Architects of Great Talent | Beyond the Pedigree: What It Takes to Build a Career in AI Today | Parikshit Nag (ABB)

AI is everywhere, but building AI that works at enterprise scale takes much more than models and algorithms. It calls for strong fundamentals, reliable data, engineering, and an understanding of real-world business problems.

In this episode of Architects of Great Talent, Parikshit Nag (Group Head of Artificial Intelligence and Machine Learning at ABB) speaks with Mridul Kumar (Senior Vice President, Products, HirePro) about what it takes to build enterprise AI and navigate a career in this rapidly evolving field.

Students and aspiring AI professionals will discover how to:

• Build a strong foundation in AI beyond simply learning tools and models
• Make side projects stand out through original problem-solving
• Navigate a career in AI

HR and talent leaders will gain insights into:

• The skills and capabilities to look for when hiring AI talent
• Why data quality, infrastructure, and adoption are critical to AI success
• How AI can augment human decision-making in enterprise environments

From studying Economics to working across consulting, consumer goods, consumer technology, and entrepreneurship, Parikshit’s career has taken him into the world of industrial AI. He shares the experiences that shaped his journey and his vision for enterprise AI at ABB, where the focus is on enabling better, faster, and more informed decisions.c

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Frequently asked questions (FAQs)

1. What does it take to build AI solutions for enterprises? 

Enterprise AI requires more than a strong model. Clean data, reliable infrastructure, engineering, and business context are equally important.

2. Why are strong fundamentals important for an AI career? 

A foundation in mathematics, statistics, and problem-solving helps professionals understand AI and apply it to real-world challenges.

3. Can you build a career in AI without a computer science background? 

Yes. Parikshit Nag’s journey from Economics to AI shows how professionals can transition by building technical skills and leveraging their existing strengths.

4. What skills should recruiters look for when hiring AI talent? 

Look beyond tools and models for strong fundamentals, problem-solving, engineering skills, and the ability to apply AI to business challenges.

5. What makes an AI project stand out? 

Projects that demonstrate original thinking and solve meaningful problems stand out more than simple applications built around existing AI tools.

6. What role does data play in enterprise AI? 

Clean data, robust pipelines, and effective data management are essential. Without them, even a strong model may fail to deliver results.

7. How can AI augment human decision-making? 

AI can provide insights and quantitative inputs that help people make faster, more informed decisions while keeping human expertise central.

8. How is AI being used at ABB? 

ABB is exploring enterprise AI in areas such as Finance and FP&A, focusing on predictive and prescriptive insights to support faster decision-making.

9. How can professionals transition into AI? 

Build on your existing expertise while strengthening technical fundamentals. Hands-on projects, continuous learning, and networking can help you make the transition.

10. What is the future of enterprise AI? 

Enterprise AI is moving toward integrated systems that combine data, engineering, and business context, with AI augmenting rather than replacing human expertise.