What a time to be AIive!
By Shakirah Akinwale
Continuing from the imperative of good data management as the foundation for AI’s effectiveness, we must also recognise the potential for AI to revolutionise the housing sector, which, like many industries, is on the cusp of a digital transformation. The integration of AI in housing is not just about predicting market trends or automating tasks; it’s about creating value for consumers and addressing public interest concerns such as affordability, accessibility, and sustainability. “AI-powered solutions are gradually transforming the real estate industry by simplifying and expediting complex processes, ultimately boosting work efficiency across various roles, including sellers, brokers, asset managers, and investors.” [1]
For consumers, AI can personalise the home-buying journey, making it more efficient and less stressful. “Efforts to reduce costs, increase efficiencies and incorporate more innovation, technology and data in the valuation process are expanding the use of alternative valuation methods.” [2] AI-powered platforms can analyse individual preferences, financial profiles, and market data to provide tailored property recommendations and realistic financing options. This level of customisation can greatly enhance the customer experience, making it easier for buyers to find homes that meet their needs and budgets [3]. These solutions eliminate human bias, and erroneous conclusions based on other interests’ valuers may have, reducing the risks to buyers and the market [4].
AI can be instrumental in the public interest by contributing to the development of smart cities. Through the analysis of vast amounts of urban data, AI can inform policy decisions related to planning, housing density, public transportation, and community services [5]. This can lead to more resilient and inclusive urban environments, where housing is not just a commodity but a right that’s integrated into the fabric of well-planned cities. AI could have a significant impact in the analysis and prediction of housing affordability trends. By drawing on diverse data sets, including income levels, housing prices, and economic indicators, AI models could provide early warnings of affordability crises, allowing for proactive measures by policymakers and stakeholders. This could lead to more effective and targeted interventions, such as the development of affordable housing projects in areas where they are most needed. AI can optimise operations, reduce costs, and improve decision-making while enhancing safety and quality for occupants of diverse needs. By employing predictive analytics, property developers and managers can anticipate market shifts, understand demographic changes, and make informed investment decisions. AI can also streamline construction processes using robotics and 3D printing, leading to faster and potentially more affordable housing development, especially with modern methods of construction (MMC) [6], as well as improving the sustainability of housing by optimising the design and materials used in construction. By analysing environmental data and simulating various scenarios, AI can help architects and engineers create buildings that are more energy-efficient, have a lower carbon footprint, and are better adapted to climate change. This will lead to long-term cost savings for homeowners and a reduced environmental impact.
An innovative example of AI’s application in Social Housing is Manningham Housing Association (MHA) in Bradford and Keighley. Despite its size, managing 1,400 homes, this forward-thinking housing provider has made significant strides and impact by integrating AI into their operations [7]. The association is leveraging AI to enhance both tenants’ and staff experiences while maintaining cost-effectiveness. A particular challenge housing providers face, whether large or small, is delivering high-quality support to tenants during non-business hours. Traditional methods are labour intensive and lacked the speed, efficiency and personalisation tenants require and, in many cases, are entitled to. MHA have deployed chatbots and AI personal assistants to revolutionise tenant support and internal operations. Tenants enjoy 24/7 access to information on a broad spectrum of topics, enhancing their experience, awareness, satisfaction and sense of ownership. “Tenants and customers can get the information and support they need quickly and easily, improving their overall experience and satisfaction by using their Chatbot and customer portal, MyMHA.” Staff are using chatbots, and AI assistants to support case work and report-writing, and to eliminate the risks of maladministration.
In the realm of property management, AI can enhance the efficiency of maintenance and repairs, predict equipment failures, and automate routine tasks, allowing property managers to focus on improving tenant relations and building community. AI plays a pivotal role in optimising communication, reducing call volumes, and facilitating self-service options for residents who prefer or are capable of managing issues independently. This strategic application of AI ultimately elevates the living experience for all residents. Accessibility is another area where AI can make a significant difference. For individuals with disabilities, AI-driven smart home technologies can provide increased independence and quality of life. Voice-activated systems, automated mobility aids, and other adaptive technologies can be integrated into homes to meet the specific needs of residents with physical or cognitive impairments [8]. AI can facilitate energy management in homes and buildings, analysing usage patterns to optimise heating, cooling, and lighting, thus reducing energy consumption and costs for tenants and homeowners.
However, to harness AI’s full potential in improving housing, the industry must overcome the same data management challenges faced by other sectors. Good data management is the foundation for AI’s effectiveness, and as such data quality, governance, and security are paramount, especially when dealing with sensitive personal information. The housing sector must incorporate data management standards, like the UK Housing Data Standards and recommendations from the Real Estate Data Foundation, that ensure the accuracy, privacy, and ethical use of data [9, 10]. Only then can AI algorithms be trusted to make decisions, and recommendation systems [10] that have real-world consequences for individuals and communities. Trust in these systems is enhanced by engaging consumers and the public in strategic and practical discussions, enriching technical solutions with diverse insights.
As we look forward, the synergy between AI and housing presents a unique opportunity to not only enhance the efficiency and profitability of the industry but also to address some of society’s most pressing housing challenges. The potential benefits are manifold, but they require a thoughtful approach to implementation, one that considers the social implications as well as the technological advancements [11]. There is a risk of exacerbating existing inequalities if AI tools are only accessible to those who can afford them, potentially leaving low-income individuals and communities behind. The use of AI in decision-making processes, such as loan approvals or tenant screening, must be carefully monitored to prevent biases and discrimination.
To address these concerns, there must be a concerted effort to develop inclusive AI systems that are transparent, explainable, and accountable. Stakeholders should collaborate to establish ethical guidelines and regulatory frameworks that protect consumers and ensure that the benefits of AI are equitably distributed. Stakeholders should increase their effort in raising awareness about the opportunities with which end users and consumers may get involved. Organisations exist like the Consumer and Public Interest Network (CPIN) – a part of the BSI (British Standards Institute) – where consumer representatives, like me, do just that. We serve as bridges for the wider community of stakeholders and public interest, being a voice for those who cannot speak, and researching to implement better strategies to reach and engage people. AI is one of those areas, and more needs to be done to remove the technical and complex barriers that exclude people or mislead people so they self-exclude themselves.
As AI becomes more integrated into the housing sector, the workforce will need to adapt. There will be a growing demand for professionals who can bridge the gap between technology and housing, such as data scientists specialising in real estate analytics, AI ethicists, and smart city planners. This calls for investments in education and training programmes that can equip the current and future workforce with the necessary skills. The housing sector holds potential to engage younger generations, particularly by clarifying its possibilities. Aligning educational and social mobility efforts with broader goals to bolster the UK economy is crucial. Attracting and retaining a skilled workforce is key for their effective training and integration into the sector.
While the housing sector stands to gain immensely from the advancements in AI, realising this potential hinges on addressing the foundational issues of data management and ensuring that AI applications are developed and deployed in a responsible and inclusive manner. By doing so, we can move towards a future where AI not only drives economic growth in the housing industry but also contributes to the creation of equitable, sustainable, and liveable communities for all.
References
[1] “AI IN REAL ESTATE: IMPACTING THE DYNAMICS OF THE MODERN PROPERTY MARKET”, Akash Takyar, CEO LeewayHerts, https://www.leewayhertz.com/ai-in-real-estate/
[2] “Rethinking Real Estate Valuations and Alternatives to Traditional Appraisals”, 2018 https://www.nar.realtor/newsroom/rethinking-real-estate-valuations-and-alternatives-to-traditional-appraisals
[3] Jafary, P., Shojaei, D., Rajabifard, A. and Ngo, T. (2022), “BIM and real estate valuation: challenges, potentials and lessons for future directions”, Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-07-2022-0642
[4] 7 Things That Make a House Hard to Sell, 2022, Meaghan Hunt, https://www.homelight.com/blog/what-makes-a-house-hard-to-sell/
[5] AI in Planning White Paper | American Planning Association, 2022. By Clinton Andrews, AICP, Keith Cooke, Alexsandra Gomez, Petra Hurtado, PhD, Thomas Sanchez, AICP, Sagar Shah, PhD, AICP, Norman Wright, AICP, https://www.planning.org/publications/document/9255930/
[6] How is AI Changing Real Estate?. June 07, 2023, Stanley Bawalan. https://www.setschedule.com/setvalue/blog/reset/how-is-ai-changing-real-estate
[7] Manningham Housing Association, Carolina Padovezi de Oliveira, Corporate Project Manager, March 1 2023 https://manninghamhousing.co.uk/taking-the-lead-in-ai/
[8] Success Story: Elevating Tenant Satisfaction at Monmouthshire Housing through Voicescape. https://www.voicescape.com/case-studies/elevating-tenant-satisfaction-at-monmouthshire-housing
[9] UK Housing Data Standards, HACT, https://hact.org.uk/tools-and-services/uk-housing-data-standards/
[10] Real Estate Data Foundation, https://www.theredfoundation.org/[10] Gharahighehi A, Pliakos K, Vens C. Recommender Systems in the Real Estate Market—A Survey. Applied Sciences. 2021; 11(16):7502. https://doi.org/10.3390/app11167502
[11] Smart Homes: Impact of Artificial Intelligence in Connected Home. Apr 1, 2021. https://www.futurebridge.com/blog/smart-homes-impact-of-artificial-intelligence-in-connected-home/
