Every private healthcare company; independent neuro-physiotherapist, case management company, supported living company or domiciliary care provider is now living through the same technology change in landscape.

The significant technological shift in how AI is beginning to shape the future of healthcare is moving at a very fast pace, making it a challenge to keep up.

Philip’s Future Health Index 2026 found that 56% of UK healthcare professionals are already turning to personal AI tools when workplace solutions fall short. That gap between informal use and formal governance is exactly where regulatory risk lives.  This new report finds AI is helping clinicians save time, expand capacity and support decision-making, while significant gaps in training and workplace readiness remain.  At a glance from the report:

  • 42% of UK clinicians say AI-enabled tools save them more than 132 hours a year on average;
  • More than a third (36%) say AI is helping them see more patients, an average of seven additional patients per week;
  • Nearly half (45%) report improved work-life balance;
  • 74% say their company’s AI training is inadequate or inconsistent. 

Why this is a Governance Question – what the CQC have to say

In May 2026 the Care Quality Commission published its first formal position on AI in health and social care, making clear it does not approve individual technologies but expects AI use to sit within the same fundamental standards that already govern every provider:

  • Regulation 9: Person-centred care – ensuring people have the information needed to make informed choices.
  • Regulation 10: Dignity and respect – protecting privacy and ensuring fair treatment.
  • Regulation 11: Consent – ensuring staff understand the care or treatment being proposed when seeking consent.
  • Regulation 12: Safe care and treatment – ensuring equipment including AI, is safe to use.
  • Regulation 17: Good governance – maintaining effective oversight, risk management and monitoring.

CQC explains: “We do not assess or approve specific technologies but have a role in ensuring that technology, including AI, contributes to safe, effective and equitable care across all settings and settings. Most regulations that we enforce have a role in making sure that innovative technologies, including AI, improve the quality of care and outcomes for people using services.”

AI can support decision-making, but it cannot replace it.  Providers of care must be able to explain how decisions are made, where human judgement sits and how risks are monitored.

CQC inspectors are not waiting for AI-specific guidance to act on, as an example, a provider was rated Inadequate after confidential care records were run through AI tools with no risk assessment and no governance framework.

So, what is the Role of an AI Champion?

An AI Champion is not necessarily your most senior manager or your most technical staff member. It is often a frontline team member who already understands the day-to-day workflow, is trusted by colleagues and is curious enough to test tools properly before they spread informally.

Industry guidance describes the role as a “bridgebuilder”- connecting compliance, IT and frontline staff, translating between “tech speak” and operational reality, and anticipating where staff will push back or misuse a tool (The AI Champion’s Playbook by Medium).

In a domiciliary care or case management setting, that could be a registered manager, a senior carer, or a compliance lead – anyone with credibility and consistency, not necessarily a job title. 

What a Good AI Champion should have in place

For a CQC-regulated provider, the practical remit should include:

  • An AI systems register – what tools are in use, what they do, what data they touch and who authorised them.
  • A simple risk assessment for each tool – covering data protection and accuracy, feeding into your existing Data Protection Impact Assessment (DPIA) process.
  • An acceptable-use standard staff can easily follow, with clear rules on what must never go into an AI tool (any document that has personal information that would identify an individual).
  • A feedback loop – noticing when a tool starts producing errors and escalating it through existing incident-reporting channels rather than letting it go unrecorded. 

Choosing Your AI Champion

Ask these three questions below when identifying the person in your team who would make a great AI Champion:

  • Who on the team already experiments with AI tools without being told to;
  • Who do staff naturally go to with a “can this help me” question;
  • Who understands your regulations and compliance obligations well enough to say no when a shortcut isn’t safe.

The right person usually sits at the intersection of curiosity and caution and would be happy to carry out a ‘data protection impact assessment (DPIA)’ as well.

The small private healthcare businesses that get ahead won’t be the ones with the most AI tools; they’ll be the ones who can show exactly who is responsible for them.