A Fleet survey of 500 IT leaders confirms it: 7 in 10 are racing into AI without the infrastructure foundation that makes it governable — exactly what AppManager builds in from day one
Fleet Device Management's "Road to AI in IT" report, published July 23, puts a number on a gap we already suspected: 46.5% of IT teams rank AI-driven automation as their top priority for the next two years, but only 29.6% are prioritizing infrastructure as code — the foundation that lets you know, after the fact, what an agent did and why.
The headline number is simple and blunt: across more than 500 surveyed IT leaders, 70% are pursuing AI automation without first laying down the infrastructure-as-code that makes it governable. The report spells out what that looks like on the ground: 87% of teams still manage endpoints manually or only partially automated (just 13% call themselves "fully autonomous"), 79% take more than a day to deploy a critical security patch, and 60% don't even have full visibility into their device fleet. Meanwhile, "shadow AI" is quietly piling up: the average enterprise runs 14 AI applications, but IT has real visibility into only 4 of them — and 78% of employees already use personal AI tools at work, outside any oversight. Fleet CIO Allen Houchins puts the risk plainly: "without that foundation, orgs risk chasing AI outcomes without the governance, visibility and controls required to deploy them confidently." Co-founder and CEO Mike McNeil goes further: "infrastructure as code turns AI from a chatbot into a force multiplier for IT teams."
For AppH
- The real problem this report names — 14 AI applications in use, only 4 visible — is the exact opposite of how AppManager is built: one hub per business area (CRM, Invoicing, Fleet, Stock) where every agent acts inside a traceable module, never one more AI tool bolted on without anyone knowing.
- Our approval panel and decision log aren't a compliance checkbox added for an audit — they're exactly the foundation Fleet describes as missing for 70% of the IT teams surveyed: knowing afterward what an agent did, who approved it, and when.
Against / what doesn't apply
- The infrastructure-as-code Fleet describes manages device fleets and security patches at large-enterprise scale — AppManager doesn't manage any IT devices, only business actions (invoicing, follow-ups, updating stock). The parallel is structural (an auditable foundation before automation), not technical: we shouldn't imply we're solving the same problem Fleet is.
- The survey covers 500+ IT leaders at companies with real, dedicated IT teams — an AppH customer often has no one in that role at all. The numbers (87%, 79%, 60%) are a useful directional signal, not a direct measurement of our own customers' reality.
AppH's take: this report says, with enterprise-scale numbers, exactly what we've been telling much smaller SMBs from day one — automation was never the problem; what happens WHEN it gets something wrong is. An IT team that can only see 4 of the 14 AI apps actually running in its company can't govern them or defend them when something goes wrong; an SMB that turns on an agent with no approval log is in that exact same spot, just with even less of a safety net behind it. In AppManager, every agent action with a real consequence — a message sent, a payment collected, a stock change — waits for an explicit human confirmation before it executes, and that confirmation stays reviewable afterward, module by module. That's not a talking point we pull out once a client is already convinced: if a prospect asks us to wire up an agent that acts without leaving that trail, we say no, even when it costs us the sale — that's precisely the foundation this report says is missing for 70% of the IT teams it surveyed.
Reviewed by a human at AppH