Investment Trends in Healthcare AI

The COVID-19 pandemic has accelerated the pace of artificial intelligence adoption, and industry stakeholders are confident AI in healthcare and machine learning can help solve some of today’s toughest challenges. According to a recent survey from KPMG, eighty-two percent of healthcare and life sciences executives want to see their organizations more aggressively adopt AI technology and are escalating their investments in AI. Fifty-six percent of healthcare and life sciences business leaders report that AI initiatives have produced more value than expected and that making processes more efficient using AI is a top priority.

Healthcare executives say present AI investments at their organizations are focused on EHR system management and patient diagnosis. According to executives, AI has proven valuable in decreasing errors and improving medical outcomes for patients. Around forty percent of healthcare executives reported AI technology has helped with patient engagement and improved clinical quality. Roughly a third of executives said AI has improved administrative productivity. Eighteen percent said artificial intelligence in healthcare has helped uncover new revenue opportunities to date.

But AI investments are predicted to pivot somewhat over the next two years. The survey found thirty-eight percent plan to prioritize telemedicine, thirty-seven percent on robotic tasks such as process automation and thirty-six percent on delivery of patient care. Clinical trials and patient diagnosis finished out the top five investment areas.

The survey found AI is mainly used at life sciences companies during the drug development process to contribute to better record-keeping the application process, and to help with clinical trial site selection. Roughly half of life sciences executives reported their organizations plan to use AI to reduce administrative costs and bottlenecks, dissect patient data and quicken clinical trials. Over the next two years, pharmaceutical companies will likely focus their AI investments on discovering new revenue opportunities, a course change from their current strategy focused on increasing profitability of current products. 

The FDA recently released its first AI and machine learning action plan, a multistep approach designed to advance the agency’s management of advanced medical software. The regulatory action plan aims to force manufacturers to be more rigorous in their evaluations.

It seems, the greatest challenge to AI adoption in healthcare is not whether it will be capable enough to be useful, but rather ensuring it gets properly adapted into daily practice. Over time, healthcare providers may put their focus more toward tasks requiring unique, personal skills, that require the highest level of human interaction. Perhaps the only healthcare organizations that will lose out on AI’s potential will be those who refuse to work in parallel with it. 

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Blog by: The ForeSee Medical Team