Is now a good time to put more money into AI stocks?

Key Concepts

• AI Thematic Investing: The strategy of investing in companies involved in the development, infrastructure, and power requirements of Artificial Intelligence.
• Risk-On Sentiment: A market condition where investors are willing to take on more risk due to optimism, often triggered by geopolitical de-escalation.
• Data Center Infrastructure: The physical and electrical requirements (power grids, real estate, connectivity) necessary to support AI computing.
• SaaS (Software as a Service) Disruption: The risk posed to traditional software companies by AI models that can perform tasks more efficiently.
• Proprietary Customer Data: Unique, non-public information held by companies that can be used to train AI models or gain competitive insights.
• KUSMA (Canada-United States-Mexico Agreement): The trade agreement currently undergoing renegotiations, contributing to corporate uncertainty and cautious hiring.

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Market Overview and Geopolitical Impact

The S&P 500 reached all-time highs driven by a "risk-on" market sentiment. This optimism is primarily attributed to reports of a potential peace deal between the U.S. and Iran, which includes the gradual reopening of the Strait of Hormuz and the lifting of blockades on Iranian ports. While geopolitical tensions have caused market volatility over the past few months, the current rebound is supported by strong corporate earnings, particularly within the U.S. technology sector.

The AI Thematic and Infrastructure Buildout

Kelsey Keane, Director of Equity Capital Markets at National Bank of Canada, highlights that the AI boom is driving significant capital flows into thematic ETFs. The growth potential of AI is currently viewed as vast, extending beyond pure software plays into essential support sectors:

• Energy and Power: Data centers require massive amounts of electricity. Companies capable of feeding this power demand are seen as primary beneficiaries.
• Infrastructure and Real Estate: There is a focus on the physical development of data centers, which requires undeveloped land and integration into existing power grids.
• Canadian Market Context: Canada is positioned to benefit due to its energy-rich equity market, with potential for data center expansion in regions like Calgary.

Sector Winners and Losers

• Winners: Companies involved in the "picks and shovels" of the AI revolution—specifically energy, infrastructure, and real estate firms that provide the physical foundation for AI connectivity.
• Struggling Sectors: Traditional SaaS businesses are facing disruption. AI models are increasingly capable of performing tasks previously handled by these software services, leading to concerns that current valuations for some SaaS companies may be overdone.
• The "Data" Differentiator: Keane notes that not all software companies are equally vulnerable. Those possessing proprietary customer data—information that provides unique insights into consumer trends—are more likely to survive or become targets for consolidation.

Macroeconomic Outlook and Labor Markets

The discussion touched on the current state of the labor market and broader economic uncertainty:

• Hiring Trends: Hiring in both Canada and the U.S. remains slow as companies delay major investment decisions due to economic ambiguity.
• Trade Uncertainty: The upcoming KUSMA renegotiations are identified as a significant factor contributing to corporate hesitation, particularly within the automotive sector.
• Central Bank Policy: Market participants are closely monitoring upcoming employment data to gauge potential "knock-on effects" for future central bank interest rate policies.

Synthesis and Conclusion

The market is currently balancing geopolitical optimism with a structural shift toward AI-driven infrastructure. While the technology sector leads the rally, the most sustainable growth is being identified in the physical and energy-related sectors required to support AI. Investors are advised to differentiate between software companies that are easily replaced by AI and those that hold high-value, proprietary data. Furthermore, macroeconomic caution remains high, with trade negotiations and labor market stability serving as critical variables for future market performance.