AI Meets Medical Coding: Progress Requires an Eye on Workforce

AI and machine learning are transforming healthcare at a breakneck pace—but progress isn’t all smooth sailing. As systems get smarter, the need for a smarter workforce grows too. According to a recent AHIMA survey, 75% of respondents say upskilling is essential just to keep up with the accelerated use of AI and other advanced technologies.

For leaders, the real test is balancing high-tech automation with the deep, often irreplaceable, human expertise that’s been built over decades. This is especially true in Health Information (HI) and medical record coding, where legacy teams are the backbone of operations.

AI and computer-assisted coding (CAC) tools have streamlined workflows, offering faster data processing and real-time code suggestions. These systems can flag documentation gaps and help manage the growing volume of health data.

But in medical record coding, speed means nothing without accuracy—especially when reimbursement is on the line. Coding errors don’t just slow things down; they lead directly to payment delays, denials, and compliance issues.

Coding Expertise Alongside AI Capability is a Win-Win for Revenue

Even the most sophisticated AI and CAC systems are only as good as the data they’re built on—which often means working with outdated, incomplete, or biased information. These tools still can’t fully grasp clinical nuance, contextual clues, or the layered decision-making that skilled coders bring to the table. Recognizing these limits is key to navigating the constantly shifting terrain of medical record coding.

Human coders stay current with evolving documentation guidelines, coding updates, and complex patient care scenarios. They apply clinical insight and critical thinking—qualities no algorithm can consistently replicate across a system governed by strict and often ambiguous regulations.

Strong coding teams also serve as a frontline defense against lost revenue and compliance risk. According to JAMIA, coding errors can shrink clinic revenue by 10% to 30%. Acute care providers aren’t immune either—the AMA reports $36 billion in annual losses tied to denials and fines from improper coding.

Technology alone won’t solve these problems. Effective coding demands a hybrid approach: smart tools paired with experienced professionals who know how to use them.

Coder Know How Improves AI Outcomes and Long-Term ROI

Human oversight is critical to making sure automation serves its purpose—not just adding speed but actually improving outcomes. Just as clinicians are essential to successful EHR use, coders bring deep institutional knowledge to the table when assessing and implementing new technologies. Their role is essential to:

Ensure new tools fit seamlessly into documentation, coding, and billing workflows—without disrupting operations or sacrificing accuracy.
Review the data and logic behind new systems to confirm reliability and relevance.
Align system outputs with strict compliance rules—and adapt them as regulatory requirements evolve.
Meeting these standards ensures that coding technologies support the organization’s goals rather than create new problems. It’s not about choosing between people or technology—it’s about combining the best of both to get the job done right.

At TruBridge, we combine technology with experienced coding professionals to help organizations manage today’s complex healthcare landscape. Our scalable solutions adapt to evolving needs, giving coding teams the tools and support they need to stay accurate, compliant, and efficient.

Discover how TruBridge helps your organization stay agile, compliant, and future-ready.