AI’s trajectory is particularly significant in India since the country aims at becoming a global hub for technology innovation. While much attention has been given to infrastructure, manufacturing capacity and policy support, skilled talent—the real determinant of success in this field—has largely been neglected. The effectiveness with which India can become a force to reckon with in the field of AI depends on its workforce and its preparation. For anindustrylike semiconductors, where it’s all about design, engineering and production, skilling strategies will dictatewhether India becomes a leader or a laggard.
Addressing the skills mismatch
AI continues to raise fears of redundancy and job displacement. Repetitive and rules-based work will be automated.However, becoming irrelevant poses a much greater risk to India’s technology workforce. But it is also creating more opportunities than it eliminates. For example, in semiconductor design and systems engineering, there is a growing demand for expertise in areas like electronic design automation, AI accelerator architecture, advanced packaging, verification and hardware security.
India’s challenge lies in ensuring that engineers are adequately equipped to integrate AI into these workflows. If the current generation of designers and system architects cannot adapt, the country risks losing competitiveness in a sector that is strategically vital and economically promising. The narrative needs to shift from the fear of job loss to the urgency of reskilling.
Reskilling leadership
Building workforce readiness needs to go beyond the engineering floor. This means leadership across India’s technology enterprises must also evolve in an AI-driven ecosystem, going beyond deep domain expertise and decision-making to one of orchestration—bridging domains, balancing innovation with risk and aligning technology with business outcomes.
In the semiconductor sector specifically, helpingleaders acquire new skills requires that companiesfocus on preparing them to steward AI responsibly across complex value chains. For example, leaders must become fluent in data-driven decision-making and systems-level thinking. They must be able to connect the dots between silicon design, cloud-scale AI workloads and end-market applications. They also need to internalize the ethical and governance aspects of AI adoption.
Embrace proactive reskilling
In India, workforce skilling has typically been reactive in nature, after gaps emerge or when bottlenecks are exposed during technology development or adoption. Such delays can prove costly in the semiconductor sector. Design cycles are long, investments are significant and global competition is relentless. India will need to foster a culture of proactive reskilling that anticipates the impact of AI and invests in learning long before the need arises.
This requires tailored and structured programs in whichengineers learn how AI accelerates verification and physical implementation, where support teams can understand how AI can streamline workflows, and where leaders can be trained to evaluate trade-offs between speed, security and scalability. It is also essential for enterprises to embed AI literacy into day-to-day work instead of treating it as a peripheral module. This way, enterprises can ensure a more natural and sustainable training process.
Create a culture of adoption
Skilling initiatives succeed only when paired with cultural reinforcement. In India, for instance, where one has to work with a diverse workforce, enterprises must encourage experimentation and recognize achievements, both big and small. Activities like innovation contests or hackathons and regular collaborative platforms can help employees see AI as a co-pilot rather than a competitor. Doing so will build momentum for AI-enabled problem-solving techniques across functions.
For the semiconductor sector, which is still relatively nascent in India when compared to global peers, this cultural dimension is also important. Employees must feel empowered enough to move beyond legacy practices and innovate within their workflows. A culture that celebrates such work practices and cross-disciplinary collaboration will be able to accelerate the sector’s maturity and competitiveness.
Building a talent advantage
If India is committed to becoming a global semiconductor hub, it must treat workforce skilling as a strategic national priority. This will require universities, policy makers and enterprises to collaborate on multiple levels—to align curricula, put research agendas into place and design training programs while keeping the realities of an AI-driven design ecosystem in mind. The industry must go beyond traditional training models to create agile learning pathways that are continuously updated.
Government initiatives like Skill India and Semicon India provide useful platforms, but their success depends on how effectively they embed AI readiness into technical education and enterprise practice. The private sector must also recognize that reskilling is an investment and not a cost center. Engineers equipped with AI tools can shorten design cycles, reduce errors and open new frontiers of innovation. Leaders who understand these implications will position their organizations to compete locally and globally. Such an alignment will translate into a talent advantage in the semiconductor sector in India.
–Authored by Navin Bishnoi, AVP Data Center Engineering and India Country Manager at Marvell Technology