Vaishnavi is an expert in Natural Language Processing (NLP). She currently leads the Generative AI-applied R&D team at Tiger Analytics. In her 12+ years of work experience, she has designed and developed NLP solutions for question answering, search summarisation, sentiment analysis, topic extraction, and text classification. Her work in Generative AI includes conversational bots, custom LLMs, RAGs, autonomous agents, and more, with several award-winning real-world implementations. This is her AI journey. 

How important do you think skilling and upskilling are in a country like India?   

In today’s dynamic world, skilling and upskilling are crucial, especially for India. A skilled workforce drives economic growth through increased productivity and innovation while fostering expansion across industries and sectors. Skilling and upskilling are also crucial to empowering India’s youth and equipping them with the tools for employability in the domestic and global job market. Regular upskilling is vital to staying relevant as technology reinvents industries. 

Beyond economic growth, skilling is a foundation for social development as well. It empowers communities and curbs poverty through access to education and skill-based training. Initiatives like the Ministry of Skill Development and Entrepreneurship and Start-up India demonstrate successful efforts in this area. 

To further solidify India’s position as a global leader, especially in the technology ecosystem, a highly skilled workforce with specialised skill sets in AI, data science, and machine learning is paramount. Skilling programs must equip individuals with these in-demand skill sets. 

For India’s continued growth, collaboration is key. Policymakers must prioritise skill development, while businesses should invest in workforce training. This combined effort will unlock India’s full potential and reap the benefits of its demographic dividend. 

Can you tell us about your AI journey? 

My formal education in mathematics and engineering paved the way for my journey in the dynamic technology field. I then graduated as a civil engineer from BITS Pilani, which helped me realise my love for technology and piqued my interest in its evolution.  

As I delved deeper into professional realities, I found myself drawn to machine learning and its various subfields, such as deep learning, reinforcement learning, and natural language processing (NLP). This was the beginning of my AI journey. 

Throughout my career, I have been fortunate to explore opportunities to work on various AI projects. This experience has helped me appreciate the complexities and various challenges in AI. Since then, I haven’t stopped!  

What is your area of expertise in AI, and what made you choose it? 

My affinity towards Natural Language Processing (NLP) has driven me to build knowledge in the field. Today, as one of the experts in NLP, I am leading the Generative AI-applied R&D team at Tiger Analytics. Over 12+ years of experience, I have designed and developed NLP solutions across domains such as question answering, search summarisation, sentiment analysis, topic extraction, and text classification. My work in Generative AI involves creating conversational bots, custom LLMs, RAGs, autonomous agents, and more, with several award-winning real-world implementations. 

In my previous role, I worked as an NLP Scientist at Elsevier, where I focused on intelligently organising global scientific research in an automated manner. My responsibilities included extracting patterns, trends, and signals by mining hundreds of thousands of research papers. 

I’ve always been intrigued by the power of language and communication, and NLP offered a way to merge that interest with my technical skills. Potential applications of NLP across various industries captivated me, mainly healthcare and financial to customer service use cases.  

Describe some challenges you have faced in reaching where you are now.   

Looking back, I remember facing some challenging tests. When I started working on civil engineering projects, I was quick to realise my inclination towards technology, specifically AI. The beginning itself was challenging as I had to unlearn first and equip myself with the relevant skills while dealing with uncertainty. It took a lot of determination and a willingness to adapt to make it work. 

Like many women, I struggled to ‘fit in’ and overcome self-doubt. Overcoming these feelings has been a journey itself. I still work on it every day, trying to believe in myself and focus on growing. 

Balancing work and life has been tough, too. With more responsibilities at work and at home, finding the right balance is an ongoing challenge. But I’m learning to manage my time better and take care of myself along the way. 

However, I have also realised that challenges will arise irrespective of your gender, background, education, etc. The important thing is to be adaptive and open to learning. 

In what direction should companies in the AI sphere move to ensure more female participation and leadership?   

In the past decade, there has been an increased focus on DE&I awareness, policies, and initiatives across sectors and companies. Organisations must create inclusive cultures, acknowledge and avoid unconscious biases, and plan interventions to hire, train, elevate, and support women leaders, which is paramount. Some initiatives we are leading at Tiger Analytics focus on mentorship programs, flexible work policies, active women-led forums for learning and upskilling, representation in leadership roles, and targeted hiring campaigns for women folks - Women in Data Science, She Roars (across streams like Consulting, Data Engineering, and other enabling functions).  

These steps towards diversity and equity will not only ensure more participation from women but will also instil confidence in the next generation of women seeking opportunities in the field of AI. 

In a country like India, where societal constraints bind women, how do you think that they should break the stereotypes? 

Manal al-Sharif, as we all know, is an ordinary woman who unexpectedly led a courageous movement for women’s right to drive in Saudi Arabia. When I think about women breaking barriers, I find inspiration to challenge societal stereotypes. 

When I consider the examples I set for my daughter, who learns from my actions, I become more mindful of being a positive role model. Societal constraints and stereotypes may take generations to change, but I believe everyone is responsible for contributing to this change for future generations. 

This belief motivates me to be the kind of person I hope my daughters will become in the future. 

What are your words of wisdom to young girls who wish to build careers in AI?  

I would like to share my journey with all the young girls out there, hoping it resonates with you and helps you realise your ambitions. Early in my career, I embraced a growth mindset and prioritised continuous learning. These traits have been instrumental in my progress. I have also found perseverance and discipline to be essential qualities that have accompanied me. So, I encourage you to cultivate these traits, as they can make a significant impact on your journey toward success in life and in your career.