The Light of Helios:
Stories, Insights, and Thought Leadership

The global IT service management (ITSM) market is worth roughly $13-15 billion in 2026 and is forecast to grow at about 14-16% a year, reaching $30 billion or more by the early 2030s. Here is the detail behind that number and what is fueling the growth. ITSM market size and growth Independent research firms land in a tight band. Fortune Business Insights values the market at $11.91B in 2024, rising to $36.78B by 2032 (15.3% CAGR). Grand View Research projects $29.93B by 2030,

Service desk automation is often pitched as faster ticket routing. That is the small version. The bigger opportunity is automating the service requests themselves, the access grants, provisioning, onboarding steps, and standard changes that make up the predictable, fulfillment side of the service desk. Routing a request faster still leaves a person to do it. Fulfilling it automatically removes the work. This post focuses on that fulfillment side, which is where the largest, m

A ticketing system was built to track work, not to do it. A request comes in, becomes a ticket, and waits in a queue for a person to pick it up, work it, and close it. An AI ticketing system changes that: the AI works the ticket itself, resolving the common ones end to end and handing your team only what genuinely needs them. The queue stops being a waiting room and starts being an exception list. This post explains what an AI ticketing system is, how it changes each stage of

For years, help desk automation meant deflection: a bot and a knowledge base that kept tickets away from agents without actually solving anything. That era is over. Resolution is now table stakes, every vendor claims it. So the question worth asking has changed. It is no longer whether automation resolves tickets, but how far it can resolve them, and that comes down to one thing more than any other: how deeply it connects to the systems where the work actually happens. Resolu

"Automate L1 support" has become one of those phrases that means different things depending on who's selling it. For some vendors, it means a chatbot that deflects common questions to a knowledge base. For others, it means automation rules that route tickets based on keywords. For a few, it means an AI agent that actually handles the L1 workload end-to-end. These are fundamentally different things with fundamentally different outcomes. The first two save some agent time. The

Every operations team I've worked with has the same version of this story. A disk fills up on a production server. The monitoring tool fires an alert. Then the dependent service fails its health check, and that fires another alert. Then the load balancer detects the unhealthy node and fires a third. Then the application monitoring catches elevated error rates and fires a fourth. Four alerts. Four tickets. Four notifications. One problem. Multiply that by every server, every s

For most of its history, IT service management has rested on one assumption: a person does the work, and the platform keeps the record. Tickets queue for humans. Dashboards exist for humans to read. Forms exist for humans to fill in. AI, when it arrived, was added as an assistant to that person. That assumption is now breaking. The real question is no longer whether AI can help the service desk. It is what happens when the AI agent, not the person, becomes the primary operato

Businesses today are under more pressure than ever to move faster, serve better, and operate smarter. Artificial intelligence is no longer a future consideration. It is actively reshaping how organizations work, compete, and grow. For any business leader navigating today’s AI landscape, understanding enterprise AI transformation is not optional. It is foundational. But here’s the uncomfortable truth most AI vendors won’t tell you: buying AI software is not the same thing as t