AI revolution will be boon to some, burden to others

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Welcome to Advisor to Go, brought to you by CIBC Asset Management, a podcast bringing advisors the latest financial insights and developments from our subject-matter experts themselves. 

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Robertson Velez, portfolio manager, CIBC Asset Management 

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Let me talk about the current economic environment in light of the tariffs, and its impact on the tech sector. In my view, the challenging environment we have seen over the past few months was due to the uncertainty, particularly about significant policy changes in the U.S. and the impact that they have on the economy. 

Over the past few months, we have seen the administration put on huge tariffs — as much as 145% on China — then reduced and deferred them significantly. And at this point, we are not even sure if the tariffs can be implemented as they are now. So the main point is that the concerns are about the uncertainty rather than the technology thesis. So it’s important to look through what’s happening and filter out the signal from the noise. 

It has been the goal of the past two U.S. administrations to bring manufacturing in key technologies back to the U.S. The only difference is in the approach.  

The Biden administration used the carrot. For example: using a massive subsidy program like the CHIPS Act to bring back semiconductor manufacturing, which would have had to be paid for with taxes or inflation. 

The Trump administration is using the stick through tariffs on foreign imported goods, which is effectively a tax to incentivize specific capital allocation. The end goal is the same, which is to bring manufacturing back to the U.S. 

If we look past the noise at what this would mean to the U.S. technology landscape in a few years, technology such as AI becomes even more critical, not less, because of the need to improve productivity in the U.S. to remain competitive in global markets. 

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There are always many factors impacting the tech sector. So let’s talk about some of the existential threats beyond tariffs. There is a current belief in the U.S. administration that they can control the competitive landscape for technologies like AI through export controls of key technologies. So many export control restrictions have been put on U.S. companies and their allies, restricting them from selling key technologies to China. 

Beyond the short-term view of lost sales, I think there is a bigger risk that China will develop these capabilities on their own, without relying on American platforms, making them a bigger competitive threat longer term. Necessity is the mother of invention, after all, and China has demonstrated significant capacity for AI innovation, even in the face of significant export controls implemented so far. 

Longer term, the biggest risk to the tech sector is disruption itself. By its very nature, tech tends to separate winners and losers through the creative destruction process over time, and it is important to be on the right side of the technology adoption trends. The current theme in tech is AI, which is both the biggest potential opportunity and disruptor. 

I don’t think we talk enough about this because most people assume AI is good for everyone. But it is important to recognize which businesses will thrive with the adoption of this technology, and which will be disrupted by it. 

This isn’t as easy as it sounds, because practically every company claims to embrace AI, and investors assume that AI is just good for everyone. But without some kind of competitive advantage enabled by AI, this would just mean added costs for companies to stay relevant. 

Not all companies will be able to achieve competitive advantage through AI, and our job is to identify those with competitive advantages. 

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So, in terms of the AI revolution and what it means for investors, about 80% of the portfolio is invested in the AI theme. Let me talk through these three themes. 

We own the fundamental core of AI, such as semiconductors and infrastructure. There’s a view that having run up so much over the past two years, it would be difficult for these companies to continue to grow, especially in the face of advancements in the cost efficiency of AI algorithms. Our view is that as the costs of implementing AI come down, the demand for AI actually goes up, not down. And this is supported by the continued growth in CapEx guidance of the major hyperscalers, like Alphabet, Meta and Microsoft. So examples of companies in this theme are Nvidia, which remains the core AI infrastructure play, and Broadcom, which benefits from AI-related connectivity solutions, as well as custom chips for AI. 

Secondly, we invest in enterprise software and tools where AI applications are used. The challenge with enterprise in using AI is not just AI itself, but in migrating its large stores of data to a form that is useful for AI training. We believe that the market for data migration tools will be as big as the AI market itself. So we invest in companies that have access to enterprise data that can use AI to significantly improve productivity. 

For example, Microsoft Copilot can access enterprise data to augment its Office suite. ServiceNow uses AI to incorporate data to enhance workflows. And Salesforce uses enterprise data to implement agentic AI to replace human functions. 

Third, we invest in direct applications of AI to the consumer. This could take many forms, such as AI enhanced search engines, better enhanced recommendation engines or analytics, or new consumer-facing applications. 

For example, Google and Meta uses AI in all its consumer-facing products to improve monetization. Apple uses AI to augment its smartphone products. 

So these are some of the opportunities ahead, and I believe we’re still at early stages of this AI adoption curve. 

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So what challenges remain? 

The biggest challenge in any adoption of new technologies is acceptance. Most industries are very resistant to change, and the tech landscape is littered with products that fail to get consumers and businesses to change behavioural patterns. 

For example, virtual reality largely failed in the past to achieve mass adoption because people didn’t want to wear a bulky headgear for their entertainment. And many businesses still run on mainframe today because of the difficulty in getting large institutions to transition out of old systems. 

AI has an advantage in that it adapts well to human behaviour, and it has gained traction in many applications that are an easy replacement for human functions, such as in contact centers and in coding. More complex tasks, however, are more difficult to penetrate due largely to issues of trust. 

As AI is proven out in various fields of endeavour, however, such as in robotaxis or in humanoid robots, I think we will soon see an inflection point in AI adoption. And I think that this is a huge opportunity over the next decade, of which we are still at early stages, probably the first two or three years of this AI adoption curve. And over the next decade, this will be the biggest opportunity in technology. 

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So, what is my outlook for the tech sector? 

My outlook over the medium and long term has been positive all year. Even ahead of the U.S. Liberation Day announcement, I had said I was cautiously optimistic on tech, ahead of what we knew would be very disruptive trade policies. 

I’ll give you some context for my optimism. The technology sector is driven by cycles. We can look back at massive tech cycles in the past, like smartphones and PCs, and we generally see a period of about a decade when we see massive growth as the technology is adopted. We are about two years into the current technology adoption cycle of AI. We have seen massive spending by the large hyperscaler companies in AI infrastructure, which I expect will translate into adoption in enterprise and consumer applications. And we are still at very early stages in the proliferation of AI. 

So, let me talk about the current environment. We have seen a lot of challenges over the past several months due to uncertainty about U.S. trade policies. But looking past the noise, we believe that AI remains the most important technology to invest in over the next decade because of its potential to massively change the way we work to improve productivity. And I think that we are still very early in that cycle, and the opportunities are still ahead of us.

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