Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

Gartner predicts that by 2029, agentic AI will autonomously resolve 80% of common customer service issues, reducing operational costs by 30%. That shift points toward a zero-friction workplace, where employees do not have to navigate support just to get back to work.

In pharma, reliability becomes an operational priority because research and trial work depend on systems performing consistently across different teams, locations, and conditions. Much of that work sits inside scientific workflows, remote sessions, and compute-heavy environments where behaviour can shift with configuration or load. When that consistency starts to break down, teams keep moving, but time is lost in small increments across the day.

In 2026, I think it’s safe to say that most mobile devices in enterprise organizations aren’t purchased just for their ability to make calls. And for millions of employees, especially frontline workers, their primary device isn’t even a laptop anymore - it’s a smartphone or tablet. Yet, mobile device insights have largely remained a blind spot for IT.

Inside hospitals and health systems, the performance of clinical technology underpins nearly every care workflow and directly influences the timeliness and quality of patient care. Electronic health records sit at the center of admissions, discharge, imaging, lab coordination, and prescribing, so even minor technology friction can become a patient safety and operational risk. At scale, reliability becomes a prerequisite for consistent care.