IT & Digital
5 min read

How to Foster AI Advocates in Your Healthcare System

Rom Cohen CIO & Co-Founder, Hyro
How to Foster AI Advocates in Your Healthcare System

The sheer growth of AI in the healthcare sector over this decade speaks volumes. We’re looking at a climb to $20.65 billion this very year, with an eye-watering leap to $187.95 billion by 2030. Those numbers aren’t just figures on a page—they’re a testament to the transformational role of AI in healthcare.


Think of it like building a high-performance car. A car’s excellence doesn’t solely rely on its engine but on every individual part working in perfect harmony. It’s about pairing the right components with precision and intention. And in the healthcare industry, AI is that turbo-charged engine revving up to propel the industry forward. What does it take to embed this powerful technology seamlessly into healthcare?

It boils down to:


  1. Building champions for the cause (AI advocates).
  2. Zeroing in on pivotal priorities.
  3. Viewing AI as more than just one tool but as several dynamic products.

Buckle up; we’re in for a transformative ride.

Building Champions for the Cause: The Role of AI Advocates in Healthcare

Defining the AI Advocate:

An AI advocate is an individual who not only understands the intricacies and potential of artificial intelligence but also passionately champions its application, promoting its benefits while addressing and alleviating concerns. They act as a bridge, linking the vast world of AI with the practical needs of healthcare.

The Significance of AI Advocates in Healthcare

Healthcare, by nature, is a field steeped in tradition, best practices, and of course, a profound responsibility for human lives. Introducing AI into this setting isn’t merely about deploying a tool; it’s about a transformative shift in how patient care is delivered, managed, and optimized. This change can often meet resistance due to concerns about efficacy, ethics, and patient outcomes.

Enter AI advocates:


  • They demystify AI for healthcare professionals, explaining in tangible terms how it can enhance patient outcomes and streamline operations.
  • They foster trust. When healthcare workers, from doctors to administrators, understand the potential of AI, they’re more likely to embrace and use it.
  • They pave the way for smoother integrations by identifying the right areas for AI application and tailoring implementations to suit the unique needs of healthcare settings.

AI Advocates in Action

Often, the best way to see the impact of something is to see it in action, so let’s do that. 


Conversational AI Example:


Take, for example, a hospital considering adopting conversational AI to manage patient inquiries. While the IT department sees its potential for efficiency, the medical staff might harbor concerns: Will it misinterpret patient symptoms? Might it depersonalize the care experience?


An AI advocate within the hospital can illustrate how conversational AI can free up administrative staff from handling routine inquiries, allowing them to dedicate more time to tasks that require a human touch. They can demonstrate how the AI system has been developed, the safeguards in place, and its efficiency in understanding and routing patient concerns. With real-world demonstrations and success stories, the advocate can build confidence in the staff, leading to a successful implementation that’s embraced hospital-wide.

Level Of Ai Automation Healthcare Call Center Leaders Are Expecting
Health System Call Center Leaders Weigh On On The Question Of Ai Automation. Source: Hyro's State Of Healthcare Call Centers Report

Zeroing in on Priorities to Amplify AI Impact in Healthcare

You can think of AI as a vast toolshed. Within it, you have a myriad of tools, each designed for specific tasks. Now, if you’re trying to fix a leaky faucet, you wouldn’t start by taking out every tool, would you? The same concept applies when integrating AI into healthcare. By narrowing down on pivotal priorities, the integration becomes more seamless, more impactful, and notably more tailored to the unique needs of the healthcare environment.

Key Focus Areas:


  • Prioritization: First things first, understanding the core objectives. What does the healthcare institution aim to achieve? Better patient outcomes? Enhanced administrative efficiency?
  • Personalization: In healthcare, personal touches matter. AI can revolutionize the patient journey, customizing experiences to individual needs, thus fostering enhanced patient engagement.
  • Anomaly Detection: AI shines in detecting nuances that the human eye might miss. From early signs of disease in medical imaging to outliers in patient data that indicate potential issues, AI can be a vigilant sentinel.
  • Automation: Streamlining repetitive tasks is the hallmark of efficiency. Marrying AI with existing healthcare procedures can revolutionize mundane tasks, from appointment scheduling to Rx management.

However, and this is paramount, the core problem needs a crystal-clear definition before diving head-first into AI’s capabilities. Imagine meeting a patient: the approach is understanding their symptoms first rather than suggesting treatments immediately. AI’s integration should mirror this – understand the challenge, then tailor the solution. And sometimes, simplicity trumps complexity. Instead of deploying intricate AI algorithms, a straightforward query could suffice.

Benefits of Adopting a Laser-Focused Approach to AI Implementation in Healthcare

  • Tailored Solutions: AI’s application aligns with the unique needs and challenges of the healthcare setting.
  • Enhanced Efficiency: By focusing on critical areas, resources are better utilized, ensuring quicker, impactful results.
  • Better Stakeholder Buy-in: Targeted projects can demonstrate early successes, building trust and confidence in AI capabilities.
  • Optimized Resource Allocation: Narrowing the focus means the right tools are used for the right jobs, conserving both time and costs.
  • Clearer Outcome Measurement: It’s easier to gauge the impact and ROI of specific, targeted AI implementations.


In essence, a laser-focused approach ensures that the integration of AI in healthcare is not just a scattergun effort but a calculated, strategic move that yields tangible, transformative results.

Viewing AI as More Than Just One Tool: Embracing its Multifaceted Nature in Healthcare

In healthcare, integrating AI isn’t about adding a singular tool to the toolbox; it’s about ushering in a suite of dynamic products, each tailored for specific tasks and challenges. To harness AI’s full spectrum, it necessitates an agile team. This is more than just having a data scientist crunch numbers; it’s about an ensemble:

  • A data scientist delving deep into the algorithms.
  • A data engineer ensuring AI’s smooth inclusion into healthcare processes.
  • A product leader discerning the needs and molding them into actionable AI solutions.
  • And crucially, a healthcare expert ensuring every solution is medically sound and patient-centric.

Together, this team crafts scalable AI assets that cater not just to the generalized but the unique, specialized challenges of healthcare.


Take, for instance, patient diagnosis. The “first mile” in this journey is understanding the myriad symptoms and conditions, then tailoring AI to aid in accurate diagnosis. This isn’t about simply throwing data into an algorithm. It’s about rigorous initial assessments, identifying the correct data subsets, and creating a solution that complements the doctor’s expertise, ensuring patients receive accurate, timely, and personalized care.

Final Thoughts on Fostering AI Advocates in Your Healthcare Enterprise

In the fastly evolving healthcare industry, AI emerges as a pivotal element, poised to revolutionize patient care and operations. Yet, its success hinges on a discerning, dedicated approach, leveraging the right tools for specific challenges. 

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About the author
Rom Cohen CIO & Co-Founder, Hyro

Rom is Hyro’s CIO & Co-Founder. He is a 2019 YJP 35 Under 35 inductee, a Cornell Tech alum, and a people-first information technology leader who earned his stripes developing Turbonomic’s Autonomic Control Platform. When he’s not burning the midnight oil resolving complex technology challenges, you can find him strolling through Central Park with his baby daughter and wife.