Cloud-First Architectures and AI: The Dual Engines Driving Healthcare’s Transformation

Healthcare’s rising costs, growing patient volumes, and workforce shortages have left the industry at a tipping point. These inherent challenges are further compounded by the fact that by 2050, the number of adults over 85 is predicted to triple, which will intensify the strain on an already stretched system. While these challenges aren’t new, they are becoming harder to work around. 

And at the same time, there’s an urgent push to improve patient outcomes while making operations more efficient—all while the cost of care continues to climb. The American Hospital Association reported that hospitals’ labor costs, which, on average, account for 60% of a hospital’s budget, increased by more than $42.5 billion between 2021 and 2023. How do we balance it all? 

The answer lies in technology, and two solutions stand out: cloud-first architectures and artificial intelligence (AI). I’ve seen firsthand how these technologies can completely reshape and redefine the future of healthcare.

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Why Cloud-First is the Way Forward

Think of healthcare’s IT infrastructure like the foundation of a house. If it’s built well, everything built on top of it will be stronger. But for too long, healthcare has been stuck with outdated, disconnected systems that make it difficult to share data, streamline workflows, and adapt to the industry’s growing challenges. A cloud-first approach that implements cloud platforms like AWS can provide the scalability, flexibility, and security that traditional systems can’t match. 

But beyond that, moving to the cloud unlocks something even greater, which is the ability to harness data in ways that weren’t possible before. By centralizing data in cloud-based repositories (or “data lakes”), healthcare organizations create a foundation for AI-driven insights. And this approach isn’t about technology for technology’s sake. The goal is to make it easier for healthcare leadership to make smarter, faster decisions that improve patient care and operational efficiency.

AI’s True Potential

We already know that AI can automate routine tasks and help reduce human error, and much of the general public is on board with its use. In fact, 53% of consumers believe generative AI will improve access to healthcare, while 46% believe AI will make healthcare more affordable. But AI is only as good as the strategy behind it. My organization focuses on what I like to call “authentic AI”—solutions that are thoughtfully designed and purpose-built to solve real problems.

Take provider onboarding, for example. Right now, getting a new provider up and running can take weeks or even months. It involves manually entering data into multiple systems, tracking down paperwork, and navigating a complex web of administrative processes. AI can help by automating data transfers between systems, which cuts down on the time and manual effort required. This one change means healthcare staff can spend less time on paperwork and more time focusing on patient care.

Furthermore, the cost savings can be massive. Administrative expenses make up about 15% to 30% of total health spending, which is three times what the U.S. spends on cancer care annually. If AI can help reduce even a fraction of those costs, the financial benefits for healthcare organizations – and ultimately patients – are huge.

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Data is What Powers AI

AI’s effectiveness highly depends on the quality and breadth of the data it’s trained on. That’s why having a strong data strategy is just as important as the AI itself, or perhaps even more so. Healthcare organizations need a centralized data platform that pulls information from across the entire healthcare ecosystem. When AI has access to comprehensive, high-quality data, its predictive capabilities become far more accurate.

Interoperability is also important. Think of it as a universal language that disparate systems like mobile apps, third-party systems, and electronic health records (EHRs) use to communicate. If a hospital’s AI solutions are pulling insights from just one system – for instance, its EHRs – it’s missing several pieces of the data exchange puzzle. Having the ability to pull data from multiple sources helps healthcare organizations make informed, data-driven decisions at every level.

Where Does Security Come in? 

In healthcare, patient data security is the foundation of everything we do, and data breaches can have serious – and costly – consequences. 2024 saw 14 data breaches, which led to the records of 237,986,282 U.S. residents – nearly 70% of the U.S. population – being exposed or compromised. And the financial implications are alarming: the average cost of a healthcare data breach in 2024 was $9.77 million.

That’s why a “security-first” mindset should be embedded in every aspect of cloud and AI deployment. It’s important that security frameworks meet the highest standards, i.e., strong encryption, proactive threat detection, and continuous testing to protect against emerging (and evolving) risks. At the same time, reducing entry points through consolidated platforms can help minimize vulnerabilities and strengthen overall security. 

The Real Impact of the Cloud and AI

At the end of the day, the success of cloud-first architectures and AI isn’t measured by how many systems migrate to the cloud or how sophisticated an AI model is; it’s measured by the real-world value these technologies bring to healthcare organizations, and most importantly, patients. That value comes in many forms like increased efficiency, better decision-making, cost reduction, and improved patient outcomes. When healthcare teams have the right information at the right time, patients receive better, safer, and more effective care.

We’re at a defining moment in healthcare’s digital transformation. Cloud-first architectures and AI are revamping the very fabric of patient care. By prioritizing interoperability, automation, and data-driven insights, we can build a healthcare system that’s more human-centered. The future of healthcare is about using technology to create better outcomes for everyone involved. And with the cloud and AI leading the way, that future is closer than ever.

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