Accelerating Careers

Nancy Wang, founder and board chair of Advancing Women in Tech (AWIT), provided a masterclass at the Nexus Start-up Hub at the American Center New Delhi. (Photograph by Rakesh Malhotra)

Nancy Wang is the founder and board chair of Advancing Women in Tech (AWIT), a global nonprofit organization that has informed and educated thousands of Coursera learners worldwide on how to get their first, or next, tech leadership role. Wang has also worked as director of product and engineering and general manager at Amazon Web Services.

Wang is excited to advance more women into technical roles through AWIT, which provides mentoring to support women in product and engineering roles at B2B companies. She has trained 40,000 women through AWIT’s product management and cloud computing courses on Coursera. Wang spent two weeks in India, speaking with audiences in Chennai, Bengaluru, Jaipur, New Delhi and Hyderabad on intellectual property (IP)-driven innovation and women’s entrepreneurship. During her time in India, she provided a masterclass at the Nexus Start-up Hub at the American Center New Delhi. Participants included women entrepreneurs, students pursuing entrepreneurship and IP law, start-ups, incubators and professionals working on IP laws.

Excerpts from an interview.

Could you tell us about AWIT? What are you doing to help more women into leadership roles?

AWIT is a nonprofit organization that I founded in 2016 when I was a product manager at Google. I had a tremendous manager and great support network, but they were all men. And I just didn’t see that many women out there. So, this was the personal mission behind getting more women into leadership roles.

Your work covers many aspects, from engineering, advising to even investing. What impact do you think artificial intelligence (AI)-enabled technologies have on innovation and creativity?

I’m excited about AI, specifically the use of copilots. Generative-AI (GenAI) technologies are used by developers to write code. However, Amazon has its own product called the CodeWhisperer. Externally, commercially, there’s also GitHub copilot, and I’m excited about that because it shortens the innovation cycle and helps you effectively innovate faster. There are many other applications for GenAI in industries, like, for example, medical diagnostics, oil and gas refining, financial services, trading decisions or transactions decisions. If we can properly leverage GenAI to improve our decision-making, enhance the speed, enhance the accuracy, that is what I’m excited about.

Are there any key trends or tactics and tools that you find are driving the wave of AI and digitization?

One of the first projects that I had when I joined tech was building healthdata.gov in 2011. At the time, I remember one of our biggest challenges was a lot of data. Whether it’s research data, patient data, experimental trial drug data—it was all on paper. And I remember the amount of work that it took to [run] OCR (optical character recognition). Digitizing those papers, storing that data into queryable databases was a tremendous effort that actually took probably the majority of the time we took to implement healthdata.gov. Fast forward to the 2020s, you have products like Google Translate where you can hover it over a text and it’ll show it to you in your native language. With augmented vision, there’s just so much potential for AI to enhance how humans can make decisions and share communications.

Can you share any stories or anecdotes about how you’ve helped people grow and get connected to their communities?

There’s one example of someone we’ve worked with for a long time. Ashley is a woman entrepreneur in New York City. She started out with not being in tech. As part of the AWIT program, she went through the courses, and I also mentored her one-on-one. She was actually able to land a product management job at Google. I’ve got messages from people in São Paulo and the United States, all completing the Coursera instruction that we have online and how it has helped them get a raise and how it has helped them find their dream tech role.

Do you have any advice for young SPAN readers who are looking at a career in AI?

On the AI front, what’s really exciting is that previously, and especially, in the last decade, we’ve had so many low codes [software development that requires little to no coding to build applications]. Essentially, AI or assistant solutions helped people write code. Before that, if you wanted to start a company, you had to do it all yourself. Fast forward to today, through the use of GenAI, we’re able to start tech companies. That represents a huge opportunity and unlocking a community of people who otherwise would not have the opportunity to start companies.

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