IT service management (ITSM) is now a core fixture of enterprise IT strategy. Yet for most employees, getting support still means raising a ticket and waiting. According to Jake Stauch, co-founder and CEO of Serval, that’s not a coincidence. It’s a symptom of legacy ITSM tools that were designed to manage requests rather than resolve them.
According to him, this is a dynamic that has consistently underdelivered on the true promise of ITSM automation and, as a result, enterprise service management.
Serval is an AI-native enterprise service management platform backed by Sequoia Capital, with a $1 billion valuation. Less than two years old, it has already landed enterprise customers including General Motors and Fox Corporation — and its founding premise is that the automation problem at the heart of ITSM has never been properly solved.
Speaking on Bloomberg’s Tech Disruptors podcast with analyst Anurag Rana, Stauch made the case that the industry has been measuring itself against the wrong benchmark for years.
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Tracking Requests Was Never the Goal — Resolving Them Was
Stauch’s argument starts with a straightforward observation: the best possible outcome of any employee support request is instant resolution. Not logged. Not assigned. Resolved. As Stauch points out:
“The world doesn’t need a better ticketing system”
He adds that: “Certainly you could build a nicer ticketing system, but that’s not really what the problem is…It is delivering a better experience. And the best possible experience for employees is that when they make a request, that request is instantaneously resolved.”
Whether it’s a password reset, a laptop replacement, an application access request, or an HR policy question — Stauch argues the technology to automate all of it exists in theory. The reason it rarely happens in practice comes down to one thing: ITSM automation is genuinely hard to build.
His illustration is easy to picture. An employee types into Slack or Teams that they’ve spilled water on their keyboard and need a replacement. In most enterprises today, that message becomes a ticket, assigned to someone, who logs into a separate procurement system and manually places an order. Multiple people, multiple systems, significant lag.
“From your perspective, you did one thing – you typed out a sentence – and then you’re going to get whatever it is that you’re asking for,” Stauch said, describing what he believes the process should look like. He explains:
“There should be no manual effort around that.”
The productivity argument is equally direct. Stauch notes the value isn’t just in freeing up IT support staff — it’s in unblocking the employees waiting on them. “…If you’re needing a password reset, you’re probably blocked from doing something. If you’re making an access request to a certain application, you’re probably blocked from doing some part of your job.”
He frames the end goal as unlocking meaningful work — getting people back to what they were hired to do, rather than waiting in IT queues.
Why Legacy ITSM Vendors Can’t Fix This — Even When They Try
The obvious question is why established enterprise service management platforms haven’t already solved the automation problem. Stauch’s answer is structural, and he applies it well beyond any single vendor.
He argues that platforms built before the current generation of AI face a fundamental constraint: their architecture predates the tools that would make deep automation accessible, and their existing customer base makes radical change nearly impossible. He summarizes:
“When you’re dealing with a legacy architecture, it’s tough to make an overnight shift…”
“You’ve got a massive customer base that can’t make that shift, that can’t upgrade all of their systems and dependencies overnight… And so you’re kind of stuck supporting a customer base that is giving you life… but you can’t make radical changes to the product”, Stauch adds.
It’s a pattern he sees across legacy ITSM and pre-AI enterprise software broadly. The cost and complexity of configuring these platforms has begun to outpace the speed at which organizations actually need to change.
“Your process is going to change much faster these days than it’s going to take to implement a lot of these legacy software solutions…the implementation, the cost to configure, starts to eclipse the pace at which companies are looking to make changes and roll out these automations and new tools.”
He also points to a utilization gap: many enterprises are paying for capabilities they haven’t been able to implement – not because the features don’t exist, but because deploying them requires significant consultant time and technical effort. For many teams, ITSM automation remains largely theoretical.
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The Hidden Multiplier: Why Scale Makes It Worse
For large enterprise IT teams, there’s a third dimension that often goes unacknowledged: IT complexity doesn’t grow in proportion to headcount — it grows exponentially.
Stauch uses a network analogy. Each employee added to an organization creates a new connection point — to applications, devices, and workflows. IT issues emerge when those connections break. He told host Rana:
“Every time you add a node…you’re increasing exponentially the amount of things that could go wrong”
Large enterprises also carry decades of layered technology: cloud systems running alongside on-premise infrastructure, tools acquired through mergers, and departments that were never fully integrated. “You’ve got many, many generations of tooling, none of which has been fully replaced… The complexity just never ends in these large orgs.”
Final Takeaways
Stauch’s core argument is that enterprise service management has been measured against the wrong metric for too long. Ticket volumes and response times tell you how the process is running — not whether employees are being unblocked quickly. When ITSM automation is difficult to build and maintain, all of those metrics can look reasonable while the underlying experience remains frustrating.
For IT and service management leaders, the practical question isn’t just which platform to use — it’s whether their current setup makes automation genuinely accessible. The alternative is a system that still requires expensive configuration work every time a process changes.
The structural constraints facing legacy ITSM vendors are also worth factoring into any modernization roadmap. Incremental AI features layered onto older architecture are unlikely to close the gap between what enterprise service management promises and what it delivers day to day.
Whether AI-native approaches resolve that gap – or eventually face their own version of the same implementation problem at scale – is a question the industry is only beginning to work through.
FAQs
What is ITSM automation?
ITSM automation uses software to handle IT service management tasks. These include password resets, access requests, or device provisioning. But without manual intervention. Rather than a support agent completing each step by hand, an automated workflow triggers the right actions the moment a request is made. The goal is faster resolution and less administrative overhead.
What is enterprise service management?
Enterprise service management extends ITSM principles into the whole organization, including HR, legal, and finance. The idea is that any team fielding regular employee requests can benefit from the same structured approach used in IT support.
What is legacy ITSM?
Legacy ITSM refers to IT service management platforms built before the current generation of AI. Typically in the early 2000s. While many have added AI features, their underlying architecture was not designed with automation at the core. This can make significant changes costly and time-consuming to implement.
What does “AI-native” mean in the context of ITSM?
An AI-native ITSM platform is built from the ground up with AI as a core part of how it works. Not bolted on after the fact. This typically means the system uses AI to generate and manage automated workflows. The alternative is relying on manual scripting or consultant-led configuration.
Why do large enterprises have bigger ITSM challenges than smaller companies?
IT complexity doesn’t scale evenly with headcount — it grows exponentially. Every new employee creates new connection points across devices, applications, and colleagues, meaning more potential points of failure. Large enterprises also carry years of accumulated technology from acquisitions and legacy systems. This adds layers of complexity that smaller organizations simply don’t face.
For a deeper dive into the current state of ITSM, explore our Ultimate Buyer’s Guide to Service Management & Connectivity!
