If you had to pinpoint the primary force causing disruption in the data center sector today, artificial intelligence would undoubtedly top the list. The push to construct and manage AI data centers, as well as to host AI workloads in non-AI optimized data centers, is catalyzing a wave of transformations within the industry.
But what exactly does this transformation entail? To what extent has the AI revolution already unfolded in the data center space, and what can we anticipate in the future?
To address these queries, let’s delve into the significant developments in AI and data centers over the past year and explore the upcoming trends in the realm of AI and data centers.
How AI impacted data centers in 2025
Let’s begin by evaluating the changes instigated by AI in the data center domain over the past year.
A growing power crisis
Supplying data centers with adequate electricity posed challenges even before the advent of modern AI technology. However, AI has exacerbated the issue, leading data centers to encounter problems such as significant delays in connecting to power grids. Some facilities are opting to bypass the grid entirely by utilizing their own power sources – a more costly approach that may become more prevalent as AI workloads consume more power.
Agentic AI doubles down on demand for AI data centers
If the years 2023 and 2024 were marked by the widespread adoption of generative AI technology, 2025 has showcased the prominence of agentic AI – denoting the utilization of AI-powered software programs capable of autonomously executing actions.
From a data center hosting standpoint, agentic AI workloads do not fundamentally differ from generative AI workloads. Both types rely on LLMs – power-intensive AI models that businesses often deploy using specialized hardware like GPUs.
The ascendancy of agentic AI emphasizes that LLMs and the data centers equipped to host them are unlikely to be fleeting trends. Instead, they are poised to drive a surge in demand for data center capacity.
Major data center outages
Every year witnesses significant IT outages, and 2025 stands out as a year where two major service and infrastructure providers – AWS and Cloudflare – experienced substantial outage events.
These outages impacted the availability of AI services like ChatGPT, underscoring that the reliability of AI applications hinges on the robustness of the data centers and networking infrastructure supporting them.
Whether these events were mere chance occurrences or indicative of a trend toward heightened data center outage risks remains uncertain. Nonetheless, it underscores the importance of investing in infrastructure resilience.
AI Data Center Trends to Watch in 2026
Anticipate continued transformation in the data center industry in 2026 driven by AI-related trends such as the following.
Acceleration of liquid cooling adoption
In addition to consuming substantial power, AI workloads generate considerable heat. Hence, a potential trend in the upcoming year could be the increased adoption of liquid cooling systems. These systems not only offer enhanced efficiency but might be the sole solution to cool AI servers running so hot that traditional cooling methods prove insufficient.
Increased regulations on AI infrastructure
While much has been discussed regarding AI regulation, tangible actions, particularly outside the European Union, where meaningful AI compliance mandates are relatively rare, have been limited.
However, 2026 could witness a shift. Regulators may impose new requirements concerning AI workloads and their hosting infrastructure to align with objectives like sustainability, safeguarding critical AI services against cyber threats, and preserving privacy. While these changes may not impede the pace of AI data center deployment, they are likely to impact the operations of data centers housing AI workloads.
Growing edge AI deployment
Regardless of the power and scalability of a data center, transferring data over the network to end-users can be sluggish. Hence, edge AI infrastructure might gain traction in 2026. By siting AI workloads closer to users physically, edge AI can mitigate network latency issues and enhance performance – crucial for AI applications necessitating real-time responsiveness.
Preparing data centers for quantum-AI convergence
The viability and timeline for practical quantum computing remain uncertain. Nevertheless, notable advancements in this realm occurred in 2025, such as Google’s assertion in October of developing a quantum chip outpacing conventional machines by 13,000 times.
Data center operators anticipating imminent quantum practicality might invest in quantum-ready infrastructure. Reliable quantum computers could usher in a new era of AI workloads, positioning data centers primed for quantum at the forefront of both the AI and potential quantum revolutions.
More on-site power
A final trend to monitor in 2026 in data centers – reflecting the energy-intensive nature of AI – is the heightened investment in on-site power sources. These serve dual purposes:
Firstly, they reduce reliance on grid power, guaranteeing adequate energy for AI workloads even during grid failures. Additionally, they offer backup power to offset outage risks stemming from grid failures, crucial considerations in an era prioritizing AI demands and data center resilience.
