The survey result that should reframe the budget conversation
Inside Higher Ed and Hanover Research's 2026 Survey of Campus Chief Technology and Information Officers, published August 13 as part of a report titled 'Overcoming Barriers to Digital Transformation,' puts a number on something most technology leaders already sense but rarely get to prove with data. Asked what actually blocks digital transformation at their institution, 73 percent of the 130 surveyed CTOs and CIOs cited insufficient IT personnel, ahead of the 69 percent who pointed to insufficient financial investment. Roughly half cited data challenges, meaning disconnected systems and poor data quality across departments, and 45 percent cited resistance from staff and faculty.
The ordering matters more than it might first appear. For years, the default assumption in both higher education and corporate IT has been that transformation stalls because the budget request gets denied. This survey, with an 8 percent margin of error across a meaningful sample of sitting technology executives, says the more common blocker is that the institution cannot find, hire, or retain the people needed to execute the plan even when money is available. That is a fundamentally different problem to solve, and it needs a fundamentally different fix than the one most finance committees are set up to approve.
Why staffing outranks budget in practice
Higher education IT has spent the last several years competing for the same data engineers, integration specialists, and AI-literate technologists that every enterprise wants, while offering compensation packages that rarely match private sector SaaS or financial services pay scales. The roles eventually get filled, but typically long enough after the fact to stall a migration, delay an integration project, or leave a security gap open past the point anyone is comfortable with. A budget line for a new platform is easy to defend to a board. A budget line for retention bonuses to keep the two engineers who actually understand the legacy student information system is a much harder sell, even though the second gap is what the survey says is actually blocking progress more often.
Data challenges compound the staffing problem rather than sitting alongside it as a separate issue. Nearly half of respondents cited fragmented or poor-quality data as a barrier, and disconnected systems are exactly the kind of problem that requires skilled people to diagnose and fix, not just software to purchase. An institution that is short-staffed and sitting on years of accumulated data debt is not solving either problem by buying a new AI tool, because the tool still needs someone competent to integrate it, and someone to clean the data it depends on.
The report's actual advice, and where it falls short
The report's core recommendation, authored by Ben Upton, is to align technology investment tightly with institutional priorities so that scarce staff time and scarce dollars both go toward the highest-impact work rather than being spread across every initiative with a champion in the room. That is sound but generic advice, the kind that applies to any resource-constrained organization and does not, by itself, solve the specific problem of not being able to hire fast enough. What the report gestures toward but does not fully resolve is the harder question: what does an institution actually do differently when the constraint is people, not money, and traditional hiring cannot close the gap on a useful timeline.
The survey notes that CTOs are exploring 'institutional strategies for addressing talent needs beyond traditional recruitment,' which is the more interesting thread here, even if the public landing page does not spell out specifics. That framing points toward the same set of options enterprise CIOs have been testing for two years: fractional and contract specialists for defined projects, shared services arrangements across departments or even peer institutions, upskilling existing staff into higher-value roles using the same AI tools reshaping the rest of the sector, and narrowing the scope of what gets built in-house versus bought as a managed service specifically to reduce the headcount required to run it.
The parallel enterprise CIOs should not ignore
It is tempting for enterprise technology leaders to read this as a higher-education-specific story, given the underfunded reputation of campus IT departments. That reading misses the point. The staffing constraint this survey documents, more IT work than there are qualified people to do it, at a compensation level the organization is willing to pay, describes most PE-backed SaaS companies and retail technology organizations just as accurately as it describes a university. The difference is that higher education has now put a specific number on it through a credible survey instrument, while most enterprises are still relying on anecdotal frustration from their own IT leadership to make the case.
That makes this report useful as a benchmarking tool even for readers who have never set foot on a campus. If 73 percent of technology leaders in a sector with famously constrained budgets rank staffing above money as their top blocker, any enterprise CIO whose board still treats every stalled initiative as a budget problem has a data point worth bringing into that conversation. The fix is rarely just headcount. It usually combines tighter prioritization, smarter build-versus-buy decisions that reduce the ongoing staffing burden, and honest acknowledgment that some transformation initiatives should wait simply because the organization lacks the people to execute them well, regardless of what the budget line says.
The decision this puts on the table
For any technology leader planning a 2027 roadmap right now, this survey is a useful gut check before the next budget cycle locks in assumptions. Before requesting more capital for a transformation initiative, it is worth running the same question this survey asked internally: is the actual blocker on the last three delayed projects money, or was it that nobody had the bandwidth or the specific skill set to execute once the money arrived. If the honest answer looks more like the second, the next budget ask should probably be reframed around flexible capacity, whether that is contract talent, managed services, or a narrower project scope, rather than a larger headcount request that will take two hiring cycles to fill.
The institutions and enterprises that get ahead of this will be the ones that stop treating staffing shortfalls as a temporary hiring market problem and start treating them as a permanent design constraint on how ambitious any single initiative can be. That is a less comfortable planning assumption than simply asking for more budget, but the data in this survey suggests it is the more accurate one. It also changes how a roadmap gets built: scope shrinks to match realistic delivery capacity, timelines account for the hiring lag rather than assuming it away, and the projects chosen first are the ones the current team can actually staff, not just the ones that would look best in next year's board deck.
