AI Fuels New Business Formation and Economic Expansion, Not Just Job Loss

The AI Dividend: Unpacking the Hidden Economic Engine Beyond Job Loss Fears

This conversation with Torsten Slok, Peter Tchir, and Ed Al-Hussainy reveals a profound disconnect between prevailing anxieties about AI-driven job displacement and the observable macroeconomic realities. The core thesis is that while fears of a "white-collar washout" are vocalized, the actual data points to a robust surge in new business formation and a dynamic labor market fueled by AI investment and significant government spending. The non-obvious implication is that AI, rather than being a net job destroyer, is acting as a powerful catalyst for economic expansion, creating more opportunities than it eliminates, particularly in sectors supporting this build-out. This analysis is crucial for business leaders, policymakers, and investors who need to understand the true drivers of future economic growth and navigate the evolving landscape of work. Ignoring this underlying engine could lead to misallocated resources and missed opportunities.

The Unseen Engine: AI as a Job Creator, Not Just a Destroyer

The prevailing narrative around artificial intelligence often centers on job losses, painting a grim picture of widespread displacement, particularly in white-collar professions. However, this conversation with Torsten Slok, Peter Tchir, and Ed Al-Hussainy offers a sharply contrasting perspective, grounded in macroeconomic data and a systems-level view of economic activity. The core argument presented is that AI is not merely an efficiency tool leading to fewer jobs, but a powerful engine for new business creation and overall economic expansion.

Torsten Slok, Chief Economist at Apollo Global Management, directly challenges the doomsayers. He points to exploding numbers of new businesses being created, citing surveys from the Census Bureau and data from Stripe showing a surge in solo founders. This isn't just about individuals starting one-person operations; Slok argues that a significant portion of these new ventures will inevitably lead to job creation.

"So there's a lot of new businesses that are formed. Yes, some of them will probably only be one employer, namely the founder, but a lot of these businesses will also result in a lot more jobs. So it's not only about the displacement that there might come at some micro levels, it's much more about the aggregate where we have a significant increase in the number of new businesses that are formed."

-- Torsten Slok

This macro perspective is critical. While individual roles might be automated or transformed, the aggregate effect, according to Slok, is a net positive for employment. He contrasts this with the predictions of layoffs and disappearing entry-level jobs that were prevalent even a year ago, highlighting the resilience of the labor market, evidenced by consistently strong weekly job numbers from ADP and low jobless claims. The AI spending boom, coupled with substantial government initiatives like "the one big beautiful bill," creates a unique economic environment characterized by both strong growth and upward inflationary pressures. This isn't a typical cycle; it's an economy on fire, driven by factors largely insensitive to interest rate hikes.

The Data Center Build-Out: A Trojan Horse for Broad Economic Growth

Peter Tchir, Head of Macro Strategy at Academy Securities, offers a complementary view, focusing on the tangible build-out required to support AI. He emphasizes the massive job creation stemming from the construction and operation of data centers. This includes not only the direct employment in the chip industry and construction but also the broader ecosystem: logistics, manufacturing, and energy generation.

"One is, I think people underestimate the data center and AI, just the amount of jobs that are being created to build this out, right? The chip industries going like gangbusters, the construction business going extremely well, the electricity generation business going phenomenally well."

-- Peter Tchir

Tchir’s analysis reveals a cascading effect. The immediate demand for building these AI infrastructures creates a surge in employment across various sectors. While he acknowledges that the operational phase of a data center might not employ as many people as its construction, the initial build-out phase provides a significant, sustained boost to the economy. This challenges the simplistic view that AI's impact is solely about automating existing tasks; it’s also about creating entirely new industries and the jobs that support them. This is where the conventional wisdom fails: it focuses on the displacement within existing structures rather than the creation of new ones.

The Political Minefield: Where Sentiment Could Derail Progress

Ed Al-Hussainy, Global Rates Strategist at Columbia Threadneedle, introduces a crucial systemic risk: political intervention. While the economic fundamentals driven by AI and government spending appear strong, Al-Hussainy warns that politicians could latch onto negative sentiment regarding electricity usage or job displacement. This could lead to policies that stifle the very growth drivers discussed.

The idea of Universal Basic Income (UBI) is raised as a potential political response, driven by a desire to share the profits generated by AI. While Slok expresses discomfort with the concept, he acknowledges its growing presence in political discourse, particularly in countries like South Korea. The concern is that this sentiment could become a significant election issue, leading to policies such as corporate tax hikes, which could derail the current economic trajectory.

"The biggest threat right now in the US to AI data center story, it's not the use, it's not corporations not wanting it. It's politicians trying to latch onto some of this negative sentiment either about the electricity generation, the electricity usage or the jobs."

-- Torsten Slok

This highlights a critical downstream consequence: the potential for policy decisions, driven by public perception rather than economic data, to disrupt a powerful growth cycle. The "horse and buggy" analogy, while often used to illustrate technological disruption, might be insufficient here. Tchir suggests that AI could be different, potentially targeting a broader range of human jobs in a way previous technological shifts did not. The risk is that political actors, responding to anxieties about AI's impact, might implement measures that prematurely curb investment and innovation, thereby sacrificing long-term economic benefits for short-term political gains. This presents a unique challenge where immediate discomfort with the pace of change could lead to policies that create lasting economic disadvantage.

Key Action Items

• For Business Leaders:
  • Immediate Action: Re-evaluate hiring strategies to focus on roles supporting AI infrastructure build-out (e.g., construction, logistics, energy, specialized IT) rather than solely on traditional white-collar roles.
  • Immediate Action: Invest in employee reskilling and upskilling programs to align workforce capabilities with emerging AI-driven industries.
  • Longer-Term Investment (12-18 months): Develop strategies to leverage AI for new business formation and service creation, anticipating increased consumer and business demand fueled by broader economic growth.
• For Policymakers:
  • Immediate Action: Focus on clear communication to counter negative AI sentiment, emphasizing its role as an economic growth driver and job creator, supported by data.
  • Immediate Action: Streamline regulatory processes for energy generation and data center development to facilitate the AI infrastructure build-out.
  • Longer-Term Investment (18-24 months): Explore policy frameworks that encourage AI innovation and investment while proactively addressing potential societal impacts, rather than reacting with broad, potentially stifling measures like UBI or punitive taxation.
• For Investors:
  • Immediate Action: Analyze subcomponents of the stock market to identify companies benefiting from the AI infrastructure build-out beyond the direct AI software/hardware providers.
  • Immediate Action: Monitor inflation expectations and bond yields closely, considering the "higher for longer" energy price theme and its potential impact on monetary policy.
  • Longer-Term Investment (12-24 months): Position portfolios to benefit from sectors experiencing reindustrialization and infrastructure development driven by AI demand and government spending.