Billing and Posting Clerks

That doesn’t mean machines do everything alone. In practice companies use “robotic process automation” (RPA) and AI to handle the easy, repetitive parts while people handle surprises and customer questions. For instance, one case study described using RPA in an insurance office to process a big backlog of claims: automation cut the backlog by half and almost eliminated errors, freeing staff to focus on tricky cases ^[2].

In healthcare billing, McKinsey notes that AI systems are being used to check claims and reduce paperwork – potentially saving hundreds of billions of dollars in administrative costs ^[2]. The common outcome is that clerks now often augment their work with technology. Software might generate draft bills or check figures, and clerks review and fix anything the machine can’t handle.

In short, machines do much of the boring calculation, while people still solve problems that need judgment, explanation, or personal touch ^{[2] [2]}.

On the other hand, adoption is not instant or uniform. Integrating AI tools takes planning and money. Smaller offices or clinics may not have big IT budgets, and healthcare/financial records are tightly regulated, so any automated system needs to be accurate and secure.

Studies and experience show that simple pilot projects often fail if data and processes aren’t carefully set up. As a result, some companies move slowly. For example, a U.S. labor report found that jobs considered “at risk” of automation have not fallen off a cliff; companies often automate gradually ^[3].

In billing, managers balance the cost of software and training against steady labor costs. Because of this, many firms start by using AI to assist rather than replace clerks – for example, automating data entry and letting people handle the rest.