IT leaders are facing rising workloads and complexity as AI adoption accelerates across organisations, with new research highlighting a growing ‘double-edged’ impact on teams.
According to data from SolarWinds, while 67% of IT professionals say AI has reduced manual work, nearly three-quarters (71%) report that their roles have become more demanding. The findings point to a widening gap between efficiency gains and the operational realities of managing AI at scale.
For IT leaders, the challenge lies in the additional oversight burden that comes with AI deployment. More than 70% of respondents say they must regularly double-check AI outputs, while 62% struggle to fully trust its recommendations. At the same time, 48% report that AI tools generate excessive insights without sufficient context, making it harder to translate outputs into actionable decisions.
This dynamic is contributing to what some are calling ‘AI brain fry’, a growing cognitive load as teams juggle traditional responsibilities alongside new demands for governance, validation and risk management.
The issue is compounded by the rapid proliferation of AI tools across the business. As non-technical teams increasingly adopt AI-driven applications, IT departments are being tasked with ensuring security, compliance and effective use—often without additional resources.
The research suggests that rather than eliminating work, AI is reshaping it, shifting the focus from execution to oversight, interpretation and control. This includes managing fragmented toolsets, validating outputs and mitigating potential risks introduced by poorly governed AI systems.
Industry experts warn that without a structured approach, AI could increase operational risk. Gaps in governance and data quality may lead to inconsistent outputs, while the need for constant verification can offset efficiency gains.
However, the findings also highlight a path forward. With the right implementation, AI can help IT teams move away from reactive workflows toward more proactive, automated environments, identifying issues earlier and reducing the need for manual intervention.
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