GEN AI: The Diversity Game Changer We Can’t Ignore

The report provides insights and recommendations to advance women's roles in GenAI. To foster a diverse and inclusive AI future, organizations should implement robust mentorship programs, support flexible work models, and clearly define GenAI career pathways. Additionally, organizations should reassess leadership teams working on GenAI to ensure diverse voices and varying ethical perspectives. By promoting continuous learning, companies can ensure women thrive in a GenAI-driven future, leading to more equitable workplaces and, critically, an unbiased and effective development of this disruptive technology.

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Key Findings

The global AI market is expected to reach $320-380 billion by 2027, growing at a CAGR of 25-35%, with GenAI poised to dominate 33% of this landscape
Female representation in tech dropped from 43% at entry levels to just 4-8% at executive levels, well below the global average of 14% in 2023
Male professionals in AI/GenAI are approximately 46% higher than female professionals, in India

Around 65% of both women and men in India believe that GenAI will act as an equalizer for women’s inclusion in tech.
GenAI could help bridge the gender gap by creating new opportunities, enhancing accessibility, and reducing biases that have traditionally hindered women's progress in tech.

Overall adoption of GenAI across Indian professionals is high with mid and junior level women leading in GenAI adoption
Senior women are close with 79%, however, they trail senior men in GenAI adoption rates, unlike their global counterparts
42% of women rate their professional ambition as very high which highlights that career ambition and extra effort are not roadblocks
GenAI adoption in India is driven by efficiency and innovation - women acknowledge the positive impact of GenAI on their career however, they lack readiness to use these tools
Limited knowledge, lack of trust, restricted access and fear of competence scrutiny are the perceived barriers in accelerating adoption

Reassess leadership teams working on GenAI to ensure diverse voices and varying ethical perspectives
Demystify GenAI career pathways, encourage participation, bridge the gap through mentorship initiatives
Advocate flexible work models to enhance learning and experimentation, prioritize responsible and ethical AI training
Build a strong community of practice in GenAI, foster an inclusive culture and measure talent pipeline diligently

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