The Democratization of AI and the Rise of Multi-Cloud Strategies in Healthcare IT

By Jim Ducharme, ClearDATA Chief Technology Officer

Not long ago, I sat at a round table with a group of Healthcare IT leaders and asked a simple question: “How many of you have a generative AI strategy in some fashion?”

Every hand in the room went up.

My follow-up question was just as telling: “How many of you are adopting a multi-cloud strategy because of this?”

Almost all the hands stayed in the air.

My conversations with customers, colleagues, and partners have confirmed that AI is actively pushing organizations, even those who resisted it, into a multi-cloud reality. AI, and the democratization of it, is reshaping how we innovate in healthcare by enabling non-developers to build powerful solutions and empowering us to tackle some of humanity’s most critical challenges.

The Democratization of AI: Innovation for Everyone

The democratization of AI refers to the process of making artificial intelligence tools and technology more accessible to a broader, more diverse audience—eliminating the need for technical skills or expertise to use them effectively.

Not long ago, building any sort of healthcare data analysis solution required an elite team of data scientists and developers—the “builders,” as AWS would say. Today, that’s no longer the case, as we can see with user-friendly platforms like ChatGPT, and so many others, which has shown that AI is now a tool for the masses.

This shift empowers those closest to the problems to create solutions. For example, an oncologist doesn’t need to be a tech expert to see how AI can analyze patient data for hidden patterns—they just need tools that understand their data and needs.

We’re witnessing a powerful movement where domain experts like doctors, researchers, and clinicians are driving technology initiatives. They have the vision to cure cancer or improve treatments; technology is the tool.

When experts in their respective domains can build and experiment without deep technical skills, progress accelerates.

The Rise of Multi-Cloud Strategies

For years, many tech leaders held fast to a single-cloud approach. It was simpler, more familiar, and seemed more secure. However, different AI tools are often best suited for specific cloud providers, compelling organizations to diversify.

This shift to multi-cloud is influenced by factors including:

• Specialized Capabilities: Cloud providers have developed unique strengths. Microsoft’s partnership with OpenAI made generative AI accessible to the masses. Google’s Vertex AI, with its vertical-specific models like MedPaLM, speaks the language of healthcare professionals. Amazon Web Services (AWS) offers a vast toolkit, but for builders with more technical skills.
• Flexibility and Resilience: A multi-cloud strategy prevents vendor lock-in and provides the flexibility to adapt to changing business needs. If one provider experiences an outage or changes its pricing model, alternatives ensure business continuity.
• Performance and Cost Optimization: Organizations are getting smarter about how they deploy AI. One model might be 10% more accurate, but 10 times more expensive. Another might be faster and cheaper, making it ideal for high-volume, lower-complexity tasks. A multi-cloud approach allows for A/B testing and the ability to route and triage tasks to the most efficient and cost-effective AI model, no matter which cloud it’s on.

To get the best results, healthcare organizations, whether it’s pharmaceutical companies, HealthTech innovators, payers, or life sciences organizations, are now using the best tool for the job, by combining the capabilities of multiple cloud environments.

Healthcare organizations are now running an “and” strategy, not an “or” strategy when it comes to leveraging various cloud platforms, by leveraging the strengths of multiple platforms to strengthen their business goals.

Governance in a Multi-Cloud Healthcare Strategy

This more decentralized world of innovation creates opportunity, but also poses governance and security challenges. When AI tools are being adopted across various departments—often without central oversight—it gives rise to “Shadow AI.” This is the modern version of Shadow IT, where technology is implemented without the knowledge or approval of the IT department.

While this drives growth, it can lead to chaos without a central governance strategy for healthcare. A doctor using AI to cure children is not focused on securing data in a cloud environment. Yet, if patient data is compromised, the CISO is responsible, and the patient suffers.

You can’t stop innovation, nor should you. Instead, healthcare organizations must govern it by providing a secure foundation that lets teams innovate safely. Think of it as guardrails on the innovation highway.

Multi-Cloud Innovation for Healthcare: Use Cases

The convergence of AI democratization and multi-cloud strategies is driving profound, human-centered change. A powerful example of AI in healthcare innovation is its potential use in pediatric cancer treatment, where advanced technologies can support early diagnosis, personalized care plans, and improved patient outcomes in children’s hospitals.

Doctors are using AI to analyze the data from visits between doctors and young patients. A child might say something that seems innocuous during a single visit. But after ten visits, the AI can detect patterns in these seemingly harmless comments that a human might miss.

It can flag potential adverse reactions to medication, allowing doctors to adjust treatments that walk the fine line between saving a child and harming them.

In the world of payers, AI is being used to detect and prevent fraud on a massive scale. By analyzing patterns in claims submissions, AI can spot anomalies that might indicate abuse in much the same way we have been using machine learning to detect financial fraud for years.

These examples highlight how those closest to the problem can now harness AI to create innovative and impactful solutions.

AI and Multi-Cloud Security for Healthcare

The goal is to let your smartest people drive as fast as possible, focused entirely on the road ahead, while a robust security framework acts as the advanced safety systems in the car—keeping them in their lane and protecting them from unforeseen dangers.

This requires a comprehensive multi-cloud security approach that is secure, compliant, and resilient. Your healthcare organization should:

• Ensure Unified Visibility: See all workloads and data flows, regardless of which cloud they reside in.
• Enforce Consistent Controls: Apply security policies uniformly across all environments to eliminate weak links.
• Automate Compliance: Continuously monitor for compliance with regulations like HIPAA, especially when handling sensitive patient data (PHI).
• Leverage Cloud Detection & Response: Use Managed Detection and Response (MDR) services to identify and mitigate cyber threats or ransomware attacks before they cause damage.

Let ClearDATA Secure Your Multi-Cloud Innovations

The democratization of AI and the rise of multi-cloud are foundational shifts that are unlocking unprecedented opportunities for innovation.

For healthcare organizations, your mission is to foster a safe environment for innovation by embracing multi-cloud, empowering domain experts, and implementing strong governance to protect your organization and sensitive data.

At ClearDATA, our mission is to help you build that secure foundation. We provide the guardrails that allow you to focus on what truly matters—whether that’s curing cancer, developing life-saving medical equipment, or transforming your industry.

Our team of experts and managed services, plus our one-of-a-kind cloud security posture management (CSPM) platform, gives you everything you need to protect PHI in the cloud.

Let us handle the complexities of securing your multi-cloud environment, so you can focus on pushing the boundaries of what’s possible and solving humanity’s greatest challenges.