In Dialog with Young Sohn

You spent years at Samsung as Chief Strategy Officer, where you shaped strategy for a global tech leader. How has that experience influenced your approach to innovation and AI at Harman, particularly within the mobility sector?
Samsung sees AI not as a feature – but as an enabler of entire ecosystems. Their »AI for All« strategy integrates ambient intelligence seamlessly into daily interactions through devices like smartphones, wearables, and importantly, vehicles. This belief is shared across Harman. It’s no secret that today’s drivers and passengers demand integrated, personalized experiences akin to the smart devices they use daily.
Technology should anticipate your needs, not just react. So Harman is now embedding intelligence across its automotive portfolio of products in order to translate user states and situational understanding into truly contextual incabin experiences. The intent is that your car understands your needs, adapts to your preferences and creates an environment that understands and uniquely engages with you.

AI depends heavily on processing power. From your experience in semiconductors, what’s the state of that industry – and why does it matter?
Semiconductors have arguably become the most valuable components on earth. No longer just components in consumer electronics, they now underpin economies, national security, and technological progress – especially as AI continues its meteoric rise. Nations are racing to secure supply chains, and companies are investing billions to push the limits of chip design and fabrication. As AI drives exponential growth in computing demands, semiconductor manufacturers are trying to meet the challenge of scaling processing power while managing energy efficiency.

AI models today are voracious consumers of computational resources. Training large-scale AI requires unprecedented amounts of processing power. For decades, Moore’s Law – predicting a doubling of transistor density roughly every two years – was enough to meet the demands of the industry. But as we approach atomic-scale limits, squeezing more transistors onto a chip gets harder, and improvements in performance are increasingly dependent on new breakthroughs in semiconductor technology.

For new semiconductor architectures, energy density and data bandwidth are the two most critical elements for addressing the demands of AI. AI workloads demand efficiency at scale, making advancements in semiconductor energy efficiency essential. The Global Semiconductor Alliance recently highlighted that by 2030, AI workloads are projected to consume up to 20% of global electricity demand if efficiency doesn’t improve. That is staggering and unsustainable. And for AI model computation, processing power isn’t the limiting factor anymore; the bandwidth between memory and GPU is the most crucial element. Complex models require the movement of massive datasets between high-speed memory and processors. High Bandwidth Memory (HBM), chiplet architectures, and innovative interconnects will shape the next wave of semiconductor designs to keep AI running at full throttle. Other semiconductor companies are leveraging design tools to accelerate the development of these next-generation, more powerful, energy-conscious chips.

During your time at Samsung, you played a key role in strategic moves like the acquisition of Harman, which brought Samsung into the automotive technology space. What did that experience teach you about the convergence of the tech world with traditional industries like automotive or manufacturing?
The strategy was rooted in a clear vision: the car was becoming a connected, software-defined device – and would become a critical link for the next big consumer electronics ecosystem. Let me share my original slide when we announced the Harman acquisition on November 14, 2016. Samsung saw this trend and knew HARMAN was the perfect partner to make that happen. By acquiring HARMAN, Samsung instantly gained a leadership position in the automotive electronics business, and would enable us to fulfill our vision of »One Connected World«.

And the acquisition has been a great success. HARMAN has grown consistently under Samsung’s ownership. The company’s annual sales have grown from about $7.6 billion in 2017 to roughly $10.5 billion in 2024, turning an Operating Profit loss of $49 million into about $1 billion in profit.

Those results weren’t accidental – they came from combining each side’s strengths. Harman was already a trusted Tier-1 partner to automakers, and building on that foundation allowed us to integrate beloved consumer audio brands like JBL, Harman Kardon, and Bang & Olufsen into vehicles to create rich, branded in-cabin experiences. At the same time, we brought Samsung’s ecosystem thinking and massive scale into the automotive space, which meant we could innovate faster and support our OEM partners globally.

It was a true convergence of Silicon Valley-style innovation with automotive industry know-how. And importantly, Harman’s strong CEOs like Dinesh Paliwal, Michael Mauser, and now Christian Sobottka are driving this vision.

What lessons can the automotive industry take from others that have already undergone digital reinvention?
I think one of the biggest lessons for the automotive industry is the need for speed and agility at scale. The traditional 5-to-7-year automotive development cycle just doesn’t cut it in today’s tech-driven world. Some Chinese EV startups are moving from concept to production in under two years – and that kind of agility is a wake-up call. They’ve basically adopted a consumer electronics mindset for vehicles. That’s a huge competitive threat to incumbents, who are finding they look slow by comparison.

So »speed and scale« has become a mantra. By speed, I mean shortening development and update cycles – using agile methods, rapid prototyping, more software-defined architectures that can be iterated quickly. By scale, I mean designing platforms (both hardware and software platforms) that can be deployed across many models and even brands, so you get economies of scale and a large user base to learn from.

But speed alone isn’t enough – this industry also demands safety and reliability. In autos, if you »move fast and break things«, you literally might break things – or hurt people – which is unacceptable. We have to balance the Silicon Valley urgency with the automotive industry’s zero-defect mentality. Reinvention doesn’t mean letting go of what makes the industry great – it means evolving fast enough to stay in the game.

How is HARMAN uniquely positioned in this transformation?
HARMAN is a brand and experience company. It is one of the few companies that truly bridges the gap between consumer tech and automotive. We have iconic consumer audio brands like JBL and Harman Kardon. And with our recently announced acquisition of Sound United’s consumer audio business, we’ve added legendary names like Bowers & Wilkins, Denon, and Marantz to the HARMAN family as well.

This gives us a one-of-a-kind consumer experience portfolio and a unique ability to bring the best of audio and emotion into the vehicle. We take what people know and love from their living rooms or their headphones – and bring it into the vehicle. It’s not just about sound quality; it’s about delivering a seamless, premium in-cabin experience that feels personal and connected. And when you combine that with HARMAN’s deep automotive expertise, it allows us to create something truly differentiated.

That’s what sets us apart – we’re not just building hardware; we’re helping automakers elevate their brand through immersive, emotionally resonant experiences that make the car feel like a natural extension of your digital life.

AI brings benefits, but also energy demands and ethical questions. How should leaders respond?
AI is unlocking amazing possibilities, but it also brings some serious challenges – especially around energy use and ethics. Just to give you a sense of scale, training and running advanced AI could require an additional 50 gigawatts of power by 2030. That’s like building 50 new nuclear plants.

So this isn’t just a tech issue – it’s a major infrastructure and sustainability challenge. Leaders need to approach this with real urgency and responsibility. AI delivers incredible benefits, but it comes with huge energy needs and thorny ethical issues. Meeting that demand is a big challenge for energy grids and the climate. So, we have to make AI more energy-efficient and ensure it’s powered by sustainable energy. Companies like Samsung and others are tackling this head-on with AI-driven solutions that shrink the energy footprint through better hardware and optimized software.

On the ethics side, it’s about trust. AI can sometimes »hallucinate« – make things up – or reflect bias in its training data. For example, a self-driving car might misidentify a pedestrian as a shadow, and mistakes like that erode trust and can be dangerous.

That’s why human oversight, constant data validation, and transparent algorithms are so important. We also have to acknowledge the global gap in AI access – building powerful AI takes a lot of resources. As we scale AI, we must ensure transparency, fairness, and bias-free systems are built into our strategies from the ground up. If we take responsibility now – on energy, on ethics, on equity – I truly believe AI can be a force for good that benefits everyone.

If you had to leave today’s mobility leaders with one message, what would it be?
If I could leave you with one message today, it’s this: embrace AI with both speed and scale – starting right now. AI isn’t just another tool; it’s transforming every layer of your business, from infrastructure and operations to customer service and R&D. Automation powered by AI is already reshaping how we work, helping teams tackle complex problems faster and more efficiently.

And we’ve only scratched the surface. The next big wave is physical AI – robotics, autonomous vehicles, and intelligent systems interacting directly with the real world. After that comes science AI, helping us discover new materials and revolutionize healthcare, speeding up breakthroughs in medicine we never imagined possible.

My advice: don’t hesitate or wait for perfect conditions. Move fast, scale quickly, and make AI a central part of your strategy. The leaders who act boldly today – who prioritize innovation and adaptability – will shape tomorrow’s mobility landscape.