AI may be the future, but it’s also a hacker’s playground – Are you prepared?

A new report by Flexential, a provider of secure and flexible data center solutions, reveals that rising investments in artificial intelligence (AI) by enterprises are significantly escalating their exposure to cybersecurity threats. According to the 2024 State of AI Infrastructure Report, a staggering 95% of surveyed IT leaders believe that their organizations’ investments in AI have made them more vulnerable to cyberattacks. This finding underscores the urgent need for a comprehensive approach to cybersecurity as AI continues to permeate business processes.

The report, which gathered insights from 350 IT leaders from companies with annual revenues exceeding $100 million—including 100 respondents from firms with revenues over $2 billion—paints a grim picture of the current AI landscape. A crucial finding is that 40% of respondents admitted their cybersecurity teams lack the necessary skills and understanding to effectively protect AI applications and workloads. This knowledge gap is particularly concerning given that 54% of respondents noted that the complexity of AI applications inherently increases the attack surface for potential threats.

AI Complexity Demands Better Cybersecurity Training

The glaring gap in cybersecurity expertise among IT teams is a critical issue that organizations must address. The complexity of AI applications and their ability to interact with multiple systems simultaneously mean that any vulnerability can lead to significant data breaches or other cyber incidents. This risk is compounded by the rapid pace at which AI is being adopted across various industries. Companies need to invest in specialized training programs to upskill their cybersecurity teams to understand the unique challenges posed by AI technologies. Simply relying on existing protocols or general cybersecurity knowledge will not suffice. The stakes are too high for organizations to gamble with their data security.

Shift to Colocation and Edge Computing: A Strategic Move to Mitigate Risks

Faced with these cybersecurity challenges, many organizations are reconsidering their AI infrastructure strategies. The report highlights that 42% of enterprises have moved their AI applications and workloads from public cloud environments to colocation data centers. This shift is driven by heightened data privacy and security concerns, allowing companies to exert tighter control over sensitive information by leveraging on-premises or third-party data centers and private clouds. In line with this trend, 51% of organizations are deploying AI workloads closer to the edge of the network to optimize performance and reduce latency, although this could potentially increase cybersecurity vulnerabilities.

Balancing Cost and Security in AI Deployments

While the shift to colocation data centers and edge computing provides a higher level of control over data and reduces latency, it is not without its challenges. Moving data storage and processing closer to the edge can indeed increase an organization’s exposure to threats if not managed correctly. Enterprises must carefully weigh the trade-offs between cost, performance, and security. Colocation can provide a more secure environment than the public cloud, but it requires a robust strategy that includes continuous monitoring, regular security audits, and strong partnerships with data center providers. Organizations must avoid the temptation to cut corners on security in pursuit of performance gains.

Performance Challenges and Skills Gaps Undermine AI Deployments

Another critical finding from the report is the widespread performance issues related to AI infrastructure. Over the past year, 82% of organizations have reported facing performance challenges with their AI workloads, with 43% citing bandwidth shortages and 41% mentioning unreliable connections as major barriers. These issues are particularly alarming because most existing data centers were not originally designed to support high-density computing and low-latency requirements associated with AI applications.

Moreover, the report underscores a significant skills gap that threatens the successful deployment of AI projects. A substantial 53% of respondents highlighted staffing shortages in managing specialized computing infrastructure, while 47% reported deficiencies in handling advanced networking technologies like Software-Defined Networking (SDN) and Network Functions Virtualization (NFV). This reliance on third-party colocation data centers and external expertise to bridge the skills gap underscores the challenges organizations face in their AI journey.

AI Infrastructure Needs a Strategic Overhaul

The performance bottlenecks and skills shortages highlighted in the report are significant barriers to the widespread adoption of AI technologies. For organizations to fully realize the potential of AI, they must prioritize investments in infrastructure modernization and workforce development. This involves not only upgrading data centers to handle the demands of AI workloads but also investing in talent acquisition and retention. Building partnerships with third-party providers can offer immediate relief, but it is not a long-term solution. Organizations must take a proactive approach by fostering a culture of continuous learning and development to stay ahead in the AI race.

Urgent Need for Robust Disaster Recovery and Resilience Strategies

Flexential’s report also calls attention to the pressing need for robust disaster recovery strategies that go beyond basic protection measures. As noted by Will Bass, Vice President of Cybersecurity Services at Flexential, the rise in AI use across various sectors comes with a proportional increase in risks that could potentially disrupt business operations. He stresses that enterprises need to embed resiliency into every layer of their IT infrastructure, rigorously test disaster recovery plans, and ensure uninterrupted service while enhancing detection and response capabilities.

Resilience is the New Imperative in AI Strategy

As AI becomes increasingly embedded in critical business functions, the emphasis on resilience cannot be overstated. Organizations must recognize that disaster recovery is not just a checkbox exercise but a critical component of their overall AI strategy. Regular testing, scenario planning, and investment in resilient infrastructure are no longer optional; they are necessities. Companies that fail to incorporate these elements into their AI roadmaps risk facing severe operational disruptions, which can have long-lasting impacts on both their reputation and bottom line.

The Path Forward for AI and Cybersecurity

Flexential’s 2024 State of AI Infrastructure Report provides a sobering reminder that as organizations aggressively pursue AI-driven transformation, they must not overlook the foundational elements of cybersecurity, infrastructure, and talent development. The rapid adoption of AI brings both opportunities and risks; how companies manage this delicate balance will determine their success in an increasingly AI-driven world. As enterprises continue to invest heavily in AI, aligning infrastructure investments with evolving business and security requirements will be crucial to mitigating risks and fully harnessing the potential of these transformative technologies.