A short answer…
Say’s Law says “supply creates its own demand”. In the long term Say's Law will apply. In the short term a surprise will mean some suppliers are producing something they should not be and it takes time to adapt so there can be temporary unemployment. When it is widespread, that is a recession.
Link to Say's Law
This is not a satisfying answer because Say’s Law will apply whether there is less automation as in the middle of the 1800s or more automation as in the middle of the 2100s. This suggests that for a long term trend like technology improvement where presumably you are interested in an answer that applies in an equilibrium, it is not productive to ask if supply and demand are mismatched.
In a highly automated world if a person works what we now consider to be part-time, they still have 1 job so jobs per person might not be the best measure for showing the effects of automation. This suggests we should consider not only the unemployment rate. I consider leisure and absence from the labour force.
As technology driven productivity increases, people can accept a mix of more income and more leisure. These are substitutable so we would expect both to increase in certain proportions, which is what occurred in the past. In the future both will increase in unknown proportions.
A longer answer…
A historical change under the circumstance of a technology driven increase in economic productivity is more years young people spent not working while enrolled in an “education” system that increases subsequent productivity but also seems to wastes peoples’ time. Productivity increases can make this possible if parents and taxpayers transfer an increasing amount of their output to young people.
Non-work years early in life
This graph of the percentage of the population with college attainment indirectly suggests that years spent in education has increased since 1940.
Link to educational attainment data
Leisure years late in life
Consider also the historical increase in the number of leisure years between initial retirement and the end of life. At the following link is information on the number of years spent in retirement. It shows that in the U.S. it increased from 11.3 or 15.0 (depending upon gender) in 1970 to 16.4 or 19.8 in 2018.
Link to years in retirement data
Leisure hours per week
In the following graph we see that leisure hours per week has been increasing (or equivalently work hours per week decreasing). This is a non-farm measure. Farm and ranch workers are only 1.3% of workers so a non-farm measure is probably still useful. It might be harder to measure farm hours.
Reference for the 1.3% figure
Lastly, I offer this graph to justify my earlier claim that income increased. More leisure (early in life, late in life, in the week) was part of a mix that included more real income.
The U6 measure of unemployment includes people who are jobless and discouraged from job seeking. The main measure of unemployment is U3 and it is defined as jobless and actively seeking a job. The people engaged in various forms of leisure or non-work do not get classified as U3 unemployed so automation does not have to lead to a long term increase in the main measure of unemployment. An increasing level of technology has been the trend for a long time, yet we know that immediately before the 2020 pandemic there was not an equilibrium condition of "mass unemployment" and so I would not expect it after the pandemic.