Embracing Generative AI: A 7-Point Strategic Plan
by Steve Shi, Chief Technology Officer, Pager
In the ever-evolving world of healthcare, one technology stands above all others in its potential to drive growth and innovation: Generative AI (GenAI). Like the internet and smartphones, GenAI is no fleeting trend. It is a catalyst for unprecedented change and enhanced productivity that is already redefining the healthcare industry.
To help your organization rise to the forefront of GenAI implementation and unlock its vast potential, Pager recommends the following 7-point strategic plan:
1. Adopt Risk Management for the GenAI Context
GenAI implementation introduces a range of new risks, ranging from model-related issues and data integrity to compliance challenges in a fast-changing legal landscape. Businesses must proactively identify, assess, and mitigate these risks to maintain a secure and responsible GenAI environment.
2. Start Today
Given the vast potential of GenAI, this is no time for hesitation. Businesses must actively start evaluating opportunities to integrate GenAI into their operations, particularly in high-value use cases that can streamline processes and produce cost efficiencies. Inaction will leave organizations behind, especially in healthcare, where vast amounts of data and complex procedures make it exceptionally fertile ground for GenAI-driven innovation.
3. Modernize Your Technology
Fully embracing GenAI necessitates a comprehensive technology infrastructure modernization. This involves phasing out outdated systems, integrating GenAI into software platforms, and adopting automation in IT operations for streamlined workflows.
· Example:
Transition to cloud-based systems that support scalable AI deployments. Utilizing platforms like Google Cloud, Azure, or AWS for deploying AI models can enhance computational power and storage capabilities. Pager has developed an “AI Built-in” architecture, which connects AI models with cloud native architecture, including microservices, open APIs, and event engines, ensuring the entire application suite can benefit from the value of Gen-AI development.
4. Build an AI-Compatible Infrastructure
Seamless GenAI integration into existing technological frameworks is crucial for success. A cohesive and interconnected ecosystem requires an organization's GenAI to interact seamlessly with current AI models and data sources.
· Example:
Integrate AI APIs into existing healthcare management systems to enhance functionality, such as using NLP APIs for processing and understanding patient records and clinical notes.
· Example:
Ensure interoperability between GenAI tools and EHR (Electronic Health Records) systems for seamless data flow and analysis.
5. Enhance Data Management
Remember, GIGO (Garbage In, Garbage Out) still applies. Quality and accessibility of data are paramount to GenAI's effectiveness. Businesses must prioritize refining their data architecture, particularly in handling complex and unstructured data, to ensure accuracy and availability of data for GenAI to reach its full potential.
· Example:
Implement advanced data preprocessing and cleaning tools to handle unstructured data such as clinical notes, medical images, and genomic data.
· Example:
Use data anonymization techniques to maintain patient privacy while making datasets suitable for AI training and analysis.
6. Create Specialized GenAI Teams
Establishing dedicated teams to oversee GenAI initiatives is essential for successful adoption and standardization across all organizational levels. These teams should have the expertise to guide effective and impactful GenAI integration.
· Example:
Assemble a cross-functional team with skills in machine learning, data engineering, healthcare informatics, and clinical expertise to work on specific AI projects like personalized care delivery plans.
7. Provide GenAI Training
Investing in the education and training of key personnel, such as software developers and data engineers, is crucial. Customized training programs tailored to various roles and expertise levels will equip your workforce with the necessary skills to navigate the GenAI landscape effectively.
· Example:
Conduct workshops and certification programs on AI for healthcare professionals, focusing on how AI can assist in their specific roles.
· Example:
Partner with online learning platforms to provide continuous learning opportunities in advanced AI topics like neural network-based deep learning, natural language processing, and RAG and other methods of fine tuning on top of a base LLM.
Conclusion
Embracing GenAI is not merely a technological upgrade; it's a strategic decision with far-reaching consequences for propelling your organization to the forefront of innovation. By adhering to these seven strategies, businesses can translate GenAI's potential into tangible business value, establish themselves as leaders in the GenAI revolution, and secure a long-term competitive edge in a rapidly evolving digital world.
