Like most industries, healthcare is experiencing financial pressure and unprecedented AI advancements. Organizations are also grappling with a political and economic environment that is more dynamic and complex than ever.
The currency of the past, present, and future is high-quality data. It’s one of the most strategic assets we have in healthcare, and that’s true for patients, providers, employers, payers, life sciences companies, and governments.
Data is fueling the AI revolution, but it must be aligned with solving business challenges. What should healthcare organizations prioritize as 2026 unfolds? They need sophistication in both data and AI, which requires sound strategies, including the following points.
Insist on high-quality, sustainable data
According to a report by L.E.K. Consulting, the healthcare industry accounts for about 30% of the world’s data volume and has a projected annual growth rate of 36%. This means healthcare data doubles in size every about two years. This growth rate is faster than that of other industries, including financial services, manufacturing, and entertainment.
Data is abundant, but not all of it is valuable. Organizations need to validate and curate their data sources to ensure they’re drawing meaningful insights from them. They must be able to put disparate data sources together to get a more complete picture of emerging trends. Ultimately, high-quality, diverse, and task-specific data translates into better system model accuracy and robustness.
Data sources must also be sustainable, meaning there are assurances of quality and cost stability over time. Timely updates, completeness, reliable aggregation, and many other factors are not one-time activities.
Sustainability is even more important with the expanded use of AI models. Organizations invest significant amounts to train AI on datasets, and if data sources are unreliable or prices spike, those investments could be at risk.
Know your users and how they work
Healthcare organizations aren’t falling for AI hype. They will only make room in their budgets for applications with a clear use case and return on investment. To make wise investments, leaders need to fully understand their users and how they work.
Because when leaders understand how their teams get work done, they can better connect data and point solutions into workflows to drive efficiency. They can drive AI adoption when the technology is seamlessly integrated into the task at hand. For example, instead of having clinicians log into a separate tool to find precise dosing information for a neonatal patient, they can simply use their clinical decision support tool with AI-powered search to get answers from trusted data sources.
Understanding how teams get work done also enables organizations to recognize when it is time to reinvent workflows and change the paradigm. For example, Amazon has recently introduced a new robotics system, an agentic AI tool and smart glasses for delivery drivers as means to reduce repetitive tasks, improve safety and boost productivity. The company says the innovative advancements are about technology working with employees to solve complex business challenges.
Incorporating user feedback is critical for success. Organizations and vendors can only achieve continuous improvement through large-scale user interactions and feedback loops.
Expect (but don’t fear) AI disintermediation
Disintermediation is another way of saying “cutting out the middleman.” Some people and organizations have been slow to adopt AI because they fear it will replace them. But this hesitancy could mean they miss out on the opportunities of this moment.
It’s true that AI is shifting workforce trends across industries. The World Economic Forum (WEF) Future of Jobs report in 2025 found that technological advancements – particularly AI and information processing – are the most significant contributing factors to the anticipated loss of 92 million jobs worldwide by 2030.
But this loss is offset by an expected increase of 170 million jobs worldwide during the same period, for a net gain of 78 million jobs. Authors of a Stanford University paper point out that in professions where AI is a tool in the hands of skilled workers, we see employment growth.
Another sign that AI is an opportunity for growth and expansion is the uptick in investment in AI opportunities in health IT. Investors put an estimated $10.7 billion into seed- through growth-stage funding to companies in AI-powered health tech categories so far in 2025. That means 2025 funding is already 24% higher than funding raised in all of 2024.
For smaller startups with niche AI applications, the risk of disintermediation is greater. They are finding they cannot compete with platforms that can add AI to more robust sets of capabilities they can deliver at scale. Enterprise technology platforms are well-positioned to acquire and integrate the most successful point solutions from the venture capital ecosystem.
Guard against cyberattacks.
Stolen credentials. Phishing. Deep fakes. The attacks keep coming, and AI is enabling threat actors to deploy very convincing appeals for sensitive information. The risk is high in healthcare; A recent survey found that 93% of healthcare organizations experienced a cyberattack in the last 12 months, with 3 in 4 reporting these attacks disrupted patient care.
The National Institute of Standards and Technology detailed in a recent publication how attackers are manipulating AI systems as a new vector for cyber threats. Bad actors attempt to change how AI systems respond to input, “poison” AI by introducing corrupted data, learn sensitive information, or insert incorrect information to subvert the system’s intended use.
Recognizing the continued vulnerability of these systems is an essential first step to combating cyberattacks. Healthy governance when selecting new technologies or data sources can help mitigate the risk, allowing access to sensitive data only under strict compliance. Cybersecurity training for team members is also essential to keeping the workforce vigilant. Companies must insist on due diligence, even as the pressure increases to adopt AI and other emerging technologies.
2026: Find certainty with data and AI sophistication
The value of high-quality data and advanced technology, and using them for better healthcare – these are not new concepts. It’s the level of sophistication required to succeed that keeps increasing every year. Our preparation now will shape the future of health IT. By embracing these sound practices, we can transform challenges into opportunities, drive meaningful progress, and build a more intelligent and resilient healthcare system for everyone.
Photo: Wong Yu Liang, Getty Images
Gerry McCarthy is Chief Executive Officer for Merative, a data, analytics, and software partner for the global health industry.
McCarthy has been in health information technology for 30 years, most recently serving as CEO of eSolutions, a revenue cycle management solution that exited to Waystar in October 2020. Before eSolutions, he was the President of Transunion Healthcare and held several executive leadership roles at McKesson.
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