At the AHRA 2025 Annual Meeting, held at Paris Las Vegas, medical imaging leaders from across the country gathered to learn, discuss evolving technologies, and strengthen their leadership in a rapidly changing healthcare landscape. The event offered a dynamic mix of educational sessions, collaborative discussions, and opportunities to connect with peers. This recap of Sara Nofzinger-Drew’s session “Transforming the Radiology Revenue Cycles Through AI” gives a glimpse into the best practices being shared at AHRA 2025.

According to session presenter Sara Nofziger-Drew, artificial intelligence (AI) is making a huge impact on the radiology revenue cycle management (RCM). This automation will improve efficiency and accuracy, automate tasks, and can provide insights for optimization. Using AI as part the RCM process can help minimize revenue loss, reduce human capital burnout, and boost patient satisfaction.

Despite what level of AI you have heard of, you may use AI more than you know. The robotics process automation type is commonly used with Alexa or Siri prompts. These forms can be used for repetitive tasks. Machine learning can be used to make predictions or improve performance or accuracy without being programmed. Large language models (LLM) are commonly used with agents like Chat GPT, and generative AI are algorithms or generative models that create new content like text, audio, or visuals. Today we learned that LLM can produce appeal letters in just seconds. The time it would take human capital to do so is much longer. There are many benefits to using AI in your radiology RCM. AI will increase efficiency, reduce waste, standardize processes, identify trends, and enhance compliance. This utilization can have major impacts to operations in such a positive way. By accelerating cash and liquidating inventory, human capital can be used for much more and find their work exciting. When human capital is engaged and valued, they want to come to work and are willing to put their all into it. AI can help radiology departments retain their staff.

The key areas for implementation can be used for manual data entry work, claim processing, data automation tasks, and patient processing. The days of completing paper HCFA 1500 forms manually are long over. AI can process your claims, tackle appeals, and retrieve denials. AI is where the world is headed. In radiology RCM, we don’t need to worry about AI replacing human capital. We need human capital to understand how AI can make this important work more efficient and automated to get more done, quicker, and with greater results.