This began with a problem
that was difficult to solve alone.

During the work of implementing AI solutions, the practical questions kept returning.

Which application should we choose? Would it fit the way we worked? What would need to change? Who would be responsible when something did not work as expected?

They were not abstract questions. Each one could influence whether an application would ever become part of everyday work.

We had frameworks, checklists and published articles. They gave us a useful place to begin.

But implementation was rarely as tidy as it appeared on paper.

A workflow might not fit. A use case described in an article might not match our setting. A new difficulty might appear only after the application met real people, responsibilities and routines.

Someone would ask, “What should we do here?” Often, that was the part we could not find in the guidance.

Vendor guidance and introductions often led to people who were successfully using an application. Those conversations were valuable, and it was understandable that these were the experiences being shared.

But we also wanted to hear the other stories.

Who had struggled? Who had changed their workflow? Who had stopped using an application - and why?

Sometimes an experience that did not go well could teach us more than another success story.

Finding honest, practical experience meant searching across professional networks, published work and personal contacts.

There was plenty of discussion about what AI could do.

What was much harder to find was someone saying, “We tried it this way. This is what happened. This is what we had to change.”

The right people were probably out there, but finding them took time. Sometimes we became lost in the search before reaching the conversation we needed.

As the same difficulty kept returning, a different question gradually appeared.

I began to wonder whether what was missing was not another framework, article or prediction about the future.

Perhaps there needed to be an open place where people could ask practical questions, share difficult experiences and find others doing similar work.

Not somewhere that opened only during a meeting or conference. A living place where the conversation could continue.

By then, the need for a shared community had become increasingly clear to me.

I discussed it first with an IT professional and later, in a separate conversation, with a technical physician.

Each recognised the same gap from a different perspective. Those conversations tested the idea, added perspectives I could not bring alone and helped turn it into something we could begin building together.

The first conversations helped create a beginning. They eventually became AI in Healthcare Community.

Creating a place, however, is only the beginning. It becomes a community when people enter it, ask questions, share what they have learned and help somebody else move forward.

Healthcare AI involves clinicians, researchers, IT professionals, implementation teams, healthcare leaders, policymakers, legal professionals and people from industry. No single profession or organisation can see the whole picture.

Professional societies already do important work within their fields. This community is intended to sit alongside them - a shared place where practical conversations can continue across professional boundaries.

Perhaps your experience is different from ours. But if you have also struggled to find the right person, an honest answer or the practical experience you needed, then perhaps this is a conversation you can help continue.