Software sprawl, shadow IT, and uncontrolled execution make modern environments harder to troubleshoot, support, and stabilize.
Organizations restore operational control by defining trusted software and governing what runs over time.
Endpoint management has never been more demanding. The explosion of diverse, geographically distributed devices, combined with constant software change across modern environments, has fundamentally rewritten the rules of IT management.
Several forces are converging to drive this complexity. The shift to hybrid and remote work and the growing embrace of BYOD policies has dissolved the traditional network perimeter, leaving employees — and their personal devices — connecting to corporate resources from home networks and public Wi-Fi.
Meanwhile, IT teams are expected to manage an expanding mix of laptops, smartphones, tablets, and IoT devices spanning every major operating system, all while keeping pace with a relentless stream of patches, updates, and software changes. Manually tracking and governing software activity at scale is no longer a viable approach.
Visibility compounds the problem. Many organizations lack a reliable, real-time picture of every device on their network — a gap that quietly enables shadow IT to flourish. In many environments, more than one-third of corporate applications are considered shadow IT, operating outside formal IT oversight and beyond consistent governance. Consider that enterprise endpoints now contain thousands of executables across business applications, utilities, developer tools, IT scripts, browser extensions, third-party installers, and other code-based or cloud-based assets. Unsurprisingly, most organizations do not have clear visibility into what software is running across endpoints.
On average, a mid-sized company uses 275 SaaS applications. Large enterprises deploy over 2,000. The problem? One-third of those apps are unknown to the IT department.
Layered on top of this is tool sprawl: many organizations now rely on a fragmented mix of management and security tools, a patchwork approach that drives up costs, creates inconsistencies, and leaves policy enforcement uneven at best. The upshot of all these threads is that IT and security teams often lack clear visibility into what software is actually running across endpoints — and that creates a serious operational blind spot.
What is uncontrolled software execution?
Uncontrolled software execution is the running of applications, scripts, installers, extensions, and other executable components outside a clearly defined trust model. In practice, that makes environments harder to support and stabilize because IT teams cannot reliably determine what belongs, what changed, or what caused a problem.
Uncontrolled Execution Creates Operational Burdens
When organizations lack clear control over what software is permitted to run on their endpoints and across the larger IT environment, the consequences ripple across every layer of IT operations. Unpredictable system behavior becomes the norm — applications conflict with one another, system resources get consumed by unknown processes, and performance degrades in ways that are difficult to trace back to a root cause.
Each of these incidents generates noise: support tickets pile up, helpdesk teams find themselves triaging problems they didn't anticipate, and resolution times stretch as technicians work to diagnose software they've never seen before and didn't sanction. The troubleshooting burden alone can be significant. When an unknown or unapproved application is at the center of an issue, IT teams often have to start from scratch — no documentation, no context, and no clear ownership. That friction doesn't just slow resolution; it pulls skilled engineers away from higher-value work and erodes confidence in the stability of the environment overall.
Over time, this lack of control creates a compounding effect. Each unmanaged application represents a variable that IT didn't account for, and as those variables accumulate, the environment becomes harder to maintain, harder to audit, and harder to manage consistently.
Software is Sprawling Out of Hand
One of the trendier claims that’s been bouncing around the media recently is that AI portends “the end of software as we know it!”
While AI is certainly changing how software gets built, what it is also doing is accelerating the creation of more software. Enterprise organizations will continue to run formal development pipelines, but smaller teams are already using AI-assisted tools to create new applications, SaaS integrations, scripts, and workflow automations more quickly than before, including increasingly autonomous agentic AI workers that can generate and execute code in pursuit of a goal.
For IT and security teams, that shift opens up a new operational challenge, as these systems are not just tools but autonomous operators that can adapt their behavior and attempt multiple approaches to complete a task. Where they once had to monitor user downloads and software updates, now they also have to account for software applications emanating from unexpected sources within the organization. Maybe the product team is developing prototype applications, or the accounting team is coding scripts to automate financial processes. Without guardrails, software environments expand continuously, with enterprises adding an average of eight new applications per month—often without IT’s knowledge or approval.
Defining Trusted Software Creates Stability
This unaccountable sprawl of software increases operational complexity and makes environments harder to manage consistently. When organizations define what software is trusted to run, the endpoint environment becomes significantly more predictable.
Application control based on allowlisting principles reduces operational noise, facilitates easier troubleshooting, improves system stability, and provides clearer visibility into software activity. More than anything, it helps organizations define trusted software, govern what runs more intentionally, and create a stronger foundation for operational stability and trusted execution.
Detection and response tools still play an important role. They help teams analyze activity and respond when something goes wrong. Application control is complementary: it helps organizations define what runs so teams have clearer control over software execution before they are forced into reactive investigation workflows.
Modern Application Control Makes That Practical
Significantly, application control technology has greatly advanced in recent years, to the point where it is now implementable at enterprise scale. A decade ago, application control systems struggled to deliver at enterprise scale because the technology was not fully mature, and the operational models for implementation required entirely too much human intervention — to the point where the entire approach was discredited.
Today's application control approaches offer flexible policy management, safe learning modes, clearer visibility into software activity, and smoother workflows to support IT operations rather than sapping resources.
Importantly, application control allows organizations to manage software execution without disrupting business workflows. As software sprawl continues to expand, organizations need a practical way to define trusted software, align trust decisions with operational workflows, and restore control over what runs across the environment.
Frequently Asked Questions