For most companies, the IT help desk is a quiet productivity sinkhole. It’s essential to keeping the business running, yet chronically understaffed, under-prioritized, and buried under repetitive requests. Password resets, access approvals, software installs—none of it is strategic work, but all of it eats up time. The fact that a startup just raised $10 million to automate this layer of the enterprise says less about novelty and more about how overdue this problem has become.
Risotto’s funding round isn’t just another example of AI being stapled onto a familiar workflow. It reflects a growing belief among investors that some of the biggest opportunities in enterprise AI live in places that were long written off as “just overhead.” Internal IT support is one of those places. Not because it’s glamorous, but because it’s expensive, predictable, and deeply inefficient at scale.
The math alone makes the case. In a mid-sized company, IT teams often spend the majority of their time handling Tier-1 requests—tasks that follow well-worn patterns and rarely require creative problem-solving. Yet those requests are still handled manually, ticket by ticket, across disconnected systems. Companies staff for peak demand, not average reality, which means labor costs stay high even when workloads are routine. Modern AI, paired with workflow automation, is finally capable of absorbing a large share of that volume at a fraction of the cost.
What separates this moment from earlier “chatbot” attempts is that automation is no longer limited to answering questions. Tools like Risotto are designed to actually do the work—reset credentials, provision access, troubleshoot issues, and close tickets by integrating directly with Slack, Teams, Okta, ServiceNow, Jira, and other systems IT teams already rely on. That distinction matters. Talking about a solution is cheap. Executing it inside a real enterprise environment is not.
That’s also why the company’s background stands out. Risotto’s leadership team has spent years inside high-growth tech companies dealing with the same bottlenecks they’re now trying to eliminate. This isn’t an AI lab experimenting at the edges of IT operations; it’s a product built by people who’ve lived inside the queue. For investors like Bonfire Ventures, that operational credibility is often what separates a flashy demo from something that can survive enterprise procurement, security reviews, and day-to-day use.
More broadly, this funding highlights where enterprise AI is headed next. The first wave focused on visible wins—writing, summarization, customer chat. The next wave is moving inward, toward operational systems that don’t make headlines but move real money. Automating internal support may not excite consumers, but for a company with thousands of employees, cutting ticket volume by half can free entire teams to work on projects that actually grow the business.
That doesn’t mean the path is frictionless. IT departments are cautious by design, especially when tools touch identity, access, and infrastructure. Rolling out autonomous systems requires trust, tight permissioning, and safeguards for edge cases that don’t fit the script. There’s also human resistance to consider—automation inevitably changes roles, and adoption can stall if teams feel threatened rather than supported.
Competition will also intensify. If this category proves large enough, it will attract attention from platform players like Microsoft, Google, and ServiceNow, all of whom already sit close to the problem. Startups like Risotto win by moving faster, integrating deeper, and solving the messy reality of enterprise IT rather than offering generic AI features.
Looking ahead, the most successful companies in this space won’t just close tickets faster. They’ll start anticipating issues before employees submit requests, spotting patterns across systems, and helping IT teams plan capacity instead of reacting to demand. That’s where automation turns into intelligence.
For enterprise leaders, the signal is clear. IT support automation is shifting from “nice to have” to baseline expectation. Early adopters will bank efficiency gains and cost savings that compound over time. Late adopters will eventually be forced to explain why humans are still doing work machines can handle instantly. The help desk may never be glamorous—but it’s finally becoming one of the most leverageable parts of the modern enterprise.
This analysis is based on reporting from The AI Journal.
Image courtesy of Risotto.
This article was generated with AI assistance and reviewed for accuracy and quality.
