Dive Brief:
- Healthcare executives prioritize data considerations when it comes to using generative artificial intelligence, which could prevent them from successfully integrating the hot button technology, according to a report by consultancy Deloitte.
- While 82% of 60 respondents rated data availability, quality and reliability as a top consideration for implementing generative AI, only 45% cited mitigating biases or patient education on the technology and its risks as their greatest considerations when implementing the technology.
- Data is important, but the industry needs a “robust overarching framework” that focuses equally on governance, consumer needs and worker concerns, the report’s authors wrote.
Dive Insight:
Generative AI, which can create new content like text or images, is an attractive area for investment for healthcare sector leaders, as technology giants produce tools they say will allow clinicians to focus on patient care instead of administrative tasks.
Companies have touted products that aim to assist providers with clinical documentation, help patients schedule appointments or find clinicians, and surface key data for tracking hospital operations.
But there are worries that about a too-rapid deployment of generative AI in the healthcare sector, with some experts pointing toward accuracy and accountability concerns, as well as the risk of perpetuating biases.
The latest Deloitte report, which surveyed 60 healthcare executives, suggests leaders could have some blind spots, like concerns from their consumers or workforces, when it comes to implementing the emerging technology in their organizations.
Just half of respondents rated building trust among consumers regarding data sharing at the top of a five-point scale when asked about their greatest considerations for establishing generative AI.
More than six in ten gave top rankings to reskilling and upskilling, and 60% said addressing workforce concerns about the technology were high priorities. In comparison, 73% of executives reported legal and regulatory compliance was a major consideration, while 72% pointed to security and privacy concerns.
Organizations will need to develop effective governance models for generative AI applications to successfully integrate the tools and avoid a “long and slow ramp-up” to adoption, the report’s authors wrote.
They’ll also need to get buy-in from their workers, build trust with consumers and gather their input, and create ways to scale generative AI products.
