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Writer's pictureLaurie M. Orlov

AI and the Future of Care Work

Updated: Jan 23

The Rise of the AI Caregiver

Laurie M. Orlov

Principal Analyst, Aging and Health Technology Watch


EXECUTIVE SUMMARY


Life expectancy for the 65+ is lengthening into mid-80s and for some even longer. While many older adults may thrive in their later years, it is likely that as individuals age, some will need more care-related services. These needs may be a result of chronic illness, disability, vision or hearing loss, or mobility limitations. The care providers that will serve this group will be drawn from families, healthcare, private duty home care, senior living (Independent and Assisted), as well as Skilled Nursing Facilities (SNF).


In parallel with the aging of the population there is a well-documented shortage of workers that provide or contribute to care. This shortage came into sharp focus during Covid-19 as professionals of all types left their jobs – today, many have not returned. Burnout among healthcare providers is well-documented; turnover has worsened across senior care organizations – and some care providers may turn away work or schedule patients far into the future.


At the same time, more care work is migrating away from institutions and into the home, driven by preferences of both care recipients and families, institutional costs, and patient frustration with access. As that happens, more tech-enabled services are now available from providers and tech vendors offering ‘Healthcare in Place.’ Opportunity has emerged for AI’s machine learning features that help care providers by capitalizing on larger and even unstructured data sets like text and notes to support detection or prediction of possible problems.


Emerging offerings such as virtual sitters in hospitals, AI-enabled medical documentation, diagnostic algorithms, avatars and voice-enabled chatbots are promising tech improvements that today augment work and fill gaps in care. However, there are limitations and barriers to broader adoption that will need to be overcome. These include perceived trust issues, lack of data integration across boundaries, and the unknown role of government regulation. But even as the

product possibilities and implications are not yet fully understood, the next five years will bringbetter definition, expanded capability and growing adoption.


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