Cloud migrations, driven by data and AI, are back on the drawing board

Fast Company

07-07-2025

It's still early days, but we are obviously witnessing the burgeoning impact that artificial intelligence (AI) is having in many areas of business. This AI-fueled progress may have a related effect—it could prompt more organizations to initiate cloud migrations.
You may be thinking, 'Been there, done that.' And while it's true that the cloud model has served businesses well for more than 20 years, there's still a lot of room to grow. By some estimates, the cloud market is on pace to surpass $1 trillion within the next few years.
Here's why I'm convinced that AI will help drive this continued momentum. At the top of the list: The advantages of the cloud model are as compelling as ever, especially with AI. Cloud services deliver the most up-to-date tools and technologies, speed of development, and cost flexibility—all of which are essential to organizations shifting their AI initiatives into higher gear.
But it's more than that. Many of the latest and greatest AI capabilities—large language models, generative AI (GenAI), and, more recently, agentic AI—are cloud-native by design. Organizations that want to implement those leading-edge technologies and integrate them into their own applications and operations will find it faster and easier to do so if their data and AI infrastructure are in the cloud.
One of the biggest motivators behind cloud migration is data readiness. AI requires accurate, well-managed data, both from outside sources and a company's own private data. Agentic AI raises the bar. Consider that today's newly emerging AI agents are capable of reasoning and taking actions autonomously. Business leaders can not afford to have bad customer experiences or employee missteps as a result of agents running on off-target data. Even a 1% error rate means trouble because it can lead to repeated mistakes.
For example, one global biopharmaceutical company took a big step forward by migrating 96% of its data to the cloud. With modern infrastructure, the company has been able to perform clinical trials faster, reduce IT costs, and improve team productivity by 40%. This also laid the foundation for them to integrate AI-powered capabilities in areas like drug development. With clean, well-governed data readily accessible, the company is better equipped to leverage AI responsibly, including agentic AI systems that require data precision.
MORE THAN STORAGE AND INFRASTRUCTURE
Another potential driver of cloud migration is that AI-powered data management can automate and accelerate the development of data pipelines. Today, the tools and platforms to do this most effectively are cloud-based. Everything from data quality to integration and governance can be ushered along with speed and efficiency using ChatGPT-like GenAI copilots and agents.
In other words, cloud migration is about more than storage and infrastructure. Think of it in terms of AI agility. In the cloud, developers and tech teams can build, test, and deliver at the speed of business.
A note about speed: Nothing is moving faster than agentic AI. A simple three-step readiness plan is to identify early use cases for AI agents, prepare the data, and ensure that the infrastructure can meet and exceed your performance criteria. Cloud computing, which scales on demand, may be the best option.
I'm bullish about this trend, but realistic. Not every business application or workload can be immediately moved to the cloud. Some organizations, particularly in regulated industries, may face data residency or other governance requirements. The good news is that they may still be able to use cloud tools for data preparation, even when their databases and storage systems are located on premises, making many of the advantages still available.
One stopper that sometimes stands in the way of modernization is legacy architecture. Some businesses continue to extend the life of systems that may be 10 to 20 years old (or more!). At some point, however, the law of diminishing returns comes into play. What's gained by keeping those tried-and-true systems running may come at the expense of business innovation.
CIOs and CTOs seldom go all-in on the cloud in one fell swoop. Migrations typically happen as a matter of priority, one application, workload, or data center at a time. Now, with GenAI and agentic AI projects increasingly moving from proof of concept to enterprise deployment, the business case for another round of cloud migrations is getting stronger.