Goldman Strategist Tim Urbanowicz sees investors hunting the next AI wave

Tim Urbanowicz, chief investment strategist at Innovator from Goldman Sachs Asset Management, is looking past the obvious hype cycle of the AI boom. In the CNBC segment, he tackles where investors may find the next “big wave” for AI trade. The punchline is not that everyone should buy the same headline stock. It is that “AI” is evolving fast enough that different parts of the stack can move differently at different times, and investors tend to pay the highest prices when they ignore that sequencing.

That idea is the core of Urbanowicz’s pitch: the AI trade is not a single moment, it is a series of waves. The first wave, widely visible, is often tied to the big beneficiaries of AI adoption, the kind of names that dominate conversations and fund flows. But once a theme becomes a crowded consensus, the risk is that investors keep piling into the same narrow set of beneficiaries. Urbanowicz’s focus on where the next wave could be signals a more selective mindset, the kind that tries to understand what changes next in demand, business models, and capital allocation rather than simply extrapolating what worked yesterday.

Why does this matter for executives and boards, not just traders? Because “AI strategy” inside a company is no longer just a product roadmap question. It is also a capital market question. Investors increasingly decide whether your AI plan is credible not only by what you build, but by how it maps to measurable spending and adoption. When the market rotates from one subset of AI winners to another, the beneficiaries of those rotations can attract more funding, better partnerships, and cheaper capital. The losers, even if they are making progress, can get mispriced because they are tied to the wrong part of the narrative at the wrong time.

There is also a second-order implication for portfolio construction. If investors are actively hunting for the next wave, that means relative winners can change even when the overall AI theme stays strong. In practice, that can tighten correlations in the short run and then loosen them later, depending on what the market decides is “next.” For decision-makers, that shows up as volatility around sectors, business models, and geographies that may not be obvious to non-investment teams. Corporate leaders who understand this earlier can plan more effectively for external funding cycles and partnership opportunities.

Now, set against all that market psychology is regulation. AI investment does not happen in a vacuum, and regulatory frameworks can re-rank opportunities. Data rules, model governance expectations, and safety requirements can all affect timelines. Even without naming any specific regulator in this particular segment, the broader context is that compliance and governance can become part of the cost structure and competitive advantage, not just a legal checkbox. When regulation tightens, the market can shift toward companies that can operationalize compliance faster. When guidance clarifies what is allowed, it can unlock new demand. That regulatory swing is a real driver of the “next wave” concept: it changes who wins and when.

The Innovator platform, connected to Goldman Sachs Asset Management, positions Urbanowicz to talk in terms that investors actually trade on: theme evolution, risk management, and relative opportunity. That matters because the AI boom has attracted capital at a scale that can make timing and narrative discipline unusually important. When everyone is trying to buy the same future, you can get price efficiency in the popular names, meaning future returns become harder. Investors then start to look for earlier-stage beneficiaries of the next step, or for infrastructure and enabling layers that are less visible in the day-to-day news.

For executives who want a practical takeaway, the strategic stake is simple: the market may not reward “AI” as a single label forever. It tends to reward the parts of AI that are closest to real spending and scalable adoption, and it rotates as that spending matures. Boards should assume investors will keep searching for the next wave, which implies diligence risk for companies that only have broad messaging. If your AI strategy is not clearly tied to measurable value creation and adoption pathways, you may struggle when the market shifts from one wave to the next.

So the value of Urbanowicz’s framing is not a stock tip. It is a discipline: think in waves, not monoliths. If the next “big wave” in AI trade is about where and how value shows up next, then your job as a leader is to make sure your company is building something that can survive the rotation, not just benefit from the initial rush.