNL acquisition, followed closely by StrongDM’s announcement, reinforces the same message. Security platforms are racing to catch up to the reality that identity is now the control plane for everything else.

And they are racing to catch up.

What Comes Next

Our prediction is simple. We will continue to see consolidation in the privileged access sector, heating up alongside the general AI space. 

For security leaders, the takeaway is not about vendors. It’s about readiness. Identity security is no longer about quarterly reviews or static roles. It’s about continuous enforcement at scale.

And that’s why this moment matters.If you’re interested in how this looks in practice, you can explore Apono’s approach to Just-in-Time, Just-Enough access and see how identity can become an enabler rather than a blocker as AI becomes part of everyday operations.