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# Women in AI - Nalini Garg

Nalini Garg warns that relying on generative AI outsources your critical thinking. Discover how to conquer the AI leadership gap, demand fair pay, and outsmart automated hiring.

- **Speakers:** Nalini Garg
- **Event:** Coffee With Developers
- **Published:** August 30, 2026
- **Duration:** 42:19
- **URL:** https://www.wearedevelopers.com/videos/2158-women-in-ai-nalini-garg

## Summary

The artificial intelligence industry presents a massive opportunity for diverse talent, yet a significant drop-off occurs as women progress toward leadership roles. Nalini Garg, AVP at Deloitte and leader within the global non-profit Women in AI, explores the systemic and psychological barriers causing this leadership gap, such as the stigmatization of career breaks, unequal maternity leave policies, and pervasive imposter syndrome. Despite early-career diversity in data science, returning to the corporate world often forces women into accepting lower salaries due to a lack of negotiation or fear of rejection. Garg emphasizes the importance of utilizing salary transparency tools and confidently demanding fair compensation to combat deeply ingrained hiring biases.

As the hiring landscape shifts toward AI-driven resume screening, standing out requires a renewed focus on the human element. Rather than submitting lengthy resumes, candidates should consolidate their experience to highlight concrete problem-solving impacts and directly engage hiring managers on platforms like LinkedIn. Furthermore, job seekers must not disqualify themselves when they fail to meet every bullet point on a "unicorn" job description. Internally, employees are encouraged to actively request employer-funded training and clear career progression pathways, demonstrating a commitment to long-term growth rather than just treating a role as a temporary stop.

Beyond career navigation, the conversation highlights a critical divergence in how AI products are being built. While many tech-centric solutions lack user empathy, a rising wave of female founders is leveraging machine learning to address relatable, human-centric challenges like mental well-being and productivity. Garg strongly cautions against the over-reliance on agentic coding and generative models like ChatGPT and Claude. She advises professionals to document their own ideas first, warning that "while you're trying to gain productivity, you're also outsourcing your thinking process to these models." Ultimately, maintaining emotional intelligence and critical thinking remains the ultimate competitive advantage in an increasingly automated world.

**Keywords:** women in AI, tech leadership diversity, AI resume screening, tech salary negotiation, imposter syndrome in tech, career break reintegration, data governance strategy, ChatGPT productivity challenges, human-centric AI development, tech hiring bias, open source AI models, tech community networking, employer funded training, generative AI critical thinking, agentic coding challenges

## Chapters

1. **Mission and vision behind the Women in AI organization** (00:31) — Creating a global community to support female voices and leadership in artificial intelligence.
1. **Addressing diversity drop-offs and career breaks in technical leadership** (02:44) — Returning to the corporate world after family responsibilities requires overcoming imposter syndrome and systemic barriers.
1. **Navigating market biases and negotiating fair technical salaries** (05:09) — Combating historical liabilities around family leave requires leveraging salary transparency tools and direct negotiation strategies.
1. **Combating traditional gender roles with continuous community advocacy** (12:05) — Reversing the regression toward traditional gender expectations involves amplifying female voices and creating supportive networks.
1. **Utilizing accessible education and hackathons for career entry** (14:29) — Free vendor courses and local hackathons provide practical experience and networking without financial barriers.
1. **Adapting resumes for AI hiring agents and applicant tracking** (16:43) — Consolidating experience into a concise format helps bypass automated screening tools while personal outreach secures interviews.
1. **Bypassing imposter syndrome during job applications and networking** (19:41) — Introverted candidates can overcome strict job descriptions by focusing on relatable narratives rather than checking every requirement box.
1. **Requesting internal training and establishing clear career ladders** (24:15) — Asking employers to fund specialized tool training demonstrates a commitment to long-term career growth and project success.
1. **Designing empathetic artificial intelligence solutions for daily life** (27:53) — Non-technical founders often focus on automating practical chores and improving mental well-being rather than purely technical challenges.
1. **Preserving open source ideals against closed corporate technology** (32:33) — Maintaining open source technology is essential to ensure artificial intelligence serves humanity rather than just corporate profit.
1. **Balancing generative productivity tools with human critical thinking** (34:53) — Relying entirely on generative models for daily tasks risks outsourcing the unique human perspectives needed for complex problem-solving.
1. **Overcoming technical overwhelm through continuous daily learning habits** (37:27) — Dedicating small amounts of time daily to learning prevents burnout and keeps skills relevant in a rapidly evolving market.
1. **Fostering hope through professional mentorship and allyship networks** (39:02) — Engaging with supportive colleagues and active communities counteracts negative experiences and opens doors to new opportunities.

## Related Moments

- [Setting the context for female leadership in artificial intelligence](https://www.wearedevelopers.com/videos/1707-behind-the-code-how-women-are-powering-the-future-of-ai) (from "Behind the Code: How Women Are Powering the Future of AI")
- [Balancing AI regulation with technological innovation in human resources](https://www.wearedevelopers.com/videos/1356-from-learning-to-leading-why-hr-needs-a-chatgpt-license) (from "From Learning to Leading: Why HR Needs a ChatGPT License")
- [Developing critical leadership skills for AI integration](https://www.wearedevelopers.com/videos/1818-what-happens-to-leadership-when-ai-becomes-a-teammate) (from "What Happens to Leadership When AI Becomes a Teammate?")
- [Addressing the emotional layers of workplace AI transformation](https://www.wearedevelopers.com/videos/1996-partnering-with-ai-building-future-ready-teams) (from "Partnering with AI: Building Future-Ready Teams")
- [Addressing bias and gender representation in training data](https://www.wearedevelopers.com/videos/909-edit-your-future-queerverse-radical-ai) (from "Edit Your Future: Queerverse Radical AI")
- [Addressing psychological safety and ethical risks of AI adoption](https://www.wearedevelopers.com/videos/1950-the-scrum-master-as-an-orchestrator-guiding-human-ai-collaboration-in-modern-teams) (from "The Scrum Master as an Orchestrator: Guiding Human–AI Collaboration in Modern Teams")

## Related Articles

- [Women in Tech: Navigating Career Transitions and Breaking Barriers](https://www.wearedevelopers.com/magazine/491-women-in-tech-navigating-career-transitions-and-breaking-barriers)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)

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