Many practices have policies sitting on TeamNet or shared drives that have been downloaded, adapted and reviewed over the years. They exist because they have to exist. The challenge is turning those documents into something that genuinely helps teams understand what they need to do and why.
That’s exactly the challenge Wayne set out to tackle when reviewing his practice’s Mandatory Training Policy.
Rather than starting with a blank page, Wayne turned to Concordia AI.
He uploaded CQC’s Mandatory Training Mythbuster alongside his existing materials and asked Concordia to produce a draft Mandatory Training Policy. The result wasn’t a finished document ready for approval — but it gave him something much more valuable: a strong starting point.
“A lot of the bulk of it was done by AI to give us that working document just to play with and move forward and make sure we were on the right track.”
Working alongside a version created by a colleague, Wayne combined the outputs and then carefully reviewed the document line by line. The AI had provided the structure and framework, but the real value came from applying his own knowledge, experience and understanding of general practice.
“It would have taken a lot longer if it wasn’t for that. There’s nothing worse than starting with a blank page.”
Using AI as a Thinking Partner
One of the most important parts of Wayne’s process was validating the AI’s output against the source material.
He repeatedly cross-referenced the policy against the CQC Mythbuster, checking that what Concordia had produced genuinely reflected the guidance rather than simply generating generic training requirements.
The result was a policy that clearly explained:
- Why mandatory training matters.
- The regulatory context behind the requirements.
- The difference between CQC expectations and wider contractual obligations.
- Which staff groups genuinely need which training.
This was particularly important because Wayne discovered that many practices are requiring far more mandatory training than CQC actually expects.
Challenging Assumptions
When Wayne reviewed the Mythbuster guidance, he found that the list of genuinely mandatory training requirements from a CQC perspective was surprisingly short.
In many organisations, mandatory training lists have grown over time, often reaching 20–30 separate modules.
By using Concordia AI to organise the guidance and structure the policy, Wayne was able to work through each requirement systematically, identifying:
- What CQC expects.
- What NHS contractual requirements expect.
- What the practice itself feels is important for staff development and safety.
The outcome was a more focused and proportionate training framework.
Instead of asking every member of staff to complete every possible training module, the policy helps define who needs what and why.
Making Policies Real
What makes this work particularly powerful is that it demonstrates a different way of using AI.
Wayne wasn’t asking Concordia to replace his expertise.
He was using it to accelerate the process of turning complex guidance into a practical working document.
The policy is no longer simply a document stored on a shared drive. It has become a framework that helps the practice make informed decisions about training, compliance and workforce development.
In many ways, this is the real value of AI in general practice governance: taking information that already exists and helping practices transform it into something useful, relevant and actionable.
As Wayne’s experience shows, when AI is combined with professional judgement, policies stop being paperwork and start becoming tools that help teams work better.