AI Readiness in Housing Associations

To set the stage for deeper discussion, attendees were invited to complete a short questionnaire, sharing their perspectives on the opportunities, priorities and challenges of AI adoption within their organisations.

The survey explored three key areas:

• Which AI use cases were seen as most relevant
• The biggest challenges in adopting AI
• The greatest potential benefits

It proved a useful primer for the conversation and what followed was a lively, thoughtful afternoon.

It started with Rob Gallagher, Chief Data Officer at Places for People, sharing how their incremental, use-case-led journey through data platform modernisation — delivered in partnership with The Dot Collective — had set them up not only to remove cost through operational efficiency and staff productivity, but also to give them the foundation from which to deploy their first GenAI workloads. Rob message was clear; “you cannot bolt AI onto bad data”.

Kate Stetsiuk, Head of AI at The Dot Collective, then picked up the thread, synthesising the group’s earlier survey responses into a broader view of where the sector stands today and what it will take to move forward; "Housing associations are sitting on a wealth of unstructured data. Generative AI gives us a way to unlock it, but the journey must start with leadership education and a deliberate, structured approach to use case generation."

As the afternoon unfolded, several strong themes emerged.

First, the danger of hype.
It’s easy, especially with cloud and software vendors enthusiasm to buy into grand promises. Yet unlocking AI’s potential, demands confronting complexity and being very deliberate with how you tackle data governance.

Key lesson: Data quality is key to success with AI.

Second, the growing relevance of federated data ownership models like Data Mesh.
There was broad agreement that embracing the complexity of the data estate and pushing data accountability closer to business domain expert is the future. To do this well though, organisations must invest in those domain experts' skilling up in data and AI literacy - that starts with the organisation’s leadership teams.

Key lesson: Federated data has lots of benefits, but business’ owning data without data literacy is a recipe for disaster.

Third, the struggle to demonstrate value from data initiatives.
Many organisations shared frustration that even successful data projects often failed to gain recognition internally, restricting future funding. The conversation highlighted the need for clearer cost attribution and usage tracking, data initiatives going live that no one notices are a sure sign you’re delivering misaligned value and a route to funding cuts.

Key lesson: Use FinOps thinking to attribute cost and be clear the benefit your delivering is measurable and one the business cares about!

Fourth, experimentation - fast but safe was a clear ambition.
Most Housing Associations in the room were at least piloting some form of GenAI in their organisations, from call centre automation to internal process improvements. Yet few had formal structures in place to move from experimentation to production while keeping the associated risks under control.

Key lesson: Comprehensive AI Governance is key. As a minimum it should cover ethics, safety, security and include a responsible way to innovate, collaborate and deploy to production.

We’re incredibly grateful to all the Housing Association that participated in our discussion. We feel like we learnt a lot and while we openly discussed varying levels of data maturity across the organisations, there was a shared sense of excitement about the future. There’s certainly a challenging journey ahead, but one that’s absolutely worth it because of the potential to improve tenant’s lives.

Sarah from Housing 21 captured the sentiment best:

"I came in curious, and left reassured. We know now where we are on the journey, where we could go, and what it will take to get there. It is a long road, but it is one worth committing to."

The Takeaway

There are no shortcuts to AI readiness.

The organisations that will lead are those who:

• Invest in strong, future-proofed data foundations
• Prioritise data and AI literacy from the leadership team down
• Build structured, safe pathways for GenAI experimentation
• Work with the business and focus on improving their results

At The Dot Collective, we believe success with AI is not about chasing the hype, but getting strong data foundations in place with solid, best practice data engineering.

We look forward to continuing the conversation.

Contact us at hello@thedotcollective.co.uk