AI has moved from experimentation to real-world use across enterprise systems. As Cockroach Labs’ latest report, “The State of AI Infrastructure 2026,” shows, 98% of global technology executives report that at least one AI project moved from pilot to production in the past year. It is clear that this change is well under way, but it does not mean that it does not pose new risks.
Unlike previous technology booms, AI workloads do not follow human usage patterns. AI brings automated, always-on, machine-driven demands that will likely, or already have, overwhelmed infrastructure originally designed for human speed. In this era, the question goes beyond AI adoption and focuses on whether the infrastructure can withstand the scale of AI demand.
Infrastructure is already being destroyed under the weight of human activity
Successfully running AI workloads introduces a new set of challenges across the enterprise that were previously unaddressable. Even before the AI era, Cockroach Labs research shows that enterprises are approaching architectural breaking point.
According to the latest State of Resilience report, 100% of leaders in nearly every industry experience a failure, with an average of 86 failures per year. 83% of leaders believe their data infrastructure will reach capacity to support AI growth within two years, and 34% say it will not be sustainable for the next 11 months. All of this was before the demand for AI accelerated further.
AI workloads run at machine speeds 24/7. The rapid emergence of these autonomous tools will push us to our limits before we know it. It is clear that technology leaders’ confidence in their current infrastructure is already being shaken and is not even remotely prepared to keep up with continuously running AI agents. At this point, infrastructure modernization is no longer a nice-to-have, but a necessity for business survival.
Without upgrades, financial and reputational losses can occur
Failure to modernize your infrastructure risks costly operational, financial, and reputational costs in the event of a failure. Data shows that more than half (57%) of organizations estimate that one hour of AI-related downtime costs more than $100,000. Even if a system is down 0.1% per year, it can result in up to 9 hours of uptime per year and cost more than $900,000 depending on the size of the organization. The larger the organization, the greater the costs. This is especially devastating given that most businesses don’t budget.
Outages that occur during peak periods, such as e-commerce events such as Ticketmaster pre-sales and Amazon Prime Day, or sports betting on popular events such as the FIFA World Cup, are also more costly. The potential loss of an outage is something that can never be recovered, and it also destroys customer confidence in the reliability of your operations at a time when excitement and expectations for your product were at their highest.
Despite almost half of consumers understanding and accepting that their website will slow down from time to time, more than a quarter (27%) expect seamless operation even during peak times, setting a high bar for infrastructure to meet. Additionally, 48% of consumers would consider switching brands if they encountered repeated technical errors, putting pressure on technology leaders to modernize their infrastructure to support the high demands of AI workloads while meeting consumer expectations and minimizing financial losses.
Prepare for success: Redesign operations, governance, and infrastructure as one
To ensure success as AI-driven workloads increase, organizations must act now and prioritize three key elements for future-proofing their infrastructure.
- Architecture designed for ongoing support demands: Legacy systems will not thrive in the AI era. Technology leaders must embrace modern architectures, such as distributed SQL databases, to provide enterprises with the elastic scaling needed to evolve with AI workloads, detect failures without human intervention, and mitigate rising outage costs.
- Data layer resiliency: To withstand the demands of AI, resiliency must be at the core of infrastructure operations. It’s all about ensuring that operational demands can be maintained despite heavy stress on data architectures, and leaders need to invest in the latest technology now. To ensure a resilient data layer, leaders must go beyond systems built solely for human activity and implement architectures with built-in, distributed, multi-region data layers to maintain consistency under stress.
- Stress testing and downtime modeling: Even the most advanced underlying systems can be subject to the immense pressures of AI, making benchmarking a critical component to see how your infrastructure will perform under all conditions, even the most unlikely. This level of understanding begins with benchmark measurements such as performance under adverse conditions. Adversity performance not only measures throughput under normal conditions, but also adds real-world stressors that test the database through outages that keep operators up at night. Extensive testing is the only way to truly know if your infrastructure can withstand a major outage, even under the most extreme conditions.
Considering all of these components when modernizing to AI scale is the secret to ensuring your organization is building a strong foundation for the near and long-term future.
Become a member of the winning team within the company
In the next era of AI adoption, businesses will be divided into two groups. The companies that succeed in scaling AI and the companies that struggle to survive. 63% of technology leaders already say their teams are underestimating the rate at which AI demands will outpace existing data infrastructure, yet no one is actively preventing large-scale failures. And with 74% of CIOs saying their role is at risk if they don’t achieve AI ROI within the next two years, now is the time to pay attention.
The message is clear for anyone looking to successfully scale AI beyond 2026. You need to start at the database layer, with resiliency and continuous demand as your top priorities. That’s non-negotiable. Limit financial and reputational damage before it’s too late.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/rudall30
