Training and Capacity Building for AI Adoption

Effective use of AI in rural healthcare depends on whether staff and providers have the training, support, and technical assistance needed to successfully use new AI tools in their daily work. Introducing AI into clinical, financial, or operational activities without adequate training can increase workload rather than reducing it.

Rural healthcare leaders shared that staff are overburdened and often do not have the extra time to learn a new technology on their own. As a result, organizations need to plan for training and ongoing support as part of AI implementation.

For AI adoption to be successful, cross-disciplinary training programs should reach across roles, including clinicians, leadership, and administrative staff. Training should focus on the clinical, technical, and operational aspects related to integrating AI into existing daily workflows.

Training approaches should include hands-on demonstrations, troubleshooting, and ethical considerations to build confidence and trust. For example, key training topics include using AI to support diagnosis, interpret AI-generated data, and apply AI data to clinical decisions.

Some rural organizations may have limited staff with technical expertise to support AI adoption. As a result, ongoing technical assistance is often needed. This may include support from AI vendors, as well as access to staff or partners with expertise in change management to lead them through the adoption process. Leveraging tele-education platforms and partnerships with academic institutions can also help overcome geographic barriers and staffing constraints.