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    Three barriers to artificial intelligence adoption

    Artificial intelligence (AI) will play a major role in healthcare digital transformation, according to new research.

    The study, “Human Amplification in the Enterprise,” surveyed more than 1,000 business leaders from organizations of more than 1,000 employees, with $500 million or more annual revenue and from a range of sectors, all in the U.S.

    Survey respondents from the healthcare sector indicated that the following AI-supported activities will play a significant role in their transformations: Machine learning (77%), robotic automation (61%), institutionalization of enterprise knowledge using AI (59%), cognitive AI-led processes or tasks (50%) and automated predictive analytics (47%).

    The research also found that almost half of the respondents in healthcare indicate their organizations’ priorities for automation initiatives is to automate processes to:

    •  Increase productivity (83%)

    •  Reduce costs (40%)

    •  Minimize manual errors (40%).

    DalwaniDalwani

    “This suggests that many processes in the healthcare sector are still manual-driven and produce a high volume of errors as a result,” says Sanjay Dalwani, vice president and head of hospital and healthcare at Infosys. 

    The survey found that 73% of respondents want AI to process complete structured and unstructured data and to automate insights-led decisions. It also found that 72% want AI to provide human-like recommendations for automated customer support/advice.

    More widely, healthcare sector respondents shared that the top three digital transformation goals of their organizations are to build an innovation culture (65%), build a mobile enterprise (63%) and become more agile and customer-centric (58%). 

    “The findings underscore that healthcare organizations are well on their way with starting to work alongside AI to selectively use it to inform and improve patient care,” Dalwani says. “However, in this process, it’s pertinent that the industry establishes ethical standards as well as metrics to assess the performance of AI systems.” 

    The study also indicates that as automation becomes more widely adopted in healthcare, employees will be retrained for higher-value work, according to Dalwani. “Healthcare organizations can benefit from redirecting a section of this talent to managing and ensuring ethical use of AI,” he says.

    Even though the majority of enterprises in the healthcare and life sciences sector are undergoing digital transformation, few have fully accomplished their goals. This is due to three primary reasons, according to Dalwani:

    1. Lack of time (64%)

    2. Lack of collaboration amongst teams (63%)

    3. Lack of data-led insights on demand (61%)

    Furthermore, when healthcare IT professionals were asked about the challenges of adopting more AI-supported activities as component of their digital transformation initiatives, 78% of respondents indicated lack of financial resources, 78% state lack of in-house knowledge and skills around the technology and 66% say there’s’ a lack of clarity regarding the value proposition of AI, according to the study.

    “This suggests that the healthcare IT sector still has a long way to go in terms of AI buy-in,” Dalwani says. “Until more senior level IT-decision makers are bought into the benefits of bringing AI to healthcare, teams won’t have access to the proper resources to support full-scale implementations.” 

     

     

     

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