Breaking into AI: A conversation with Jeevantika Lingalwar
16/04/26
AI may dominate headlines, but for those looking to build a career in the field, the starting point is often less technical than it seems. As demand for digital skills accelerates, understanding what truly matters is increasingly important for your people.
Jeevantika Lingalwar, Head of AI Business Application at HCS and former Microsoft Partner Solution Architect, argues that breaking into AI is less about mastering complex code and more about developing the right mindset.
In this interview, she outlines the foundational skills, learning pathways and real-world competencies that can help turn curiosity into a career.
Q: You lead large-scale AI initiatives today, but what are the foundational digital skills young people should start building now if they want to work in AI in the future?
JL: Although AI can sound complex, the foundations are very human and achievable. The most important skills are curiosity, problem‑solving and digital confidence. Before writing advanced algorithms, young people need to understand how technology fits into everyday life, how data is created and how systems make decisions.
From a practical perspective, I encourage building a strong baseline in digital literacy – understanding data, learning basic coding or logical thinking, and becoming comfortable with digital tools. You do not need to become a computer scientist on day one. Learning how to break a problem into steps, test ideas and improve them over time is far more important.
Critical thinking and awareness of ethics are also essential. Young people should feel confident asking where data comes from, who a solution benefits and who might be left out. Responsible AI starts with awareness, empathy and accountability.
Communication and collaboration are equally important. AI is not built in isolation, but by diverse teams for real people. Future leaders will be those who can explain complex ideas clearly, listen to different perspectives and work across disciplines.
My message is simple: you do not need to wait to be “ready” for AI. Start small, stay curious, and focus on learning how to think, not just what to build.
Q: Many students learn coding through initiatives like Code Week. In your experience, what makes informal or community-based learning effective compared to traditional education pathways?
JL: In my experience, informal and community-based learning is effective because it changes how young people feel about technology. Traditional education pathways can make digital skills feel rigid or intimidating, while initiatives like Code Week focus on participation, curiosity and learning through mistakes.
These environments are practical and relevant. Instead of abstract concepts, students build, experiment and solve real problems. When they see how coding connects to everyday life or issues they care about, it becomes meaningful.
Another factor is accessibility. Flexible and inclusive settings support different learning styles and allow students to engage on their own terms. For many, this is the first time they feel confident in a technical space.
The sense of community is equally powerful. Learning alongside peers and mentors shows there is no single pathway into tech and makes success feel more achievable.
What I see time and time again is that informal learning builds confidence first. Once that belief is established, many are more willing to pursue further education or careers in tech.
Q: There’s often a focus on technical skills, but your career shows strong leadership and cross-functional work. What non-technical skills are just as critical for succeeding in tech today?
JL: It is easy to assume success depends mainly on technical ability, but some of the most important skills are not taught in code editors or textbooks. One of the most valuable is how you think. Being able to see the bigger picture, ask the right questions and understand why a problem exists will set you apart. Technology is most powerful when it is used with purpose.
Communication is also critical. People in tech spend a lot of time explaining ideas and working with others. Being able to express yourself clearly, listen and collaborate effectively is essential in any role. Confidence and self‑awareness matter as well. You do not need to know everything to belong in tech. In fact, curiosity and the willingness to learn are far more important. Good judgement is increasingly important as technology evolves. Success is not just about building something impressive, but making thoughtful and responsible decisions.
Finally, take ownership of your learning. Explore beyond school curricula, join communities and work on small projects that interest you. You do not need to wait for permission or the “right time” to start.
