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  • Vignesh Shetty, Senior Vice President and General Manager, AI and Platform, GE Healthcare

Vignesh Shetty, Senior Vice President and General Manager, AI and Platform, GE Healthcare

Describe your career to date

At the heart of GE HealthCare’s data and artificial intelligence (AI) infrastructure and Cisco’s prior to that, my role as the digital data and platform leader is to build bridges from an idea to reality and break ties when teams get blocked. At its core, my team is laying the platform to unlock the boundless potential of our data and AI capabilities to address both clinical and operational challenges in healthcare.  

Our mission is audacious yet simple: to create a world where healthcare has no limits. We envision a future where diseases are not just managed, but prevented; where treatment is not just personalized, but predictive. We are not working in isolation. We are collaborating with our customers, building technology and tools that accelerate the development of smart devices, digital capabilities, and disease state-based care solutions. Our collaboration is the catalyst for innovation, transforming healthcare one data point at a time. 

How are you developing the data literacy of your organization, including the skills of your data teams and of your business stakeholders? 

It is a multi-pronged approach. Focus on usefulness, not volume of training: We are not teaching abstract statistics; we are equipping teams with practical skills to ask the right questions of data and unearth actionable insights.  

  1. Our goal is to empower caregivers and providers to translate complex AI outputs into clear patient care decisions,  

  1. Think more Aesop, less Einstein. We translate complex data concepts into simple, relatable stories. After all, humans are wired for narratives. Imagine explaining a new risk prediction model through the analogy of a weather forecast, not a dense mathematical formula.  

  1. Make data digestible, not intimidating. We are building interactive dashboards, chatbots, and clear visualizations so we meet our employees and stakeholders wherever they are in the data journey.  

  1. Learn by doing, not doctrine. We create opportunities for hands-on learning, not just lectures. Think hackathons or innovation challenges where healthcare professionals and data scientists collaborate to solve real-world problems using real-world data.  

By following these principles, we are fostering a culture where data is not a black box for the chosen few, but a shared language for driving better healthcare outcomes. It is about empowering everyone to become data-informed decision-makers, not just data consumers. 

What role do you play in building and delivering conventional artificial intelligence solutions, including machine learning models? Are you also involved in your organization’s adoption of generative AI?  

In my role at GE Healthcare, I play a pivotal part in the development and delivery of solutions that internally leverage machine learning and deep learning models. The responsibilities of my team span the entire AI solution lifecycle, from working backwards from the customer identified problem, data collection and preprocessing, to model development, validation, and deployment for both our own AI models and integrating models from our ecosystem of partners into existing clinical and operational workflows.  

I work closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to ensure that our AI solutions are tailored to meet specific business needs and are integrated seamlessly into our existing infrastructure. This involves not only technical expertise in developing robust and efficient machine learning models but also a deep understanding of our business domain to ensure that our solutions are practical and impactful.  

In terms of generative AI (genAI), my team is actively involved in exploring and advocating its adoption within our organization to drive both clinical outcomes for our customers and internal productivity for our employees. I believe genAI has immense potential in healthcare, from creating synthetic patient data for research to generating 3D medical images for improved diagnosis. We are currently collaborating with our research teams and partners to pilot projects in this area and have been providing inputs on the strategic direction for the adoption of these advanced AI techniques.  

My role is not just about building and delivering AI solutions, but also about driving innovation and shaping the future of AI in healthcare at GE Healthcare. I am committed to leveraging both conventional and gen AI to deliver high-impact solutions that enhance patient care and outcomes. 

How are you preparing your organization for AI adoption and change management? 

At GE HealthCare, we understand AI is not just a shiny new tool – it is a transformative force. That is why we are not just throwing AI solutions at problems and focused more on how AI assist with solving those challenges; we are preparing our organization for a smooth and successful AI adoption.  

1. Leadership as the lighthouse: Our leaders are champions for AI, not bystanders. They actively communicate the why behind AI adoption, ensuring everyone understands how AI will augment, not replace, human expertise.  

2. Transparency is key: We believe in open communication about AI capabilities and limitations using our AI principles.  

3. Upskilling, not upscaling: Weare investing heavily in AI education for all employees. This does not mean turning everyone into data scientists; it is about equipping everyone to understand how AI works, how to interact with it effectively, and how to leverage its insights.  

4. Change management champions: We are fostering a network of AI champions across departments. These individuals become internal advocates, helping colleagues navigate the new landscape and troubleshoot concerns.  

5. Focus on the human touch: We recognize that AI is a tool, and humans remain the decision-makers.  

Our focus is on building human-AI collaboration, not blind reliance on automation. The goal is to start small, scale smart – we are prioritizing high-impact, low-risk AI implementations to showcase the benefits and build confidence. This crawl, walk, run approach avoids overwhelming the organization with disruptive change. 

Vignesh Shetty
has been included in:
  • 100 Brands 2024 (USA)