India’s semiconductor boom is pulling test and measurement into the design cycle

Norma Dorst is Vice President, Global Marketing for NI Test and Measurement at Emerson, where she leads global marketing strategy across brand, demand, partners, and field marketing. A technical business leader with over 30 years at NI, she has helped drive large-scale marketing and sales transformations that returned the business to double-digit growth while significantly reducing costs. With experience across applications engineering, product management, and global marketing leadership, Dorst combines deep technical understanding with go-to-market rigour, and is known for building customer-centric strategies, strengthening engagement with top accounts, and aligning marketing with sales and product teams to deliver measurable impact.

How is India’s manufacturing and semiconductor momentum changing conversations around design and testing?

India’s manufacturing push, especially in semiconductors, is reshaping how companies think about design and test earlier in product development. Government investments and global shifts in supply chains are driving new fabs and local testing capabilities. India is becoming a more important semiconductor manufacturing hub because of political considerations and supply-chain diversification, and we are excited to support semiconductor companies as they establish fabs and testing capabilities locally.

Semiconductors are foundational to electronics, automotive, and aerospace, so the demand for advanced test and measurement rises alongside that growth. What is changing is the urgency to integrate test earlier. Approaches like “shift left” and design-for-test matter because they help teams move faster and accelerate innovation.

Test and measurement is often treated as a cost centre. Why do you argue it is now strategic?

The old view of test and measurement as a cost centre is shifting. Product complexity is increasing, and that is pushing test from a back-end function to a competitive advantage. Test and measurement helps engineers get work done faster, even if it was previously viewed as an overhead.

AI and generative AI are also disrupting traditional test approaches. They can improve productivity and support faster delivery to market. As complexity rises, customers have to rethink how they test, and how they bring confidence into the engineering cycle earlier.

You have spoken about complexity doubling roughly every six months. What does that mean for engineering teams?

It means engineering teams need new ways to keep up without compromising safety, reliability, or quality. When complexity rises at that pace, you cannot rely only on older patterns of test and validation. The opportunity is to modernise how test is designed and executed so teams can move faster, with better outcomes.

Where does Nigel AI fit into this shift?

Nigel AI is advancing rapidly. We announced significant updates in February, and we have another set planned for May at NI Connect. The intent is to help customers rethink their test approaches as complexity grows and AI becomes a practical tool for productivity in test and measurement workflows.

Which industry segments in India stand out most for NI right now?

We see strong opportunities in aerospace and defence, semiconductors, and electric vehicles. Aerospace and defence are major growth sectors, and India’s progress, including achievements associated with ISRO, reflects that momentum. India’s academic strength and engineering talent also provide a strong foundation for future innovation.

In EVs, India is pushing forward with domestic development led by Tata and others. That creates growth potential in areas such as battery testing and ADAS technologies. Our longstanding semiconductor presence also aligns with India’s manufacturing expansion and supply-chain diversification.

How is NI evolving its platform strategy as AI becomes more central to engineering work?

We are advancing a platform strategy that combines modular hardware with AI-driven data insights to create new engineering workflows and competitive advantages. Modular hardware remains core to our approach because it lets customers adapt to technology shifts without rebuilding entire systems.

You have described a more data-centric platform philosophy. What does that mean in practice?

It means moving beyond measurement data alone and incorporating the broader context that AI needs. We look at four types of data: measurement data, test system data, company IP, and product data. Generative AI workflows will rely heavily on this mix to optimise test solutions and accelerate engineering tasks.

As this becomes more common, engineers will increasingly need data skills alongside traditional hardware and software expertise.

How are you approaching generative AI adoption so it does not feel disruptive for engineers?

The aim is to help engineers adopt new workflows with minimal training. Our platform supports AI-driven workflows through embedded optimisation and intelligence, and we also use training and seminars to ease adoption and accelerate productivity gains. We see AI as a career-long enabler rather than a disruptive overhaul, consistent with NI’s software-centric legacy.

Many vendors sunset older technology. You have said NI is not taking that route. Why?

We are keeping modular hardware as a foundation while layering new AI and data capabilities on top. The platform supports adding new technology without discarding customer investments. We are investing in optimising data use, not just expanding hardware features, so customers can stay ahead of shifts cost-effectively. This platform approach also supports a broader ecosystem, including IP and community resources.

In your view, what stays human even as AI accelerates workflows?

Humans remain central because oversight and responsibility for real-world performance cannot be delegated. AI can accelerate code generation, testing, and product development, but it does not remove the need for human judgement. Nigel AI and related technologies will support this evolving collaboration between engineers and AI.

How do you balance excitement about AI with uncertainty about where it will lead?

We cannot predict every future application, but we are confident AI will unlock unexpected opportunities. We have seen how breakthrough tools in the past empowered engineers and led to broad innovation. We aim to continue that tradition with AI-driven tools tailored specifically for test and measurement. NI Connect in May will highlight these advances and bring the community together around them.

Why is India strategically important to NI beyond market growth?

India has a strong academic and engineering culture, and that creates long-term opportunity to inspire and train new generations of engineers and scientists. We view India as vital across semiconductors, life sciences, and electronics within our portfolio, and we are engaging with academic institutions and industry partners to deepen our presence.

Even as global EV demand can dip, India is pushing forward with domestic EV development led by Tata and others. Our expertise in battery testing and autonomous driver assistance can support India’s evolving automotive landscape. The “Made in India” approach aligns with government priorities and supply-chain localisation, and that strengthens the business case for local testing capability.

On semiconductors, how does NI’s legacy connect to India’s manufacturing expansion?

We have a 25-plus-year presence in semiconductor testing and validation, and that aligns well with India’s growing manufacturing footprint. We are partnering with players such as Kaynes Semicon to support local fab development. As India expands manufacturing and design capabilities, it also builds a competitive advantage globally, and we want to be a trusted partner in that ecosystem.

Finally, NI is marking 50 years. How does that milestone shape your vision for what comes next?

NI was founded in 1976, and we are marking 50 years of innovation with a focus on future technology, including generative AI. We see AI as a “virtual teammate” that will assist but not replace human engineers. Safety, reliability, and quality remain paramount, so careful adoption is essential in industries that are rightly conservative.