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    Home » News » Healthcare organizations still struggle to operationalize AI at scale: Arcadia study
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    Healthcare organizations still struggle to operationalize AI at scale: Arcadia study

    healthadminBy healthadminJune 18, 2026No Comments2 Mins Read
    Healthcare organizations still struggle to operationalize AI at scale: Arcadia study
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    Despite the increase in the use of artificial intelligence, healthcare systems and organizations across the United States are lagging in its integration, according to a new study from Arcadia.

    Although 52% of respondents report that AI can fundamentally change healthcare with the right applications, nearly half (53%) of AI insights are only “partially integrated” into decision-making processes, and only 14% report that they are fully integrated at “key decision points.”

    This healthcare platform study garnered insights from 281 healthcare leaders across providers, payers, and service organizations at the HIMSS26 conference in March.

    “Healthcare leaders are increasingly united around the potential of AI to improve care and drive measurable value, but many organizations are still working to operationalize that capability,” Michael Meucci, president and CEO of Arcadia, said in a statement. “The next wave of AI value won’t come from better models; it will come from better execution. Organizations that can successfully incorporate AI insights into their daily decisions and workflows will be best positioned to realize meaningful clinical, operational, and financial impact.”

    21% of respondents report that AI is most valuable in certain scenarios, and a further 21% report that solutions provide the most value in combination with “strong human oversight.” Only 6% of respondents reported that they view this technology as more dangerous than valuable or overhyped.

    31% of respondents cited day-to-day decision-making as a challenge in scaling AI responsibly. Other needs for responsible implementation included education (27%), strengthening data infrastructure (22%), and measuring effectiveness (20%).

    “As healthcare leaders move beyond experimentation, success will increasingly depend on the ability to incorporate AI into decision-making and workflows that improve care, reduce costs, and deliver measurable outcomes,” said Meucci.

    Healthcare leaders want AI to deliver measurable business outcomes, citing cost savings (33%), reduced turnover (27%), and improved financial forecasting (21%) as the most important outcomes.



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