UBS Asian Investment Conference 2026: Investing in an Age of Change

Investors face an unusual challenge in 2026: balancing near-term uncertainty against long-term transformation.

Geopolitical tensions, energy-market risks and policy shifts continue to cloud the economic outlook. Meanwhile, rapid advances in artificial intelligence are creating new opportunities, from enterprise software to biotechnology.

At the UBS Asian Investment Conference, more than 4,800 global policymakers, business leaders and investors gathered in Hong Kong to discuss the competing forces reshaping markets. Here’s how they’re thinking about both the risks and the opportunities ahead.

For Arend Kapteyn, Global Head of Economics and Strategy at UBS, today's investment landscape is being shaped by two powerful forces.

“The two big forces right now are the energy uncertainty and the AI capex wave. Tech has really started to dominate the price action. Basically 60% of the global equity market returns are now driven by tech stocks, even though they only have about 30% of weight in equity indices.”

Despite geopolitical tensions and market volatility, Kapteyn believes the underlying economic backdrop remains resilient.

“There's a lot of weakness in the soft data and the surveys, but what's remarkable is how little damage we've seen so far in the global hard economic data. Central banks have cut interest rates. Credit growth is picking up globally. We've survived the tariffs. Healthy labor markets, recovering credit growth, neutral fiscal policy and neutral monetary policy: it's actually not a bad backdrop for the global economy.”

Against largely healthy macroeconomic indicators, Kapteyn cautions against underestimating how quickly conditions can change.

“I am very worried about what happens if we keep depleting energy inventories. Once you get to a certain level where panic buying starts, prices begin to move exponentially. And once you get into a rationing phase and you physically run out of product, the economic damage multiplies. The interesting thing is not so much the level. It's the speed.

What's interesting about the US in particular is that you can now do more damage through an equity market sell-off than through the oil price itself. US households are sitting on roughly 232% of GDP in equity wealth. A 15% drawdown in the S&P 500 would destroy around 35% of GDP in equity wealth and could easily take a percentage point off consumption. To some extent, the outlook has become endogenous to whether the equity market panics or not.”

For Kapteyn, another tension lies in AI. Market enthusiasm has not necessarily translated into widespread business transformation.

“What's striking to me when we look at enterprise surveys is how vague the responses still are. There is a massive gap between the optimism people have about the speed of adoption and the actual speed of adoption. A year ago, 85% of respondents said they were going to be implementing AI at scale within 12 months. The actual increase in adoption was 3%. We're still in the figuring-it-out phase.”

If investors are overestimating the speed of AI adoption, Simon Johnson, Nobel Laureate and Professor at the Massachusetts Institute of Technology, believes they may also be underestimating its ultimate impact.

“AI is obviously the topic of the day. The really interesting thing is what does it create that's new, brand new? What is it that companies or entrepreneurs or scientists can do that humans couldn't do before AI? Looking for those opportunities and really engaging with the creators of the intellectual content – the science and technology – that's what investors should be thinking about.”

Johnson sees healthcare, education and finance among the sectors most likely to be transformed, but argues that societies must ensure technological progress creates opportunities for workers rather than simply replacing them.

“You have to embrace automation. It's an unavoidable part of economic development. But you also need to create new tasks and increase the demand for human labor. Otherwise you get a really big split between people who have money and wealth and the right kind of human capital – and everybody else.”

Johnson also cautions that increasingly capable AI systems may evolve in ways that challenge both investors and society.

“We have this idea that there will be layers: large language models at the bottom and applications built on top. But what if those base models become so capable that they can take over finance, law and other verticals? That would obviously be quite disruptive to some existing investment models.

AI will become immensely capable, and I think we will imbue it with human characteristics because it will be more productive if you make it quirky, entertaining and charming. But when you give it personality, you also begin to lose control. When you create immensely powerful, competent servants, they do not remain quiescent. They want to go off and do their own thing.”

While many companies are still struggling to quantify returns from AI, Randy Abrams, Head of Taiwan Research at UBS, sees evidence that investment in the underlying infrastructure continues to accelerate.

“In the supply chain, we're seeing supply short of demand everywhere. Everything has gotten tighter. As quickly as the hyperscalers bring on more data center capacity and more capacity to process AI, they have the demand for it. So it's not as speculative as we had back in 2000. We're in a shortage for compute.”

What has changed over the past year is the breadth of companies benefiting from the trend.

“A year ago, you probably would have said a lot of the benefits of AI compute was concentrated among a few winners. Today, a much broader number of companies are starting to benefit and find AI truly useful. If you want to do agents, you need a GPU and you need a CPU. All of a sudden, that means stronger demand for CPUs as well. It surprised people that the CPU came back into favor because it was treated as mature and slow. Now CPUs are doing well.”

Looking beyond today's infrastructure buildout, Abrams believes investors are beginning to focus on the next generation of AI-enabled products.

“I'm watching physical AI, autonomous robots and humanoids. China has the supply chain. They have a lot more startups, the systems and the components. The pace of iteration is very fast. You can start to see applications in healthcare, caring for the elderly, education and the factory floor.”

Another area he is watching closely is on-device AI.

“We're still waiting for on-device AI. You're seeing some product cycles emerge, but they're not yet mass market. Smart glasses are one example. We're going to see more devices coming to market and the question is whether they can make on-device intelligence compelling enough to drive an upgrade cycle. That's one of the next frontiers I'm watching.”

Even amid strong demand, Abrams remains mindful of the risks.

“Cycles usually end when supply catches up to demand. AI is recession-resistant. It's not recession-proof.”

While AI adoption remains uneven across much of the economy, healthcare is emerging as one of the sectors where the technology may have the greatest long-term impact.

For Alex Zhavoronkov, Founder and CEO of Insilico Medicine, the real promise of AI lies in helping researchers tackle problems that were previously considered too risky.

“We like to work in moderate to ultra high-risk areas where we rely on AI to give us more confidence in both novel targets and novel molecules. When we initiated the first internal program, we had zero experience in producing drugs. And right now we are outperforming most of the very large companies that have been around for centuries. 13 of my AI-generated drugs have received Investigational New Drug (IND) approval. So the sheer speed and the scale by which we apply AI to drug discovery – and the productivity we managed to achieve – is undeniable proof that AI has impacted this industry.”

When evaluating AI-powered innovation, Zhavoronkov believes investors should focus less on AI claims and more on measurable outcomes.

“There is a lot of noise and a lot of companies claiming that they are applying AI to drug discovery. But in reality, AI drug discovery is, at the end of the day, drug discovery. You need to look at the performance metrics.

If the productivity metrics significantly exceed what you see in traditional pharmaceutical companies, then the company is making real progress. If not, you have to be very cautious. It's better to have drug discovery companies that are faking AI than AI companies that are faking drug discovery.”

Zhavoronkov also points to China's growing role in biotechnology innovation.

“Over the past 20 years, China has become the go-to place for biotechnology innovation. This is the new paradigm, where drugs are being born in China and then raised by big pharmaceutical company parents around the world. If your R&D base is in China and you apply AI on top of it, you can shave years off the drug discovery cycle.”

Looking further ahead, Zhavoronkov sees quantum computing as a catalyst for the next phase of innovation.

“Quantum technology is still in its infancy. We demonstrated the first proof of concept that quantum can do this. However, we did not claim quantum advantage. If you were to do this on regular GPUs, you could. We have to be very realistic in terms of timelines. Quantum is not going to disrupt drug discovery in the next two years.”

Atsushi Seki, Japan Pharmaceuticals Analyst at UBS, agrees the long-term opportunity could be significant.

“With quantum computing, you can calculate more precisely and simulate interactions with proteins and water much more effectively. That's why we expect significant enhancement in productivity.”

Beyond today's dominant healthcare themes, Seki believes investors should be looking for the next wave of opportunities.

“People are paying attention to cancer and obesity. We need to think about what's next. There are still many diseases to be treated, and there are plenty of opportunities in healthcare and pharmaceuticals that nobody is talking about.

Historically, Japan contributed four or five approvals a year out of roughly 50 drugs approved annually by the FDA. Now Chinese biotech is catching up, and five years from now we could see significantly more approvals coming from China.”

Areas attracting growing interest include muscle preservation and quality-of-life treatments.

“If you're taking GLP-1 therapies, you lose both fat and muscle. There could be huge demand for muscle boosters – not only for elderly people, but potentially for younger people as well. It's also important to think about how we can live with cancer and improve quality of life. I can imagine that in five or 10 years, the lives of cancer patients will be much better than they are today.”

For investors, Seki believes one of the most intriguing questions is whether healthcare could become one of the next major beneficiaries of AI.

“If you look at pharmaceutical stocks in the last 12 months, they're underperforming compared to the S&P 500 because pharma is so far not a huge beneficiary of AI. Once that changes, once pharmaceutical research begins benefiting from AI at scale, the growth could be significant. Across drug discovery markets, we're seeing great opportunities in oncology, obesity, autoimmune diseases and many other therapeutic areas. I'm so excited about the opportunities.”

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