New guidance gives care home leaders in England a useful reason to review AI. The starting point should be a better working day for staff and better care for residents.
If you run a care home, an AI demonstration can make the possibilities look straightforward. A tool can turn a meeting into a summary or help draft a care plan. The more useful question is what happens afterwards, when your team has to check the output, act on it and take responsibility for the result.
That is where I would start: with the work you want to improve and the people affected by it.
What the new guidance actually changes
On 29 September 2026, the Department of Health and Social Care published Using AI in adult social care. It covers possible applications, from administration and care planning to monitoring, alongside practical safeguards. It gives providers a useful starting point for decisions about adoption.
Separately, the National Commission into the Regulation of AI in Healthcare published recommendations for a future regulatory framework on 10 September. Those are recommendations to government. Their publication does not itself create a new set of AI laws for care homes.
Existing responsibilities continue. CQC’s position on AI connects its use to person-centred care, dignity, safe care and good governance. CQC regulates the care provided; it does not approve individual AI products. A supplier’s presentation cannot replace your own assessment of whether a system is suitable for your service.
Start with the work that needs improving
Before comparing products, choose one recurring problem. Perhaps managers repeatedly copy information between systems, or staff spend too long assembling routine reports. Be specific about the outcome you want and how you will measure it.
Then work through the options in order. Can you remove an unnecessary step? Can you simplify the process? Does your existing software already solve the problem? Would straightforward automation do the job? Consider AI where it adds something useful.
For example, if a weekly management report takes too long, first check why the same information is being collected more than once. An existing reporting feature might remove the duplication. If an AI summary still helps, test whether it reduces the total time spent producing and checking the report.
Include licence costs, implementation, staff training and ongoing review in the calculation. A quick first draft offers little value if the checking creates more work than it removes.
Match the safeguards to the task
Administrative support can be a manageable starting point, particularly with non-confidential material. But administration is not automatically low risk: meeting notes and recruitment records may contain sensitive information about residents or staff.
Care planning needs closer scrutiny. DHSC says evidence that generative AI can produce genuinely personalised care plans is currently limited, and a member of care staff must review an AI-generated plan for accuracy. Treat it as a draft. Check it against the individual’s needs, preferences and current information before relying on it.
Clinical monitoring and decision support carry higher stakes. An incorrect alert can create unnecessary work; a missed alert could affect someone’s care. Assess the evidence for the specific purpose, population and setting.
Whether software is a medical device depends on its intended purpose and functionality. MHRA’s software guidance explains the distinction. Ask suppliers to explain the product’s status and provide evidence of any applicable regulatory compliance. The presence of AI alone does not settle that question.
Ask suppliers questions they can evidence
A useful buying conversation should go beyond a demonstration. Ask:
- What exactly is this system intended to do, and what is outside its scope?
- What evidence supports its performance in settings and with people like ours? Where does it perform less well?
- Where does our information go, who can access it, how long is it retained, and is it used to train models?
- How are errors, outages and security incidents handled? What can we export if we leave?
- How will you notify us when the model, functionality or data arrangements change?
Get answers in writing. Compare them with the contract and your actual workflow. If the supplier cannot explain an important limitation, resolve that before the pilot.
Make responsibility and data rules clear
Give staff a short, usable policy covering approved tools, permitted tasks, information they may enter, required checks and incident reporting. Name the person responsible for each use. Human review needs someone with the knowledge, time and authority to challenge the output.
Before using resident or staff information, establish the lawful basis, any additional conditions for sensitive data, and appropriate supplier and security arrangements. Keep data to what the task needs. Explain its use clearly to the people affected. Consent requirements depend on the activity and circumstances; a blanket AI consent form is not a substitute for assessing them.
Complete a data protection impact assessment where required, before processing starts. The ICO’s guidance on AI governance explains that likely high-risk processing triggers this requirement and that the assessment is case-specific. Involve your data protection lead early.
Bring residents and, where appropriate, their representatives into the discussion. Consider privacy, dignity and how people can raise concerns about technology used in their care.
Test the whole workflow before expanding
Run a bounded pilot with a named owner and agreed success measures. Use realistic scenarios within approved data arrangements, including incomplete information, incorrect outputs and system failure. For monitoring tools, test false alerts, missed events and the staff response.
Train the people who will use it on an ordinary shift. Make the fallback process clear, including how care continues during an outage and when use should stop. Record errors and feedback, and review significant supplier changes before expanding reliance on the system.
Measure the complete result: time saved after checking, quality of records, extra workload and any effect on residents. Continue only when the evidence supports it.
Choose one improvement worth making
Building the next generation of a care business starts with understanding how the work gets done. Technology should help staff deliver quality care and give them more capacity for the people they support.
At your next management meeting, choose one process that causes avoidable work. Map it with the staff who do it, agree the outcome you want and assess the simplest safe way to improve it. That gives you a practical basis for deciding where AI belongs.
Source note: Guidance checked on 2 October 2026. This article focuses on care homes in England and provides general business guidance, not legal or clinical advice.
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