Women may suffer the most from AI technology – in the short term

An estimated 70% of workers whose jobs are at risk of being replaced by automation are female, however AI could prove a positive change for women in the long term


According to a study conducted by the Institute for Women's Policy Research (IWPR), up to 70% of workers at risk of being replaced by automation are female. AI presents a different change to how employers are likely to view the workforce and will impact workers that deal in jobs that can be automated. The BBC estimates that as many as 800 million jobs are likely to be "taken" by robot automation by 2030. From what we see in terms of the study from the IWPR, this could mean a lot of women ending up replaced by robots because of the nature of their jobs.

A disproportionate balance

Among the jobs most susceptible to AI automation, according to City Lab, are those in routine data work, such as administrative and secretarial tasks – fields where women make up 58% of the workers that are at risk, according to CityLab. This comes from a combination of the enforcement of gender roles that encourage women into these kinds of jobs and a lack of positive reinforcement in other areas of work. In other fields where hands-on work is not as easily automated, such as in the fields of engineering and technology, men still dominate the field. The development of AI comes from this area of research so there is a good likelihood that people who work within this field would not set about making themselves redundant.

Retraining to deal with changes in the workplace

The World Bank notes that gender needs to be a factor in the determination and drafting of economic policy and in this case, it is of the utmost importance. While there are a lot of jobs that are at risk because of the development of AI automation, there are also likely to be a lot more employable positions opening up in other areas of the field of AI. Forbes makes mention of 58 million new jobs being created by 2022 because of AI, but this number reveals a massive difference between the number of people who are likely to be made redundant and the number of new jobs that will be available for suitably qualified individuals. For a worker that is dependent on a position that can be easily automated, this could spell disaster. However, being retrenched because of automation does not mean the end of the line. In some cases, it could mean a push for a new beginning.

While in the past it could be a safe bet that a routine data job would remain throughout one's lifetime, the age of AI and digital innovation has made that assumption erroneous. McKinsey says that two-thirds of a sample of 300 executives states that addressing the skill gaps that exist between their workers' current designations and jobs that cater to automation/digitization as among their top ten priorities. The result is that workers have the option of waiting for their employers to reskill them or taking the initiative and reskilling themselves.

Closing the gender employment gaps

While the figures suggest women are likely to be affected far more negatively by AI than men, the Financial Times suggests that some fields where women form the majority of workers, such as those where high emotional intelligence is required, may become more valued – and thus more valuable.

Still, there remains the issue of the gender inequality among AI professionals. According to the World Economic Forum, only 22% of professionals working in AI development are women, which highlights a concern that AI might reinforce a digital society that is built for men by men. How far women are negatively affected by AI may depend on how strong an attempt is made to reduce this imbalance.

Another McKinsey study indicates a positive correlation between gender diversity in workforces and financial performance, which may increase the demand for women in AI development. While in the short term, women might suffer from AI technology, it has the potential to level the playing field within the industry and without in the long run.

How big data can achieve its potential in healthcare small

Read next:

How big data can achieve its potential in healthcare