The purpose of this paper is to establish the true extent of existing demand for social housing in Australia, and to model the potential future demand that could be created by shifts in the labour market as a result of automation and artificial intelligence (AI).

Measures of existing demand are calculated by estimating the number of households in Australia who meet current eligibility requirements in the state or territory in which they live. These calculations are based on household income data sourced from the 2016 census which has been indexed by the consumer price index (CPI). The findings demonstrate that current waiting lists are not an accurate record of the true level of social housing need, and that if every household which met the current eligibility requirements in their state or territory decided to apply, waiting lists across the country would increase by more than 300%.

The coming wave of automation and digital disruption is also likely to significantly add to social housing demand by eroding the wages of affected workers. Experts predict it will be low income workers who are most affected during the initial phase of this fourth industrial revolution. Structural dislocations in the economy often leave affected workers struggling to re-enter the workforce. As many as 20% remain out of work three years later. Those that do re-enter the workforce generally experience wage declines of between 10-20% compared to prior earnings.

Depending on the proportion of the low to moderate income workforce that is ultimately impacted by automation, we estimate there are currently between 21,387 to 44,378 low income households in Australia who are not currently eligible for social housing but would become eligible if they experienced a 10% decline in household income. If impacted households experienced a decline in household income equivalent to 20% of current household income, the number of extra households that would become eligible for social housing would be between 44,802 and 92,964.

These figures do not account for population growth which itself is expected to increase demand for various forms of housing assistance over the period in question.