Operations | Monitoring | ITSM | DevOps | Cloud

For many EUC and digital workplace leaders, the challenge isn't a lack of technology. It's understanding why workplace issues continue to surface despite years of investment in automation, AI, and digital transformation. Support teams are still dealing with high ticket volumes. Rollouts intended to improve employee experience can create new sources of disruption, and IT often struggles to understand what employees are experiencing until problems escalate into complaints, incidents, or support requests.

The modern service desk is not short on entry points. In fact, employees can open a portal, search a knowledge base, start a chatbot conversation, or submit a ticket from almost anywhere. In theory, that should mean fewer queues and faster resolution. But if access to IT has improved so dramatically, why has the operational burden behind each interaction barely moved?

The biggest cost in your business may not appear anywhere on your balance sheet because some of the most expensive problems are rarely measured directly. Lost productivity, recurring technology issues, underused applications, and the effort required to manage them all accumulate over time without ever appearing as a line item in a financial report.

Dear Nexthink community, We are excited to be named a Leader in the 2026 Gartner Magic Quadrant for Digital Employee Experience Tools for the third year in a row. I want to share this recognition with our customers, our partners and ecosystem, and every Nexthinker across the world. As a founder, it’s a true honor to work alongside so many talented people. To us, this recognition is also yours.

For decades, IT operations have followed a familiar model. Specialized teams manage different parts of the environment, from infrastructure and networks to security and endpoint management. When employees encounter issues, they submit tickets to the service desk, which are then triaged, escalated, and resolved. This structure has endured because it provided a reliable way to maintain system health and respond to problems as they arise.

Enterprise IT was built for a more predictable workplace, where support began when an employee reported a problem and IT worked backward from the details they could provide. That model made sense when devices, applications, and ways of working were easier to control. Today, the digital workplace moves too quickly for IT to rely on reported issues alone. By the time a ticket appears, employees may have already lost time, worked around the problem, abandoned the tool, or turned to an unmanaged alternative.

Brandon Woods, Keysight Technologies, on the Difference Between a DEX-Powered IT Agent and a Generic AI Assistant “Spark’s real power is the Nexthink data behind it.

Most IT organizations are trying to reduce help desk demand the same way they have for years: by making the help desk itself more efficient. They improve routing, tighten SLAs, expand self-service, and add AI into the support flow. These changes can make the queue move faster, but they do not stop the work from arriving in the first place. The same problems keep finding their way back to IT. Employees lose time to slow devices, unreliable apps, failed updates, access issues, or confusion after a rollout.

CIOs are under pressure from every direction. Budgets remain tight, geopolitical uncertainty is forcing organizations to rethink resilience, and workforce expectations continue to evolve. At the same time, AI is accelerating a broader shift across enterprise IT – changing not only how organizations operate, but also the skills and roles they will increasingly depend on. The question is not whether AI will reshape IT teams, but how quickly organizations can adapt to these new ways of working.

Technology companies are being pushed to deliver faster outcomes while justifying growing investment in AI, SaaS, and digital infrastructure. But productivity does not improve just because new tools are deployed. It improves when employees can use those tools without the constant drag of slow devices, unstable applications, and fixes that do not fully solve the problem. That is the productivity tax of digital friction.