As the pressure to fully leverage generative AI grows, IT leaders are increasingly concerned about whether their current infrastructure can handle the technology’s demands.
While the push to implement generative artificial intelligence (Gen AI) accelerates, IT decision-makers are wary that the rush to adopt this technology could negatively affect their company’s broader infrastructure in the long run.
A study by network services platform Console Connect revealed that 69% of IT leaders feel their existing network infrastructure is inadequate to support the full potential of Gen AI. Furthermore, 76% expressed concerns that hasty adoption of Gen AI could lead to long-term consequences for their IT infrastructure planning. The study surveyed 1,000 senior IT professionals and CTOs in the US, UK, Singapore, Australia, and Hong Kong. Despite these concerns, 76% of respondents acknowledged that their teams face mounting pressure to implement Gen AI tools.
In fact, 88% of those who hadn’t yet adopted Gen AI said they planned to integrate the technology soon.
When asked about their reservations regarding Gen AI, 70% of IT leaders cited the increased risk of cyberattacks or data breaches. This concern was especially pronounced in Australia, where 90% of respondents shared this fear. Additionally, 41% of respondents identified cybersecurity risks as a major barrier to immediate adoption, and 39% pointed to a lack of IT expertise as another hurdle.
Leaders in Singapore appeared to be especially cautious, with 82% of respondents indicating that the rush to implement Gen AI could have long-term consequences for their infrastructure. Similarly, 81% of Singaporean IT leaders felt their network systems were not yet capable of fully supporting Gen AI, though 89% had already included the technology in their strategic plans. Moreover, 80% of IT teams in Singapore reported facing increasing pressure to deploy Gen AI.
According to Console Connect’s CTO, Paul Gampe, “The rapid advancement of Gen AI is creating demands on networks that we’ve never seen before.” He emphasized that as organizations integrate Gen AI, they need to account for both the short- and long-term impacts of handling large volumes of sensitive data between private and public cloud systems.
Moreover, a separate study by SAS revealed that lack of clarity around Gen AI strategies is a significant challenge for early adopters. According to the study, 90% of respondents admitted they did not fully understand Gen AI and its effects on business operations. Among organizations that had already implemented Gen AI, 75% expressed concerns about data privacy and security. Notably, just 5% had established reliable systems to assess bias and privacy risks in large language models (LLMs). Despite these concerns, 75% of organizations surveyed by SAS indicated they had allocated budgets for Gen AI in the upcoming fiscal year.