AI is making significant strides in many industries, but its adoption in long-term care facilities remains slow and challenging. While AI has the potential to revolutionise patient care through fall detection, bedsore prevention, and sleep quality assessments, the road to widespread deployment has been anything but fast. This is an issue of great importance for investors, care home managers, and system integrators, all of whom are keenly aware of the transformative potential AI offers. Yet, despite its promise, AI in long-term care is not being implemented at the speed or scale we might expect.
That isn’t to say AI should be thoughtlessly embraced without any safeguarding or checks, but there is a clear apprehension in the care industry that is causing the sector to fall behind with the times. If you look elsewhere, there is more openness to AI coming from other industries, even in different health sectors. AI is being utilised more and more to diagnose diseases, or to train health workers and to make their lives easier, so why should it not be the same in long-term care?
What Venture Capitalists Should Know
For venture capitalists, long-term care AI is appealing for several reasons. First, healthcare software is typically sold through recurring licensing agreements, which makes companies offering these solutions prime acquisition targets. Companies with recurring income streams, especially in a sector as robust as healthcare, are attractive for acquisition at premium valuations. Recent market activity underscores this: for instance, in July 2024, Nordic Capital acquired Oslo-based Senso, while Avasure picked up San Francisco-based Ouva, signalling a hotbed of investment in the long-term care space.
But despite these market drivers, VCs frequently ask, “Which technology will dominate?” There are many contenders – wearables, radar, and optical sensors—but identifying the winning solution is not easy for them.
Care Home Managers: Navigating Competing Agendas
The core issue for long-term care providers is a growing staff shortage. AI can help by increasing caregiver productivity by 20-30%, making it a crucial tool for maintaining quality care in the face of resource constraints. However, managers need to be aware of the competing agendas among suppliers. Many system integrators have established long-term relationships with care homes, and they might not be fully incentivized to embrace AI. The reason is simple: their revenue depends on selling and maintaining current, often outdated, systems. These systems are beginning to be overshadowed by the introduction of AI, that simplifies everything and uses less equipment, such as only one camera where it can be combined with computer vision learning.
Long-term care facilities rely heavily on these outdated technologies, often installed by system integrators with vested financial interests in maintaining the status quo. The list of products currently in use includes infrared motion sensors, door contacts, acoustic monitoring, bed sensors, and wearable devices. While these systems are functional, they are far from optimal in that they generate so many false alarms that care givers develop alarm fatigue. The advantage to the system integrators is that these systems require frequent maintenance and support.
For system integrators specialising in security, the long-term care market presents a promising opportunity. Security is an overcrowded, competitive space—a “red ocean”. In contrast, long-term care facilities represent an emerging “blue ocean” thanks to the introduction of AI. There is money to be made by those willing to pivot to this burgeoning market, but they must understand the unique challenges that AI brings to the table.
The Overwhelming Problem in Care
The problems facing the long-term care sector are immense and twofold:
- Increased demand for care, driven by a rapidly ageing population and longer life expectancy.
- A dwindling supply of caregivers, exacerbated by declining birth rates over the past several decades. A recent analysis found that the UK fertility rate is falling faster than any other G7 nation, dropping by 8%.
Globally, the market for care beds is set to explode—from 63 million today to 121 million by 2050. The challenge is how to meet this rising demand while managing limited human resources. Care workers across the globe are already overworking, with long working hours, poor pay and high stress, causing more and more of them to understandably leave the industry.
Why AI Adoption Is Taking So Long
The slow uptake of AI in long-term care boils down to four key factors:
- System Integrator Resistance: AI threatens to replace the multiple sensors currently used in care facilities with a single, camera-based solution powered by advanced computer vision. This, in turn, threatens the revenue streams of incumbent system integrators. In many ways, this situation mirrors other well-documented business battles—like Netflix vs. Blockbuster or digital cameras vs. Kodak and Polaroid. The disruptive potential of AI is clear, but the reluctance of existing players to embrace it is equally evident.
- Hardware Lag: MIT robotics expert Rodney Brooks points out that while software adoption happens at lightning speed (think of ChatGPT reaching 100 million users in two months), hardware takes far longer to implement. AI-powered solutions require physical cameras, cabling, and installation, which inherently slows down the adoption process.
- Training and Cultural Barriers: In long-term care, young caregivers learn on the job from more experienced staff. While this mentorship model has its advantages, it also creates a significant barrier to adopting new technologies like AI. Caregivers trained in traditional methods are often resistant to learning how to work with advanced systems, which can slow down integration.
- Perception: AI has come under immense criticism, sometimes understandably but sometimes due to a lack of education on the subject. There is a fear that AI is going to replace jobs in healthcare, taking away income from hard-working people. However, when AI is created and applied correctly, the goal is not to take away jobs, but to enhance and make people’s jobs easier and allow them to focus on the important parts of care work.
Conclusion: The Future Is Here—But it’s arriving slowly
AI offers transformative potential for long-term care, but the adoption process is far slower than it needs to be. Care home managers must recognize the opportunity AI presents for improving productivity, even if it challenges the existing supplier landscape. Venture capitalists should keep an eye on vision technology that unifies and improves current fragmented systems. System integrators who pivot to offer AI-based solutions in long-term care can position themselves for success in a growing and underserved market.
Ultimately, the introduction of AI into long-term care will be a slow but inevitable process. The question isn’t if AI will transform this sector, but how quickly it will happen—and who will lead the charge.
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