21 Oct 2020 19:39 IST

More prospects for women in AI and analytics than five years ago: Survey

The increase in opportunities is attributed to more women in the workforce and lesser bias in hiring policies

In a survey conducted by the EdTech company Great Learning on the participation of women in the data science domain, specifically AI and analytics. The survey underlines the opportunities that exist for women in these sectors, factors that influence these opportunities, and focus areas to increase the participation of women in the data science sector. It also offers insights into the current representation of women in data science — demographics that offer the most opportunities, distribution across industry sectors, and the paths of entry for women into the domain.

The survey recorded the responses of close to 2,000 women from the data science industry. This was complemented by direct discussions with women leaders from the AI and analytics domain to gauge their perspective on the broader participation of women in AI.

Influential factors

According to the survey, 54 per cent of the women believe they have greater opportunities in AI and analytics now versus five years ago. The top five factors cited for this increase in opportunity include positive workplace policies, greater participation of women in the hiring process, favourable recruitment policies, lesser bias towards women, and the presence of more role-models for women than before.

The workforce policies that have had a positive impact on women’s participation in the sector include training or logistics support for such roles, flexible working hours, availability of work from home, and more maternity leaves. Also, the fact that more women pursuing analytics and data science programmes has had an impact.

Companies are also doing their bit by reaching out and short-listing more women candidates than before. Then, the fact that more women have risen to significant roles not just in the AI and data science domain but also across the broader IT and Technology domains has had an impact. Senior women data scientists and CIOs across industries and organisations are now serving as role models to numerous women seeking a career in AI and Analytics.

What will encourage more women to join?

As per the survey, 27 per cent of the respondents believe that equal growth and pay for the same level of experience and education will inspire more women to apply. The lack of equal growth and pay for women in AI continues to be a roadblock, discouraging many qualified and experienced women from entering this domain.

Moreover, 24 per cent of women believe that if they have a greater awareness of the roles and the support that organisations now provide in terms of work-life policies, training, and support, it will be a huge motivator to enter this field. Nearly 17 per cent think that the right mentorship and support system right from school to firms will encourage more women to take up AI and analytics roles.

And 16 per cent believe that greater access to analytics education and seeing more women in leadership roles will catalyse more women to join the industry.

Hari Krishnan Nair, Co-founder, Great Learning said, “We have been buoyed by the growing interest among women towards learning data science. Increased participation of women is imperative if India has to become the hub of data science in the world. What is heartening to see is the improved workplace and recruitment policies by corporates that are paving the way for the entry of more women in the sector.”

Bangalore offers the most opportunities

Bengaluru has beaten all other Indian cities hands down when it comes to offering most opportunities to women in the data science space with 31 per cent of respondents selecting it as the city with most opportunities. It is followed by Delhi (NCR) and Mumbai which are favoured by 10 per cent of the respondents, while Hyderabad and Pune are preferred by 9 per cent of the respondents. The remaining cities have single-digit preferences of 6 per cent or below.

The large gap between Bengaluru and the rest of the cities is a result of the city’s ability to attract all kinds of organisations — technology companies, start-ups, engineering organisations, consulting firms, and IT firms, all of which deal with large amounts of data. Bengaluru has emerged as the favoured destination for opportunities in AI, deep learning, NLP, and analytics. Moreover, the enabling ecosystem in the city such as educational institutes, mentoring, and housing, is more conducive for women looking for a career in data science compared to other cities.

Maximum representation comes from IT sector

As per the survey, the maximum women representation in the data science space comes from the broad IT / ITES sector, represented by 36 per cent of the participants. This is followed by the technology sector, both at 16 per cent. Pharma and healthcare, an emerging industry in the broad data science domain are represented by 12 per cent of the participants.

The broad automobile / industrial / infra sector is represented by 9 per cent of the participants. The remaining sectors including BFSI, e-commerce, FMCG, consumer electronics, travel and hospitality, and digital media have a small yet significant representation in the survey. So, while a little over half of the respondents — 52 per cent — are from the broad IT and technology segments, the remaining 48 per cent of the respondents represent diverse industries, signifying the emergence of data science as a domain spanning a host of industries and sectors.

Entry path for women in AI and analytics

The respondents were asked about how they started their careers in the AI and analytics domain and 31 per cent, the highest proportion, had cross-trained from a non-technology function and 26 per cent had upskilled from a related function within IT. This signifies that the majority of women who have entered the sector have managed to do it indirectly, highlighting the opportunity available for women across sectors who wish to change their career path and build a career in data science.