Generalist teams vs specialist tools -- the enterprise IT paradox [Q&A]

With hyperscalers better able to attract the best talent and headcount tight across the board, most enterprises are leaning heavily on generalist IT teams to manage their environments.

But in many cases the tools they’re expected to use were designed for specialists. Legacy tools like ConnectWise, Device42, or ServiceNow often require deep expertise, complex integrations, or expensive customization making them unsuitable for generalist teams.

Jeff Collins, CEO of observability platform WanAware, calls this the ‘tooling mismatch no one wants to talk about.’ We spoke to him to learn more.

BN: Why are more companies opting for generalist IT teams, and what challenges does this trend present for traditional, complex tooling?

JC: As businesses scale and IT environments become more distributed, companies are increasingly leaning on generalist IT teams to manage infrastructure. It’s a shift driven by necessity in light of tight budgets, leaner teams, and the growing need for agility across hybrid environments. But this generalist model breaks down when teams are asked to manage legacy systems or complex ITAM, CMDB, monitoring and ticketing platforms. Complex tooling assumes dedicated experts with time to spare and most generalist teams have neither. What they need instead are intuitive, intelligent systems that surface insights, automate tedious work, and guide action without requiring weeks of training or constant babysitting. If tooling can’t adapt to that reality, it ends up gathering dust while teams build makeshift workarounds.

BN: Do you think this is hindering moves towards digital transformation?

JC: Absolutely. Digital transformation relies on visibility, automation, and interoperability, but generalist teams can’t deliver that if they’re stuck navigating outdated, fragmented systems. When the tooling itself creates friction, transformation stalls. We see teams spending more time chasing down asset data or resolving configuration drift than deploying new capabilities. The promise of digital transformation can’t be realized with systems that require a specialist just to interpret the dashboard. The reality is, you can’t modernize with tools that require a manual just to get started. If the systems aren’t built for speed, clarity, and adaptability, they become the biggest blockers to progress.

BN: What can help to improve usability and reduce burnout?

JC: Usability starts with empathy for the people doing the work. Generalist IT teams don’t need more features. They need clarity, context, and automation. That means tools that prioritize clean interfaces, surface the right information at the right time, and automate repetitive tasks without adding complexity. Burnout happens when teams are stuck firefighting in systems that don’t talk to each other or require deep technical knowledge just to perform basic functions. The fix isn’t more dashboards, it’s fewer tools that do more and better.

BN: How is the skills gap contributing to the problem of maintaining legacy systems?

JC: Legacy systems were built in an era where enterprises had full in-house teams of specialists to support them. That era is gone. Now, the people who deeply understand these systems are retiring or already out the door, and the documentation they leave behind is rarely enough to keep things running. What’s left is a growing reliance on institutional memory and duct-taped solutions. The skills gap isn’t just a workforce issue. It’s a structural liability for any organization still depending on complex, high-touch platforms.It slows down troubleshooting, delays critical upgrades, and turns basic maintenance into high-stakes guesswork. Unless systems evolve to meet the capabilities of today’s workforce, the gap will only widen.

BN: Are enterprises beginning to move away from their legacy platforms and what types of solutions are they adopting to replace them?

JC: Yes, we’re seeing more enterprises question whether their legacy platforms are worth the overhead. The shift isn’t always loud, but it’s steady. Teams are quietly shelving tools that are too complex or too rigid and looking for lighter, more intelligent alternatives. They’re prioritizing platforms that work out of the box, require minimal training, and support generalist workflows without sacrificing visibility. Cloud-native, AI-assisted tools are gaining traction because they reduce the operational burden and surface insights automatically. Success today isn’t measured by feature depth, but by how easily teams can move.

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