Generative AI adoption poses long-term challenges for tech infrastructure, warn global CTOs
Businesses that hastily adopt generative AI (Gen AI) tools are likely to face prolonged challenges with their existing infrastructure, reveals a new research from global Network-as-a-Service provider: Console Connect.
These concerns emerged from a global survey conducted by Arlington Research and spanning across the UK, US, Australia, Hong Kong, and Singapore. The research collected insight from 1,000 CTOs and senior IT leaders revealing that an impressive 76% of respondents believe that the too rapid adoption of Gen AI is going to have long-term repercussions on their technology infrastructure planning. Moreover, nearly 70% of senior IT leaders and 66% of CTOs have admitted to a lack of capacity from their current network infrastructure in supporting Gen AI to its full potential.
Excessive complexity amongst amongst an increased pressure
An excessive rush to integrate Gen AI could be the main reason for the increased pressure on IT teams. In fact, according to the research, 76% of CTOs believe that their teams are under increasing pressure to adopt Gen AI within their organisations. The introduction of large volumes of additional data generated by Gen AI, along with the need to move this data across private and public clouds, is already adding major costs and higher degrees of complexity to enterprise networks.
Paul Gampe, CTO of Console Connect commented: “The rapid development of generative AI creates a demand on networks that we have not seen before. As CTOs and senior IT leaders adopt Gen AI tools within their organisation, they need to consider the short and long-term implications of moving larger volumes of sensitive data to and between private and public clouds.”
Most affected sectors
Not every company is affected in the same way. The challenges posed by the adoption of Gen AI vary across different sectors, small and medium-sized enterprises (SMEs), in particular, often lack the robust infrastructure and financial resources to easily integrate Gen AI. It should serve as a warning that these companies will face a steep learning curve and a significant financial investment in upgrading their networks in order to handle the increased data loads and processing requirements.
In the finance sector, the stakes are even higher as financial institutions handle vast amounts of sensitive data, and any disruption or security breach can have severe repercussions, which is an extremely timely topic following the CrowdStrike crash. The survey found that 70% of respondents fear that the use of Gen AI will increase their organisation’s risk of cyberattacks or data breaches, interestingly, this concern appears to be particularly acute in Australia, where a whopping 90% of respondents expressed heightened anxiety over cybersecurity threats.
Finally, tech companies, which are typically at the forefront of AI adoption, also face unique challenges. While these organisations often have more advanced infrastructure, the rapid pace of AI development means they are required to continuously evolve their networks. The need for constant evolution can obviously strain resources and lead to bottlenecking if it is not strategically managed.
Re-examining cloud access
As enterprises build hybrid and multi-cloud architectures to deliver and support Gen AI, they need to re-examine how they access the cloud. The ‘traditional’ public internet is quickly becoming inadequate for handling the high demands of Gen AI applications and this is why more and more businesses are exploring automated, private, and secure network connections that can be dynamically adapted to meet the needs of Gen AI.
“These survey results demonstrate that when it comes to deploying mission-critical AI applications, businesses are growing increasingly concerned about the need to be securely connected,” continues Gampe. “The public internet is no longer suitable for handling many of these applications and workloads.”
Cybersecurity is facing a skills shortage
Cybersecurity risks and a lack of IT skills and expertise are seen as major barriers to Gen AI adoption. And with an impressive 70% of respondents fearing an increased risk of cyberattacks or data breaches, and in light of the recent global outage, organisations are more than ever compelled to prioritise secure network solutions. A shortage in required skills further complicates this scenario, as businesses struggle to find qualified professionals to manage and secure their AI infrastructure.
What’s next?
This groundbreaking research highlights the critical need for strategic planning in adopting and managing Generative AI technology and businesses must invest in upgrading their network infrastructure and explore secure, private network solutions in order to mitigate the risks and roadblocks associated with this new technology. By doing so, they can harness the full potential of Gen AI while ensuring their operations remain secure and efficient.
Access the full ConsoleConnect 2024 Interconnection Report: “The impact of generative AI on networks”.
