By Deepak Agarwal, CVP, Silicon Design Engineering, AMD
Every generation of silicon brings greater complexity. The challenge is no longer simply designing a better chip, it is enabling engineers to keep pace with that complexity while maintaining quality and speed. As architectures become more sophisticated and AI workloads expand, engineering capacity must scale alongside technical ambition.
Verification illustrates the urgency. The 2024 Wilson Research Group study found that only 14% of IC and ASIC projects achieved first-silicon success, the lowest level recorded in two decades. This reflects how difficult it has become to validate increasingly complex systems within demanding development timelines.
AI can help address this challenge, but its value lies in practical application. In chip design, AI is already supporting design exploration, verification, debugging, validation, and code and test generation. It can help engineers analyze large datasets, identify patterns faster, reduce repetitive work, and improve the speed of iteration. The objective is not to replace engineering judgment, but to enable engineers to apply it more effectively.
The real transformation is not about creating a new category of engineer. It is about equipping every engineer with the ability to use AI as naturally as they use simulation, automation, or debugging tools today. That shift requires more than technology. It requires learning, experimentation, and a culture that encourages engineers to rethink established workflows while maintaining the rigorous quality standards semiconductor design demands.
Over the next couple years, AI will evolve from supporting individual engineering tasks to orchestrating entire design workflows. Specialized AI systems will increasingly collaborate across architecture exploration, verification, physical design, and system validation, while engineer provide the judgement, oversight and system-level decisions that ensure quality and reliability. India’s strength lies in its combination of engineering scale, deep technical expertise, and ability to solve complex system-level problems.
As AI becomes embedded into semiconductor development, this talent base positions India to play an even more strategic role. Engineering teams here are moving beyond execution-led responsibilities to take greater ownership across IP development, SoC verification, physical design, design-for-test, and physical design. At AMD, teams in India have contributed to every generation of AMD EPYC server processors since their launch in 2016, demonstrating the depth of capability available in the country.
Technology alone will not create this transformation. Organisations must create an environment where engineers are encouraged to experiment, share successful use cases, and continuously learn from one another. AI adoption is as much a cultural shift as it is a technological one.
For young engineers, the future of semiconductor innovation will not be defined by AI alone, it will be defined by engineers who know how to combine deep technical expertise with AI-driven workflows. Organisations that invest equally in tech, talent and culture will be the ones that define the next era of computing.
Express Computer is one of India's most respected IT media brands and has been in publication for 24 years running. We cover enterprise technology in all its flavours, including processors, storage, networking, wireless, business applications, cloud computing, analytics, green initiatives and anything that can help companies make the most of their ICT investments. Additionally, we also report on the fast emerging realm of eGovernance in India.