AI in Social Care needs to be about outcomes, not technology
By Thomas Tredinnick, CEO and Co-Founder, Ally Cares
As the use of AI grows across social care, so does the debate about what it should – and shouldn’t – do. Reflecting on Care Home Professional’s recent discussion, Could advanced technology undermine the human side of care?, Thomas Tredinnick considers why the answer lies not in how much technology we adopt, but in the outcomes it enables for residents and the people caring for them.
I recently read Care Home Professional’s discussion on whether advanced technology could undermine the human side of care, and there was a lot in it that resonated with me, particularly the point that providers need to start with the problem they are trying to solve rather than starting with AI and looking for somewhere to apply it.
I would take that one step further. As a sector, I think we need to be careful that adopting AI, or any new technology, doesn’t become an objective in itself. The measure of success isn’t how sophisticated the technology is, how much data it can process or even how many processes it can automate; it is whether using it leads to better outcomes for the people receiving care and the teams supporting them.
Much of the conversation around AI has understandably focused on efficiency, whether that is reducing administration, making processes quicker or helping care teams access information more easily. All of that has value, particularly in a sector facing considerable pressure, but if efficiency becomes the primary measure of success, we risk overlooking what could be a much more important opportunity.
For me, that opportunity is using AI to help us understand things about residents that we simply haven’t been able to understand before, and then using that understanding to improve the care they receive.
Care has always had gaps in information, particularly during the time residents spend alone in their bedrooms. A member of the care team might see somebody at 10pm and again at midnight, but traditionally there has been very little information about what happened during those two hours unless the resident used their nurse call system or somebody physically entered the room.
A resident may have woken repeatedly, been coughing, moved around their room several times, attempted to get out of bed or shown signs of discomfort, and while any one of those events may not appear particularly significant in isolation, together they can begin to tell us something about that resident and potentially help explain what the care team sees the following day.
This is where I think AI becomes genuinely valuable. It can help identify patterns across information that it would be impossible for a person to continuously observe and make that information available to the people who actually know and understand the resident. The outcome might be recognising a change in behaviour sooner, identifying possible signs of deterioration, understanding why somebody is unusually tired or simply having better information when reviewing that person’s care.
That doesn’t remove the human element of care at all. Used properly, I believe it strengthens it. Technology can provide information, but it is the care team who understands the individual, recognises the context and decides what that information means for the care they provide.
The Care Home Professional discussion also raises important questions around fragmented data, trust and governance. As more AI enters social care, providers will increasingly need to understand not only what a system can do, but where its information comes from, how it is protected, how reliable its outputs are and what happens when the technology gets something wrong.
That becomes particularly important when we are dealing with information that could influence decisions about somebody’s care. AI can produce an answer with confidence, but confidence is not the same as accuracy, which is why human oversight, clear governance and evidence of how technology performs in real care environments have to remain fundamental.
The same principle applies to interoperability. Providers already have systems containing information about medication, nutrition, care planning, incidents and many other aspects of a resident’s life, and simply adding another source of data doesn’t necessarily improve care if that information remains locked within a separate platform. The opportunity is to bring those different sources together so that care teams can develop a more complete picture of each resident over 24 hours and use that understanding in everyday care planning and decision-making.
There is also an interesting wider opportunity here for how we understand and evidence quality. Much of care quality has traditionally been assessed retrospectively through records, incidents and periodic inspection, but increasingly rich data could allow providers to understand what is happening within their homes much more continuously. Used responsibly, that could help identify changes earlier, demonstrate where care is improving and give providers stronger evidence about the outcomes they are achieving.
As AI becomes more widely adopted, I therefore think providers should become increasingly demanding about evidence. Calling something “AI-powered” tells us very little about whether it is useful, safe or capable of improving care. Providers should be asking what problem it solves, what evidence supports it, how information is protected, how it works alongside existing systems and, ultimately, what measurable difference its introduction is expected to make.
Through Ally’s own work with care providers, the NHS and ICB partners, I have become increasingly convinced that the most valuable role technology can play is not to make care less human, but to give the people providing that care a better understanding of the people they are supporting.
AI can process information, recognise patterns and highlight changes, but it is the care team who understands what those changes mean for an individual resident and decides what to do next. If technology gives them better information on which to make those decisions, then rather than undermining the human side of care, it has the potential to support it.
Ultimately, the success of AI in social care won’t be measured by how much technology we adopt, but by what changes for the people we care for.
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