The floodgates have opened when it comes to AI and hospitals. Vendors and internal advocates alike are knocking on the doors of CIOs, asking for funding.
We’d better get used to it—and have a process to deal with the requests. Data suggests the use of AI in healthcare will expand substantially in the next decade. Researchers project AI in healthcare will grow from a global marketplace value of almost $27 billion in 2024 to more than $613 billion by 2034.
And for good reason: AI solutions promise reduced costs, improved diagnoses, refined robotic surgical techniques, better monitoring of patients, and reduced paperwork and billing headaches. Who wouldn’t want these results?
Establishing a Seven-Step Comprehensive Process and Sticking to It
That said, moving too fast could have consequences. The challenge for CIOs is not how to say “No,” but how to say “Yes.” We must start by developing an AI readiness strategy that avoids a “shiniest object first” approach or a “ready-fire-aim” decision tree.
Such preparedness to adopt, implement, and effectively use responsible AI technologies requires these seven components:
- Data Infrastructure: IT must have the right data management systems in place, addressing the quality, accessibility, trust, and security of data. Remember: garbage in, garbage out.
- Technical Expertise: Staff and teams require sufficient knowledge of AI, machine learning, and related technologies. This includes all roles and all leadership levels understanding the infrastructure that AI requires to support its potential.
- Business Alignment: AI adoption must be aligned with business goals, ensuring AI applications solve relevant problems and create value.
- Cultural Readiness: Organizations must foster a culture that is open to innovation, change, and the use of AI-driven insights for decision-making through an effective and efficient governance model.
- Ethical and Legal Considerations: Hospitals need frameworks in place for the responsible use of AI, including addressing issues like fairness, transparency, accountability, and compliance with relevant regulations. This is crucial for the governance model.
- Change Management: Prepare ahead of time for the changes AI programs will bring to workflows, job roles, and the organizational structure.
- Financial Investment: Allocate the necessary resources, both for upfront investments in AI technology and for ongoing maintenance and improvements.
A CIO’s Imperative: Ask the Right Questions
A CIO’s job is to assess the readiness of the organization to capitalize on AI opportunities while managing the associated risks and challenges. In this sense, the reaction to an AI proposal should be no different than any technology request. Does it comply with the governance model? Does it align with the technology roadmap? How will related data remain trusted? How will this technology integrate with other IT initiatives and frameworks? Does it advance patient care? How does it impact revenue? Ultimately, is it a priority or a distraction? How can we guarantee its success?
With these seven processes and disciplines in place, CIOs will be better prepared for the AI Gold Rush that’s hitting all of us right now!