Seema, can you tell us about your AI journey? 

I was introduced to the fascinating world of Artificial Intelligence (AI) during my university days in the 90s. We explored the basics of AI, discrete mathematics, and learned the Prolog programming language – one of the early logical programming languages intended to express logic as relations. However, AI was still an aspirational area of tech at that time and not ready for mainstream adoption. 

In the past decade, however, the conditions have changed dramatically in favour of AI, thanks to the advent of the Cloud, high-performance computing infrastructure, and the ubiquitous availability of data. My early work with AI in the industry required me to advocate the technology to communities of developers, students, and startups across the country. I have also had the opportunity to work closely with key enterprise customers to chart out their AI journey and embed AI into their core business processes.

What made you interested in AI?

I have always been fascinated by the fact that machines can be made to think and replicate human-based decision-making. AI systems help reduce the burden of repetitive tasks and complex data processing, freeing up our time and intellectual capacity to do more human-centric tasks. AI allows us to amplify and scale intelligence in ways never done before. The application of AI in industries such as healthcare, manufacturing, financial services, and several others, enables us to apply data-processing at scale and automate intelligent decision-making, thereby reducing costs and applying crucial human capital to more value-added work. It has been interesting to see how AI has been adopted across different customer segments. 

One of the factors that influence the adoption pattern is the maturity of their existing data estate. For example, an early-stage startup would embrace AI by leveraging cognitive services and cloud-based APIs to build virtual chatbots, cognitive search, natural language, speech processing, and the likes. On the other hand, large enterprises will look at modernizing their large data estate to create actionable insights and embed advanced Machine-Learning-based models to streamline intelligent decision-making. 

What are the major challenges you faced as a woman in reaching where you are right now?

By nature, I am not one to shy away from challenges and have always thrived in chaos. I have a strong support system of allies – both personal and professional – who have helped me tide over difficult times and allowed me to push boundaries, take risks, and keep moving forward. 

What's your area of expertise in AI and why choose that one?

Having worked with a varied ecosystem of customers, partners, startups, and developers, I have seen the application of AI across the spectrum. I strongly believe in the democratization of AI, wherein AI-based services and modelling are made available to every person and every organization. My expertise lies in identifying these opportunities, uncovering interesting use cases for AI, and marrying the application of this technology with real business benefits for customers. 

What's the one thing that you see AI transforming completely?

I believe we are just getting started on the AI journey and that it has the potential to disrupt and redefine entire industries. AI will push knowledge workers to enhance their digital skills to ensure a seamless man-machine experience. Whatever the industry – healthcare, manufacturing, retail, automotive, education, citizen services, or any other – AI technologies will enhance the overall customer and employee experience and enable end-users to make intelligent choices. 

Your biggest AI nightmare?

As AI becomes ubiquitous, we must manage and maintain trust and ethical standards while designing, developing, and training responsible AI systems. Systems and platforms need to ensure they build transparency into AI-based decision-making to detect and remove biases and augment human creativity. Young children today are introduced to AI at a very early age – in the form of voice assistants, video recommendations, and the likes – and I worry about the impact it will have on their ability to make the right ethical choices and how it will influence their thinking and opinions. Hence the need for the right set of regulations and standards for responsible AI that is inclusive of all groups in the human population. 

What is your advice for other women who want to pursue a similar journey?

Never miss an opportunity to learn new things. Cultivate a mindset for lifelong learning, always be curious, and do not hesitate to question assumptions. The best parts of being in the tech industry are the ever-evolving landscape, the high degree of innovation, and the opportunities to keep picking up new skills and sharpening your expertise. A career in AI is no different. You can choose to go deep and build engineering expertise around data science, Machine Learning and AI algorithms. Or you could specialize in a particular industry or business domain, wherein you can use AI for enabling efficient decision-making, improving processes, and enhancing customer experience. Whichever area you choose to pursue, as long as it aligns with your interest and your passion, you will find ways to go deeper, learn, and more importantly, share what you know to inspire others.