CONTRIBUTORS
Stephen Dover, CFA
Chief Market Strategist,
Head of Franklin Templeton Institute
Kate Lakin
Director of Research and Portfolio Manager–US Research Strategies
Putnam Investments
After impressive returns in 2023 and 2024, technology stocks, especially top artificial intelligence (AI) infrastructure companies, experienced some losses and high levels of volatility in 2025. In this era of unprecedented technological innovation and heightened macroeconomic and policy uncertainty, volatility is expected. But we believe this backdrop also creates an incredibly fertile hunting ground for investors seeking to take advantage of market dislocations.
I sat down with Kate Lakin, Director of Research and Portfolio Manager of US Research Strategies at Putnam Investments, to discuss where her team sees long-term investment opportunities.
Kate, it’s been a turbulent start to the year for AI-exposed technology companies. Where do AI technology companies stand now?
In our analysis, fundamentals remain solid for now. Year-to-date, when AI-exposed technology companies underperformed or outperformed valuation (price-earnings ratio) drove changes rather than any fundamental deterioration. Consensus earnings estimates for the broader AI basket of technology stocks have remained relatively stable, demonstrating resilience so far in 2025. However, the market is forward looking, and investors have begun to consider potential uncertainties for 2026 and beyond.
Why are some investors hitting the pause button when it comes to AI investing?
We track several factors—both idiosyncratic and macroeconomic/policy—that have contributed to investors’ growing caution about the sustainability of AI-investment levels.
AI-industry-specific factors include China’s DeepSeek’s efficient model innovation, slower-than-anticipated enterprise AI adoption, increased scrutiny of the economics behind large-language models, and growing signals that major players are reassessing optimal levels of capital investment.
A shifting political policy landscape also further complicates these evolving industry-specific dynamics. This has created significant disruption and uncertainty both for the AI-infrastructure market and the broader economy. Examples include increased restrictions on chip shipments to China—driven by national security concerns—as well as fluctuating tariff levels across a variety of end markets, including AI-exposed infrastructure. This does not help businesses gain the confidence needed to make the long-term investments required to build and deploy AI. So, while the development and deployment of AI may be secular in nature, it is not immune to fluctuations in the broader economy.
Does AI continue to offer compelling investment opportunities?
In our opinion, there remains undeniable potential in AI, which is poised to transform and reshape both personal and professional realms. We expect to see AI use cases and monetization methods proliferate in the coming months and years. According to the World Economic Forum, within the next five years, most organizations are expected to reimagine every part of their value chains using AI technologies.1 We are encouraged by the incredible growth at a number of companies in this space—proving that AI technology can disrupt even the largest and most established companies and industries. We note that over 100 mobile-first companies that were founded after the first iPhone in 2007 have exceeded a US$1 billion market capitalization.2 So while it makes sense to proceed with caution for many of the reasons noted above, we remain enthusiastic about the long-term opportunities and expect many AI beneficiaries (and losers) to emerge across multiple sectors both within technology and beyond.
What are some key areas of focus when researching AI stocks?
The daily, and even hourly, shifts in trade policy can dominate headlines—and in our view they exert a larger near-term impact on markets than the underlying long-term AI investment trends. We focus on the companies’ strategic rationale and subsequent expected outcomes of the administration’s policy agenda.
Equally, we conduct rigorous, ongoing analysis of AI adoption and deployment across both consumer and enterprise channels. We evaluate the return on investment on scaled application rollouts, track investment commitments from major hyperscalers (or companies that provide cloud computing and data management services to organizations) and monitor emerging preferences in compute-infrastructure design. By integrating these insights, we aim to filter out transitory distractions and identify the companies we believe are best positioned to lead over the next market cycle.
Early AI gains have been concentrated in a limited set of infrastructure providers, but the global AI infrastructure market size was estimated at US$35.42 billion in 2023 and is projected to grow at a compound annual growth rate of 30.4% from 2024 to 2030.3 In a market that has developed at such a staggering pace, with the search still on for the right economic model, fundamental research is critical. We believe the recent market turmoil is creating attractive dislocations for investors in AI who are able to stay focused on the process and ignore the elevated noise levels.
Endnotes
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Source: “What the AI transformation of consumer industries can teach others.” World Economic Forum. April 18, 2025.
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Source: Putnam research.
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Source: “AI Infrastructure Market Size, Share & Trends Analysis Report By Component (Hardware, Software, Services), By Technology (Machine Learning, Deep Learning), By Application, By Deployment, By End-user, By Region, And Segment Forecasts, 2024 – 2030.” Grand View Research.
WHAT ARE THE RISKS?
All investments involve risks, including possible loss of principal.
Equity securities are subject to price fluctuation and possible loss of principal.
Investment strategies that incorporate the identification of thematic investment opportunities, and their performance, may be negatively impacted if the investment manager does not correctly identify such opportunities or if the theme develops in an unexpected manner. Focusing investments in the information technology- and/or technology-related industries carries much greater risks of adverse developments and price movements in such industries than a strategy that invests in a wider variety of industries.
Any companies and/or case studies referenced herein are used solely for illustrative purposes; any investment may or may not be currently held by any portfolio advised by Franklin Templeton. The information provided is not a recommendation or individual investment advice for any particular security, strategy, or investment product and is not an indication of the trading intent of any Franklin Templeton managed portfolio.
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