Artificial intelligence is moving from hype and speculation to practical adoption in health technology. The opportunities are endless and the potential pitfalls are real too, as I explained earlier this year.
As healthcare organizations begin to consider how AI will be integrated into their workflows, it is essential to consider what best practices should be implemented with their technology partners.
Innovate, with risk mitigation in mind
McKinsey’s Technology Outlook for 2025 states that AI is the “accelerator” of innovation; I tend to agree, but limits need to be set regarding transparency, the degree of automation and how AI is regulated.
The U.S. “AI Action Plan,” outlined by the White House in July, is focused on innovation, with less emphasis on risk mitigation than the European Union’s Artificial Intelligence Act.
Health technology innovators must focus on both innovation and risk mitigation. Because in healthcare, trust is a currency. Every tool leveraging AI should be designed with compliance, security, and regulation in mind.
Partners can start small but make a big impact
Technology partners should view their product offerings as a way to enable healthcare organizations to realize their own vision of AI. With interoperability and data backed by security measures and compliance insights, the industry can move toward seamless operations that inform care, delivery and compliance in new ways.
AI can be an additional layer within the solutions currently in use. Technology partners can explore how AI can support and improve operations, workflows or profitability, rather than overhaul or replace solutions, and make a huge impact while maintaining security and compliance.
Intentional implementation: the MEG approach
AI adoption should never be an end in itself. To ensure that each initiative delivers measurable value, technology leaders can take a structured approach like the MEG framework: maintenance, experience and growth.
- Interview covers the must-haves – the foundational investments that ensure reliability, compliance and security.
- Experience represents things to do – improvements that improve usability, trust and differentiation in the long term.
- Growth drives new initiatives – AI-driven innovations directly linked to clear ROI and measurable results.
By scaling investments in this way, organizations can integrate AI responsibly, balancing innovation with stability and trust.
Tools to get there
To reduce friction, save time, and create a qualitatively superior experience, technology partners must adopt key tools and operations to enable AI innovation at scale, including comprehensive API documentation, robust adoption of FHIR, and defined data retention and security policies.
With these foundational components in place, technology partners are poised to help providers spend less time on administrative work and more time on patient care, and help payers and pharmaceutical companies have clearer visibility into ROI, adherence outcomes, and real-world evidence. It also helps health technology providers scale more quickly and securely.
AI can be used to focus on scale, savings and informed decisions – with the right tools and partners in place. Imagine being able to visualize prescription price transparency, through AI analysis of available coupons, and provide personalized, easy-to-understand medication information directly to patients. AI can also significantly reduce reminders regarding prior authorizations, pharmacy routing, and follow-up questions.
When I think about the trajectory ahead, I am energized by the possibilities of integrating AI into technology, bringing measurable value and seamless workflows to healthcare. If technology partners can safely use AI to make better, faster, more transparent decisions across the care continuum, we will have done our job. And if we think about starting with the patient, we will solve the right problems.
Photo: Gerasimov174, Getty Images
Julian Herbert began his career in technology product development as a business analyst focused on e-commerce in the semiconductor industry. Following his curiosity, he became a management consultant at Deloitte and led divestiture and M&A integration engagements in various sectors, including pharmaceuticals and biotechnology. He then returned to product development and e-commerce at Amazon, launching machine learning solutions for third-party sellers on the platform. Julian was also responsible for leading product development for AWS startups, creating their first micro-targeted product line.
At DoseSpot, Julian leads product innovation, helping the company grow and deliver safe and reliable e-prescription technology and software integrations across multiple healthcare markets. Julian is a Louisiana native and graduated from Southern University in Baton Rouge with a bachelor’s degree in computer science. He also holds an MBA from the University of Michigan Ross School of Business, focusing on strategy and entrepreneurship.
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