Nordic recently partnered with Modern Healthcare to survey U.S. healthcare executives on their readiness in foundational preparations for AI implementation. The findings provide valuable insights into AI governance, infrastructure, and training priorities at healthcare organizations of all sizes. Healthcare leaders should recognize opportunities for improvement in technology infrastructure and data capabilities to realize long-term success in AI.
Overcoming infrastructure challenges
Healthcare organizations face significant challenges scaling AI initiatives. Many healthcare leaders are confident in their AI readiness, but the reality is that most still require substantial improvements to support scalable AI solutions. Over half of the respondents acknowledged that their existing systems need further development, yet only 15% reported having infrastructure that is easily scalable.
Key areas identified as critical infrastructure elements needing investment include:
- data integration and interoperability;
- data processing and analytics;
- data security.
To successfully scale AI, healthcare organizations must focus on strengthening their data capabilities. Less than half (44%) of healthcare leaders rate their organization's ability to securely and effectively manage large datasets for AI applications as moderately capable, with significant gaps in data management and security.
The primary data challenge reported is scattered data across disparate systems, hindering seamless integration. Further complicating an organization's ability to manage and prepare data for AI include issues like:
- inconsistent or erroneous data;
- poor documentation;
- and lack of proper tools.
To unlock the full potential of AI, addressing data readiness challenges is essential, ensuring that healthcare organizations can leverage clean, well-organized data to drive AI innovation.
Closing the AI governance gap
While healthcare executives recognize the importance of AI governance, many are still in the early stages of developing the necessary policies, culture, and oversight mechanisms. Survey results show that close to three quarters of respondents (70%) express confidence in their AI governance yet report that existing governance structures need improvement to support responsible AI innovation.
Only about half of survey respondents report having a team or department that manages or oversees AI-related projects and technologies. Within this group of respondents, only 41% report having a dedicated steering committee created specifically for AI initiatives. The effectiveness of AI teams may vary as many teams share responsibilities in managing and overseeing other technologies.
Healthcare leaders should prioritize building strong governance structures that ensure clear accountability, alignment with organizational goals, and ongoing evaluation of AI’s impact and effectiveness.
Training to optimize AI expertise
Proper training and expertise across the enterprise are critical to ensuring AI preparedness. But, the survey results highlight that only 6% of healthcare organizations prioritize AI training and have extensive programs in place, and nearly half are just beginning to prioritize AI education. This lack of formal training poses a significant risk, as organizations may struggle to differentiate between AI solutions that provide real value and those that are hype.
Many organizations heavily rely on internal resources, such as IT departments and clinical staff, for guidance on AI implementation. To fully leverage AI, healthcare leaders must invest in comprehensive training programs across all levels of the organization. Developing a skilled workforce with the knowledge to evaluate and implement AI effectively will put healthcare organizations in the best position to make informed decisions and ensure successful integration.
Moving forward: Learning from key insights
Explore the executive research brief to gain deeper insights into the challenges and opportunities surrounding AI adoption in healthcare. The survey highlights findings on:
- scaling AI infrastructure;
- addressing data management and security gaps;
- establishing effective governance frameworks;
- and building AI expertise across organizations.
Healthcare leaders can take proactive steps to strengthen their AI strategy to align with successful AI implementation and adoption by understanding these critical areas.
Would you like to assess your organization’s AI readiness? Contact us to schedule time with a Nordic expert.