With the surging worldwide interest in artificial intelligence, IT professionals are eyeing hybrid cloud as the perfect IT infrastructure solution to realize AI’s phenomenal potential fully.
AI has stormed onto the scene at an incredible pace. Two short years ago, it wasn’t front and center in the public consciousness. Still, it is a tool known primarily to IT insiders as an integral, but not particularly exciting, resource used in various analytical applications. But with the launch of ChatGPT in November 2022, and the subsequent burst of discussion about AI’s game-changing potential in nearly every industry, it has become a driving force for rethinking cloud infrastructure.
Why Hybrid Cloud is the Perfect Partner for AI Applications
Even before AI shook up the world, hybrid cloud was already making its presence known. A cloud setup involving a combination of public cloud, private cloud, and some on-premise data center solutions, hybrid cloud’s use has grown exponentially over the last few years. According to the Flexera 2024 State of the Cloud Report, 73% of respondents had adopted hybrid cloud.
The secret to hybrid cloud’s growing popularity? It offers the best of both worlds regarding scalability, elasticity, and security. These same factors have made it appealing in AI circles. With hybrid cloud, organizations can strategically utilize the scalability and flexibility of public cloud services to manage resource-intensive AI workloads, such as training large datasets while private cloud environments offer a secure solution for handling sensitive data and applications that require stringent compliance.
Beyond some of the more obvious advantages listed above, hybrid cloud offers several additional benefits featured below. You can also learn more about our hybrid-first mindset here.
Cost Efficiency and Resource Optimization
One of the most compelling arguments for adopting a hybrid cloud for AI is cost efficiency. Setting up and maintaining the infrastructure necessary for large-scale AI projects can be extremely expensive. With the hybrid cloud model, businesses can optimize their spending by tapping into the public cloud for more demanding AI tasks, without having to purchase the additional infrastructure themselves.
Besides saving money, hybrid cloud also makes better use of resources. AI projects often need special hardware like GPUs or TPUs, which are costly to buy and maintain. By using a hybrid cloud, companies can access these tools on a pay-as-you-go basis via the public cloud. This approach not only cuts down on expenses but also gives companies the freedom to try out new AI technologies without having to heavily invest upfront.
Enhanced Data Management
Data is the backbone of AI, and managing it well is key to making any AI project successful. Hybrid cloud offers several advantages for data management. For instance, users can enjoy the added security of private cloud while also helping to meet industry compliance regulations regarding restricted access to specified data. Meanwhile, less sensitive data can go into the public cloud, where it can take advantage of the cloud’s scalability and powerful analytics tools.
Hybrid cloud also supports a unified data management strategy by enabling seamless integration of data across on-premises and cloud environments. This is especially important for AI, where data from different sources often needs to be aggregated, cleaned, and pre-processed before being used to train models. By centralizing data management, hybrid cloud cuts down on the stress and inefficiency of managing data in separate systems, freeing up AI teams to focus on what they do best: developing innovative solutions.
Accelerating Innovation and Time-to-Market
Hybrid cloud is not just about cost savings and efficiency — it’s also a powerful enabler of innovation. By providing IT teams with on-demand access to AI’s vast computational resources, hybrid cloud removes many of the barriers that can slow down AI development. This accelerates the pace of experimentation and iteration, allowing companies to bring AI-driven products and services to market faster than ever before.
For example, in the healthcare industry, innovators are leveraging AI to develop personalized treatment plans based on patient data. AI requires rapid analysis of large datasets, which can be efficiently handled by a hybrid cloud environment. By leveraging the public portion of hybrid cloud, healthcare providers can quickly develop, test, and deploy AI models, ultimately leading to better patient outcomes and a competitive edge in the market. At the same time, the private side of hybrid cloud is advantageous for restricted patient data.
How Lightedge Can Help Businesses Harness AI’s Game-Changing Potential
The rise of AI presents both opportunities and challenges for businesses. To fully capitalize on its potential, executives must ensure their organizations have the right infrastructure in place. That means partnering with a cloud provider offering the full spectrum of cloud options – public, private, hybrid, and multi-cloud services.
Lightedge has been the leader in compliant cloud and colocation for nearly three decades. Our team has significant expertise in helping customers adapt to their changing business needs. Through the power of hybrid cloud, we’ve helped businesses accelerate their AI initiatives, optimize their resources, and maintain a competitive edge in an increasingly AI-driven world.
Our goal is to ensure each workload operates where it delivers the most value, whether on-premises, in a private cloud, or across multiple public cloud platforms. Contact us today to get started!
