AI Adoption in Social Housing: Insights from the Housing Tech Conference

Artificial Intelligence (AI) is rapidly transforming industries, and social housing is no exception. At the recent Housing Technology Conference, Voicescape hosted a fireside chat with Adrian Moore, IT Director at BPHA, who is a leading figure in the social housing technology space. The discussion, led by Voicescape’s Sales Director Peter Hudson, examined the role of AI in arrears caseload management and explored Adrian’s AI Adoption Hierarchy, a framework guiding AI adoption in the sector.

The Evolution of AI in Social Housing

BPHA, a forward-thinking housing provider, has embraced AI as a key enabler for improving operational efficiencies and tenant engagement. Adrian shared insights into their journey, explaining how BPHA moved towards an integrated data and service model, underpinned by Microsoft Dynamics CRM and an in-house integration framework. This approach ensures a single, comprehensive view of properties, tenants, and service needs, making AI adoption more seamless.

The AI Adoption Hierarchy

During the talk, Adrian introduced his AI Adoption Hierarchy—a model outlining the different levels of AI implementation. The pyramidal model was built live on-screen as he explained its principles:

1. Policy & Security Guardrails – The foundation of any AI strategy must be robust policies and governance structures to protect the organisation and its tenants. At BPHA, strict policies ensure that no personal or sensitive data is published into public AI platforms and that AI is used to inform rather than dictate service delivery decisions.
2. Public AI Tools – The next layer consists of accessible AI tools like ChatGPT, Gemini, and DeepBrain AI. These tools offer low-cost, high-accessibility solutions for organisations looking to experiment with AI. BPHA has encouraged innovation by allowing employees to explore AI’s capabilities in tasks like document drafting, policy refinement, and meeting summarisation.
3. Vendor Integration – As organisations become more confident in AI, they move to vendor-integrated AI solutions that enhance core business functions. Voicescape’s Caseload Manager is a prime example, using AI to prioritise arrears cases for income officers by analysing tenant behaviour and payment patterns. This reduces unnecessary interventions and allows teams to focus on high-need cases, improving efficiency and debt recovery.
4. Custom Integration – At the highest level, AI is fully integrated into an organisation's infrastructure, providing tailored solutions to specific operational challenges. BPHA has developed bespoke AI-driven workflows, such as predictive maintenance scheduling and automated compliance monitoring, demonstrating the immense value of AI when deeply embedded within business processes.

Real-World Impact of AI in Case Management

The integration of AI in income and case management has yielded significant benefits. Housing providers using Voicescape’s Caseload Manager, have reported:

• A up to 71% reduction in manual case reviews, freeing up staff for more meaningful engagement.
• A significant drop in false positive cases, ensuring officers spend time on tenants who truly need support.
• Enhanced collection rates, thanks to early and data-driven interventions.

Addressing AI Challenges

While AI presents numerous opportunities, it also comes with challenges. Adrian highlighted key lessons learned:

• Skill Development: AI shifts work from drafting to editing. Staff must be upskilled to critically evaluate AI-generated content.
• Vendor Collaboration: Choosing the right AI partners is crucial. Vendors should offer open, flexible technologies that integrate well with an organisation’s ecosystem.
• Human Oversight: AI should assist but not replace human decision-making. BPHA ensures AI recommendations are reviewed by experts before implementation.

The Future of AI in Social Housing

Looking ahead, AI’s role in social housing will expand beyond internal efficiencies to directly enhancing tenant experiences. Potential applications include:

• AI-powered chatbots for tenant queries and self-service solutions.
• Image recognition AI to assess property damage from tenant-submitted photos.
• Predictive analytics to pre-emptively address tenant needs before they escalate into issues.

Key Takeaways

1. Start Small & Experiment – Encourage employees to explore AI tools in non-critical functions before scaling up.
2. Implement Clear Governance – Establish policies that balance innovation with ethical and security considerations.
3. Leverage AI for Decision Support – AI should inform, not replace, human judgement in service delivery.
4. Foster an AI Culture – Cross-functional innovation groups can drive AI adoption and unlock new efficiencies.

Harnessing AI’s Potential

The Housing Technology Conference fireside chat with Adrian Moore provided invaluable insights into AI’s practical applications in social housing. With a structured approach like the AI Adoption Hierarchy, organisations can navigate the complexities of AI implementation and unlock its full potential to enhance tenant engagement and operational efficiency.

To learn more about Voicescape’s AI-driven solutions for social housing, visit our website www.voicescape.com, or connect with us at industry events. AI is here to stay—how will your organisation leverage it?