IT didn’t start the fire but they’re sure feeling the heat. “A big reason for burnout is things outside of a CIO’s control — economic uncertainty, political tension, market shifts,” says Manuj Aggarwal, founder and CIO of TetraNoodle Technologies, an AI and automation company. “When that happens, companies lean heavily on their tech teams to fix things: cut costs, automate, and generate revenue fast.”
This hard push for IT to fix anything and everything isn’t smart or sustainable. Many CIOs know that but assume the burden anyway and push forward rather than push back.
“This strain cascades into performance. Overworked teams cut corners, increasing technical debt and security risks. Worse, CIOs themselves aren’t immune, often mirroring their teams’ unsustainable pace. This vicious cycle, where leaders, drowning in their own burnout, lack the bandwidth to recognize or address staff struggles, says Alex Kratko, founder and CEO of Snov.io, a platform that automates sales on LinkedIn.
The cycle of CIO accelerated burnout often pedals along, picking up momentum despite the growing futility of the effort.
“If the overarching culture of the IT division is highly reactive, then staff burnout is more likely. A highly reactive environment is characterized by unplanned work, shoulder tap requests, heroically putting out fires and a lack of strategic direction,” says Andy Miears, partner, at global technology research and advisory firm ISG.
Decades-long, persistent burnout now flames higher than ever under the auspices of CIOs who typically are more misguided heroes than cruel task-masters.
AI to the CIO’s Rescue?
Ah, but what about AI and automation? Surely these advanced technologies will soon lift the burden from the shoulders of CIO and IT staff members alike, right? Not exactly. Or at least not in the short term.
“The rush to implement AI is exacerbating tech burnout as CIOs grapple with unrealistic expectations from boards and shareholders. Under pressure to deliver ROI, many leaders prioritize speed over sustainability, greenlighting overlapping AI projects without aligning them with team capacity,” says Kratko.
Rightly or wrongly, AI is being touted as salvation for beleaguered companies struggling to survive in uncertain times. The C-suite demands IT “make it so” as if they are all captains in Star Trek’s Starfleet. Meanwhile, IT tends to hope it’s a fix for the growing number of fires that they can’t seem to put out. But while efforts of transformation spring eternal, AI has yet to show up as a reliable rescuer.
“One of the biggest challenges plaguing workforces today stems from transformation fatigue. This isn’t necessarily exhaustion from too many change programs, rather a frustration and weariness stemming from little to no meaningful progress stemming from those initiatives,” says Alex Adamopolous, chairman and CEO of Emergn, a technology services and business consultancy.
According to Emergn research, 58% of employees report feeling burnout from change initiatives, with 50% of employees blaming leadership failures and bosses who are out of touch with the concerns of their employees for transformation failures.
By all accounts, AI is the gorilla in the data center and it’s pounding out the biggest changes with little care about whether that change works for anybody concerned.
“Execution speed is increasing but operational design hasn’t caught up. Teams are pushed through AI rollouts and security shifts without recalibrating load or sequence. Engineers get pulled in too many directions without runtime control, while the CIO stays too abstract to resolve bottlenecks,” says Nic Adams, co-founder and CEO at 0rcus, a pen-testing software provider.
Developers echo those same concerns.
“From my experience leading development teams through high-pressure digital initiatives, including AI implementation, the biggest contributor to burnout isn’t the technology itself, it’s the pace and expectations surrounding its rollout,” says Antony Marceles, founder at Pumex, a software development and technology integrations company.
“CIOs often unintentionally worsen burnout by underestimating the human toll of constant context switching, unclear priorities, and always-on availability. In the rush to stay competitive with AI-driven initiatives, teams are pushed to deliver faster without enough buffer for testing, reflection, or recovery,” Marceles adds.
In the end, it’s the panic surrounding AI adoption, and not the technology itself, that’s accelerating burnout. The panic is running hot and high, surpassing anything CIOs and IT members think of as normal.
“The pressure to adopt AI everywhere is real, and CIOs are feeling it from every angle — executives, investors, competitors. But when that pressure gets passed down as back-to-back initiatives with no breathing room, it fractures the team. Engineers get pulled into AI pilots without proper training. IT staff are asked to maintain legacy systems while onboarding new automation tools. And all of it happens under the expectation that this is just “the new normal,” says Cahyo Subroto, founder of MrScraper, a data scraping tool.
To Err Is Tech, to Burn Out Is Human
The focus on tech overshadows the needs of mortal humans. Which is an odd development, if you think about it, since tech is supposed to help or protect the people it serves and not the other way around. Somewhere along the way, the priority flipped.
“What gets lost is the human capacity behind the tech. We don’t talk enough about how context-switching and unclear priorities drain cognitive energy. When everything is labeled critical, people lose the ability to focus. Productivity drops. Morale sinks. And burnout sets in quietly, until key people start leaving,” Subroto says.
Relieving burnout requires flipping the priority back to human-first.
“To fix this, CIOs need to slow the rollout down — not in terms of strategy, but in terms of how it lands on people. That means setting clear phases. It means choosing fewer tools but supporting them properly. And it means protecting focus time for staff and for themselves. Because burnout doesn’t just erode performance. It breaks trust. And once that happens, even the best tech strategy falls apart,” Subroto adds.