Ambient scribes convert verbal patient-provider interactions into structured notes for clinical documentation and, eventually, medical billing. Useful, of course. The innovation saves time. But at least one study suggests the financial impact is unclear.
That is likely to be a recurring issue for many types of artificial intelligence features and apps.
The issue is that faster task completion, reduced human error, and streamlined workflows do not always translate that into immediate financial gains. In fact, financial impact might be neutral to negative at first precisely because time and money has to be spent to implement the solutions.
This perhaps is not unusual for new technology solutions. Enterprise resource planning (ERP) systems also promised efficiencies, such as the ability to generate reports faster. Still, the financial payoff wasn’t instant. As always, firms had to redesign their business processes to scale up.
Likewise, cloud computing cut information technology overhead and boosted agility, but early adoption did not always lead to an immediate financial outcome.
Perhaps AI operational wins are the low-hanging fruit. Customer service chatbots reduce call center workload, but revenue metrics do not automatically improve.
A 2023 Gartner report suggested 60 percent of AI projects improve process metrics, but only 30 percent show clear financial uplift within a year, for example.
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