New Flexential Survey Unveils AI Infrastructure Challenges and Investment Priorities

The 2024 State of AI Infrastructure Report shows that 93% of respondents said there would be consequences if their organizations don’t achieve the goals laid out in their AI roadmaps

Flexential, a leading provider of secure and flexible data center solutions, today released its 2024 State of AI Infrastructure Report, a new survey on AI infrastructure investments and challenges. As organizations across nearly all industries plan ambitious roadmaps for AI adoption, Flexential’s report highlights crucial areas where IT leaders must evolve their current infrastructure to meet the growing demand of high-density AI workloads and latency-sensitive AI applications.

Also Read: The Risks Threatening Employee Data in an AI-Driven World

The report findings are based on a survey of 350 IT leaders at organizations with over $100 million in annual revenue, including 100 respondents at organizations with over $2 billion in annual revenue. The survey found that IT leaders are optimistic about plans to integrate AI into their operations, yet they face challenges when it comes to scalability, workforce skills gaps, security, sustainability, and C-suite commitment to solutions.

Among organizations with AI roadmaps, 59% of respondents said increasing IT infrastructure investments was an element of that roadmap. Flexential’s survey also found that 45% of respondents from organizations with AI roadmaps said failing to meet the goals in their roadmap would affect their ability to innovate – suggesting that enterprises need to be dedicated to up-leveling AI infrastructure and employing a strategic, proactive approach to AI workload deployment in order to harness AI’s potential. Notably, nearly all respondents (93%) indicated there is a greater expectation that IT leaders in their organization minimize time-to-revenue for AI-driven IT infrastructure compared to five years ago.

However, AI infrastructure investments face significant hurdles for many organizations. Networking challenges and data center scale are leading causes of AI performance issues, with 82% of respondents having encountered a performance issue with their AI workloads in the past 12 months related to bandwidth shortages (43%), unreliable connections (41%), or difficulty scaling data center space and power (34%).

“The stakes are high for AI infrastructure investments,” said Chris Downie, Chief Executive Officer of Flexential. “Our survey shows that enterprise leaders are ready to execute on ambitious AI plans, with over half of leaders (53%) stating that C-level leadership is behind the pressure to rapidly adopt AI.  Yet, many enterprises feel held back by significant challenges in their IT infrastructure, workforce, or organization’s leadership. The findings underscore the urgency in addressing data center needs to successfully deliver on their AI roadmaps and optimize performance through strategic IT service partners.”

Also Read: AiThority Interview with Asaf Somekh, Co-Founder & CEO of Iguazio (acquired by McKinsey)

Additional key findings from Flexential’s report include:

• AI receives board-level scrutiny. AI initiatives are increasingly driven by the C-suite and boards, with 53% and 46% of respondents respectively identifying these groups as the main forces behind AI adoption. This top-down pressure has increased both support and scrutiny for AI investments.
• Finding the right people for the job is difficult. 91% of respondents say they have experienced some sort of skills or staffing gap related to AI in the past 12 months, and 53% reported skills gaps or staffing shortages related to the management of specialized computing infrastructure.
• Privacy and security are a top priority. 42% of respondents whose organizations have pulled an AI workload back from public cloud said it was due to data privacy and security concerns.
• High performance requirements lead organizations to partner with experts. 51% of respondents are addressing performance issues by using third-party colocation data centers to process data closer to the edge of the network.
• Sustainability is top of mind. 94% of respondents would pay more for data centers or third-party cloud vendors to use clean or renewable energy and/or buy credits to offset their carbon footprints.

Also Read: Essential Steps for Intelligent Document Processing in Clinical Trials

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]