Autonomous Endpoint Management: From Endpoint Automation to Autonomous DEX
The digital workplace has outgrown the support model built to maintain it. Employees now depend on an mix of devices, applications, AI tools, and connected workflows to get their work done. As this environment becomes more complex, IT is expected to support more technology, control costs, and enable greater productivity.
Traditional, ticket-driven support makes that difficult. It requires IT to respond after something has gone wrong, leaving less time to prevent disruption or focus on operational efficiency.
For many organizations, the endpoint is the starting point for addressing these challenges. AI and operational intelligence are helping IT teams identify and remediate device-level issues more proactively through autonomous endpoint management (AEM).
But leading organizations are recognizing that endpoint health does not equal employee productivity. A device can be secure, compliant, and performing as expected, yet an employee may still be unable to deliver work for a client because of a critical application is slow, a network connection is unstable, or an authentication issue is preventing access.
To understand whether employees can work effectively, the view needs to be beyond the device. That is where Autonomous DEX comes in.
Key takeaways
- Traditional, reactive IT support models are no longer sufficient for the complexity of the modern digital workplace
- Autonomous endpoint management can improve endpoint health, but a ‘healthy’ endpoint doesn’t always mean an employee can work effectively
- Autonomous DEX addresses further than just the endpoint alone. Instead applying autonomy across the entire digital ecosystem that surrounds the endpoint, in order to deliver a better digital employee experience
- At Southwest Airlines, autonomous DEX helped transform ticket-driven support into proactive, preventative operations. This approach enabled 1.1 billion remote actions in 2024 and 2.4 in 2025 – saving thousands of hours for employees
Why traditional IT support models are not enough?
Recognising the gap between endpoint health and employee productivity is one thing but changing how IT responds to it is another.
The traditional IT support model is designed to restore service after disruption has occurred, not to understand the experience leading up to it or prevent the disruption in the first place. As employees rely on an increasingly complex web of devices, applications, services, and workflows, maintaining a seamless and productive digital experience becomes harder. Problems do not always announce themselves through a ticket, and employees may continue working around an issue rather than report it. Using the traditional support model, by the time IT sees the problem, valuable time has already been lost.
One of the key issues is that the support process starts too late. IT needs to move closer to the point where issues emerge. This is possible through intelligence that detects what is changing, understands its potential impact, and acts before employees are forced to raise a ticket.
Autonomous endpoint management applies this principle at the device level. It is an important step forward, but as the next section explores, AEM alone fails to address every technology component of employee, and business, productivity.
What is autonomous endpoint management?
Autonomous endpoint management is the use of automation, artificial intelligence, and operational data to monitor, manage, and remediate endpoint environments with limited human intervention.
Is endpoint automation the same as autonomous endpoint management?
Not exactly. Endpoint automation performs a predefined task, while autonomous endpoint management can identify when action is needed, determine an appropriate response, and apply it across devices at scale.
The result is a more proactive approach to managing devices at scale. But there is an important question that autonomous endpoint management alone cannot answer:
What happens when the endpoint is ‘healthy’, but the employee still cannot work as productively as they should be able to?
Is autonomous endpoint management alone enough?
In short, not quite. But why not? Because a healthy endpoint can still support a frustrating workday. An employee may be using a secure, compliant, fully updated device and still be unable to complete a task, whether because an application is slow, a network is unstable, authentication has failed, or a collaboration service is disrupting communication.
These are not failures of autonomous endpoint management. They are the limits of a device-focused view.
Traditionally, autonomous endpoint management gives IT and end-user computing teams the visibility and automation they need to understand whether endpoints are healthy, secure, and functioning as expected.
DEX broadens that view beyond the device itself. It helps teams understand how employees are experiencing the applications, services, connectivity, and workflows they rely on throughout the workday.
Together, the distinction is between knowing that the endpoint is working and knowing that the employee can work effectively.
From autonomous endpoint management to Autonomous DEX
Autonomous endpoint management is an important development in the evolution of IT. It helps organizations manage devices more efficiently, identify issues earlier, and automate remediation.
But the endpoint is only one part of the employee experience. Autonomous DEX builds on that foundation by considering the employee’s ability to work across the wider digital environment, including the applications, connectivity, services, and other digital touchpoints they rely on every day.
This changes the outcome IT is working towards. AEM helps maintain healthy devices, whereas autonomous DEX focuses on reducing the friction that can prevent employees from working effectively, even when their device itself appears to be functioning normally.
An application may be slow, a connection may be unstable, or an authentication issue may prevent access to an essential service. These issues may not be endpoint failures, but they can still disrupt the employee experience.
This distinction matters because the endpoint is one of the tools employees use to do their work, but keeping it operational does not necessarily mean work can happen without disruption. The real measure of success is whether employees can complete their tasks, collaborate effectively, and move through their workflows without unnecessary friction.
Autonomous endpoint management | Autonomous DEX |
Keep endpoints healthy and compliant | Keep the digital employee experience healthy and productive |
Continuously detect and remediate device-level issues | Continuously detect and resolve friction across devices, apps, services, and workflows |
Automate endpoint operations at scale | Automate experience management across the digital workplace |
Reduce manual effort required to manage devices | Prevent disruption before it affects employees and restore productivity faster when it does |
Autonomous endpoint management solves for device health. Autonomous DEX solves for business continuity.
The next question is how organizations’ can make that broader model of autonomy operational.
How Southwest Airlines is putting autonomy into action
For Southwest Airlines, digital employee experience is closely connected to business operations. With employees relying on digital tools across maintenance, flight operations, and gate services, device and application issues can quickly affect aircraft turnaround times and customers.
In this environment, looking at endpoints in isolation was not enough. Southwest needed a broader view of how technology was affecting employees and the operation as a whole.
Using Nexthink, Southwest combines DEX visibility with remote actions and automated workflows to detect degradation, resolve endpoint and application issues, and validate the outcome before problems escalate.
The scale of that approach is significant:
- In 2024, Southwest conducted 1.1 billion remote actions, saving approximately 13,000 hours.
- In 2025, this rose to 2.1 billion remote actions, saving approximately 23,000 hours.
Southwest demonstrates how endpoint automation and autonomous remediation can support Autonomous DEX in practice: using endpoint and application insight to reduce disruption for employees, strengthen operational stability, and move IT from reactive support towards proactive, preventative operations.
“This has shifted the team from a ticket-driven, reactive support model to a proactive operations model.”
– Derek Whisenhunt, Head of End User Computing at Southwest Airlines
How Nexthink enables autonomous DEX
Autonomy should not stop at the endpoint. Autonomous endpoint management is an important layer, but it draws the circle of visibility around the device. Autonomous DEX expands that circle to include the wider conditions that determine whether an employee is effective at work.
Nexthink applies autonomy to the full digital employee experience by continuously observing the signals that shape day-to-day work. It then combines intelligence, AI, orchestration, and automation to help IT detect friction, understand its impact, determine the right response, and act before the employee needs to raise a ticket.
A device may be healthy while an application is failing, or an application may be available while the network is creating friction. By connecting these signals, Nexthink helps IT understand the problem in context and address what is preventing employees from working.
The goal is to move beyond managing infrastructure to improving the digital conditions in which work happens.
See how Nexthink enables Autonomous DEX to detect digital friction, automate remediation, and help employees work more effectively. Book a demo today.