Samer Choucair: AI Is No Longer Just a Growth Story It Is a Test of the Cost of Capital
Investment leader Samer Choucair said mounting warnings over the risks associated with artificial intelligence are beginning to reshape the global investment equation, arguing that markets can no longer treat AI purely as a technology growth story. Instead, it is increasingly becoming an economic transformation that requires investors to reprice risks related to governance, regulation, labor markets, and the cost of capital.
Samer Choucair said Bill Gates’ warnings come at a sensitive stage in the technology investment cycle, as governments and companies compete globally for data centers, semiconductors, energy capacity, and digital infrastructure.
“The key question for investors is no longer only who has the best model,” Choucair said. “The question is who will bear the economic cost of the transition if jobs are displaced faster than public policy can absorb the shock.”
Choucair explained that artificial intelligence differs from previous technology cycles because of how quickly it can expand into a broad range of cognitive tasks across industries including law, customer service, software development, medicine, and manufacturing.
That creates substantial opportunities for productivity gains, but it also introduces potentially significant risks associated with the restructuring of labor markets.
Samer Choucair noted that Gates has warned that some jobs could disappear permanently if governments fail to respond effectively. He has also highlighted risks linked to cybersecurity, fraud, deepfakes, biological threats, and the continued development of increasingly advanced AI systems.
“Institutional capital has traditionally priced cyclical risks through interest rates, inflation, and profit margins,” Choucair said. “Now it must also price the possibility that the social cost of artificial intelligence becomes a capital cost through taxation, regulation, and restrictions on labor displacement across entire industries.”
Choucair stressed that this does not mean investors should retreat from artificial intelligence. Instead, the investment universe within AI should be reclassified more carefully, distinguishing between companies that can demonstrate measurable productivity improvements and those whose investment thesis depends primarily on a broad narrative of replacing human labor.
The distinction could become increasingly important as governments begin confronting the fiscal and social consequences of labor-market disruption.
If rapid AI adoption leads to significant job displacement, policymakers may respond through new taxes, stricter labor regulations, mandatory retraining programs, tighter compliance requirements, or restrictions governing the deployment of autonomous systems in sensitive sectors.
For investors, those interventions could directly affect margins, valuations, and required rates of return.
Returns May Shift Toward Companies That Manage the Transition at Lower Cost
Choucair said investment opportunities may gradually shift away from companies focused exclusively on accelerating automation toward businesses that help economies manage the transition more effectively.
That could include companies involved in workforce reskilling, cybersecurity, regulatory compliance, productivity software, and systems that enable businesses to integrate artificial intelligence without creating unacceptable operational, legal, or social risks.
In this environment, the strongest AI investment opportunities may not necessarily belong to the companies promising the greatest degree of labor replacement. They could instead emerge among businesses capable of translating artificial intelligence into measurable productivity while reducing the economic and regulatory friction surrounding adoption.
The cost of transition therefore becomes part of the investment case.
A company that can demonstrate higher output, lower operating costs, stronger cybersecurity, regulatory compliance, and a credible approach to workforce transformation may deserve a different valuation than one whose economics depend almost entirely on eliminating labor costs as quickly as possible.
That distinction is particularly important for institutional investors with long investment horizons. Pension funds, sovereign wealth funds, private-equity firms, and large asset managers must consider not only the immediate productivity upside of artificial intelligence but also the secondary effects that could eventually influence taxes, regulation, consumption, employment, and political risk.
Samer Choucair said the investment framework for AI in 2026 therefore needs to expand beyond traditional technology metrics such as model performance, computing capacity, user growth, or revenue expansion.
Investors will increasingly need to assess which businesses can deploy artificial intelligence efficiently while managing the broader costs created by that deployment.
“Economic trends in 2026 suggest that returns will increasingly shift away from those who simply promise greater speed and toward those who can manage the transition at a lower cost,” Samer Choucair concluded. “Investment funds that understand this shift will treat artificial intelligence as economic infrastructure, not as a temporary technology theme.”