How AI and Investment Are Driving the US Productivity Boom

The US Productivity Revolution: AI, Investment, and Market Shifts Driving the Next Economic Boom

For over a decade, the US economy remained stuck in a productivity trap characterized by low productivity, where growth depended upon cheap credit and financial engineering rather than real efficiency gains. From 2004 to 2019, labor productivity averaged only 1.6% per year, far below the level necessary for sustained wage growth and economic expansion. This epoch, however, seems to be passing away.

Now, we are entering into a structural productivity boom fueled by advancements in AI, record capital investment, and a new wave of business formation. Productivity growth rebounded, with a strong 2.7% in 2023, the highest since the dotcom boom of the late 1990s when personal computers and internet gained prominence, revolutionizing the economic output.

Falling in the wake of this positive productivity story are rising labor costs, a changing Federal Reserve policy, and tightening labor market conditions. In Q4, unit labor costs increased by 3.0%, and hourly compensation rose at an annualized rate of 4.2%, implying that companies must continue investing in AI and automation to protect their margin. Simultaneously, the Federal Reserve is revisiting its view, as higher productivity generally would increase the neutral policy interest rate, meaning rates could remain elevated longer than the markets expect.

The central inquiry is whether this productivity rise is cyclical or structural. Should AI adoption speed up as anticipated, this might be the initiation of a transformation in the economy lasting several decades, akin to what occurred with the internet boom of the 1990s that paved the way for skyrocketing wages, elevated corporate profits, and protracted economic expansion.

From Stagnation to Acceleration: The US Productivity Surge

After the global financial crisis, in most periods, US productivity growth averaged just 1.6% per annum- very much lower than before historical achievement levels. The last productivity boom happened between the years 1994 to 2004, which resulted in a productivity increase at the annualized rate of 2.8% owing to the phenomenal mainstreaming of the internet, personal computing, and automation. The current revolution is transforming productivity with gains in three structural forces accelerating it:

A record-breaking surge in business formation, reversing a 40-year decline in entrepreneurship.
A wave of capital investment as businesses modernize outdated infrastructure and adopt AI.
Deregulation, reducing barriers to entry and accelerating business expansion.

Business Formation:

The "startup deficit" that characterized the years from the 1980s to the 2010s, hindering innovation and competition, has now turned around. High-propensity business applications, those with a strong likelihood of evolving into employer firms—are currently 37% higher than they were before the pandemic. Even more significantly, new business formation is taking place in high-productivity sectors, especially within technology and AI-driven industries, which is enhancing efficiency gains.

Capital Investment:

Since 2020, the US has seen a three-phase wave of capital deepening:

Phase 1 (2020-2022): Digital Transformation → Software became an investment for companies amounting to annual growth of 13%. Cloud adoption, automation, and integration of AI were accelerated by firms.
Phase 2 (2022-2023): Infrastructure Expansion → A surge in spending was observed in manufacturing and data center expenditures with the support of the CHIPS Act and Inflation Reduction Act, creating a boom for corporate buyouts of $550 billion and record levels of capital expenditure.
Phase 3 (2024-Present): Equipment Modernization → Factories and data centers that had been set up two years back are now being tooled up with AI-driven automation for sustained productivity increases.

Deregulation & Labor Markets:

Easing deregulation has made it easier to expand business in areas such as financial services, healthcare, and energy. Meanwhile, the market for labor is changing:

Initial claims for unemployment benefits rose to 219,000 in the first week of February from 208,000 the week before, and continued claims rose to 1.86 million.
This indicates a withdrawing of companies from hiring and a shift toward automation, reaffirming the trend to an AI-directed productivity.

With tighter labor markets, rising wages, and AI - companies will soon have leverage against competition when integrating AI and automation within those walls, further accelerating long-run productivity growth.

AI: The Ultimate Productivity Accelerator

AI is the biggest wildcard in this productivity revolution. Its recent breakthroughs, such as OpenAI's o1-preview and o1-mini models, testify to AI's evolution from a knowledge-retrieval system into a complex reasoning system, capable of performing what humans would describe as real decision making. This was one of the purposes for which OpenAI has built its latest models: to maximize the abilities of the Chain-of-Thought (CoT) model that dissects complex problems into a sequenced, stepwise solution for comparative performance and reliability in STEM fields.

Data from OpenAI’s latest AI benchmark tests underscores the rapid advancement in AI capabilities:

GPT-4o achieved 81% on AP Calculus and 83.3% on AP Chemistry, surpassing previous models.
o1-preview outperformed GPT-4o in problem-solving tasks by 10-15%.
AI models are now closing the gap with expert human performance in fields like law (LSAT: 95.6%), coding (Codeforces: 78.3%), and physics (AP Physics 2: 69.7%).

The rapid improvement in AI suggests it could soon occupy the central stage in decision making, automation, and business optimization-and translate into very high productivity improvement across industries.

However, challenges remain. The cost to train frontier AI models has scaled from about $40 million to $400 million within the last five years, and estimates are that even more than $1 billion will have to be spent on the next-generation AI model. While big companies like Nvidia, Microsoft-jointly and OpenAI dominate AI infrastructure, enterprise-scale end adoption of the AI technology is still in the second phase of its evolution.

The productivity payoff of AI will most probably take the shape of the internet boom, as penetration and climbing toward critical mass have often taken time, but once there, it tends to transform entire industries.

The Market and Economic Implications of Rising Productivity

For investors and policymakers, the productivity revolution carries major implications. Historically, higher productivity growth has been associated with stronger equity market returns, rising real wages, and changes in Federal Reserve policy.

Interest Rates and the Federal Reserve's Dilemma
- The neutral policy rate is raised by productivity growth, which could result in interest rates staying higher for longer than the markets anticipate.
- The Fed's long-term GDP growth projections are still between 1.8% and 2.0%, although persistent productivity gains may raise that range.
- As of early 2025, bond markets are pricing in rate cuts later in the year, but if productivity growth continues accelerating, the Fed may be forced to maintain higher rates.

Corporate Earnings and Equity Market Impact
- Historically, productivity cycles have been associated with returns on the S&P 500 that are above average. Efficiency-driven profit growth propelled the S&P 500's 417% decade-long increase during the tech boom of the 1990s.
- Businesses who are at the forefront of automation, AI adoption, and infrastructure upgrading stand to gain the most.
- As a sign that markets are starting to factor in long-term efficiency benefits, the equity risk premium (ERP) has already dropped below its long-term average.

The Labor Market’s Shifting Dynamics
- In Q4, unit labor costs climbed 3.0% on a quarterly basis, while hourly compensation jumped to 4.2%, indicating increasing wage pressures.
- The Fed's wage tracker indicates that companies must rely on automation to sustain profit margins, as evidenced by a 3.9% year-over-year increase in Q4 compared to a 4.1% increase in Q3.
- While digital, artificial intelligence, and capital-intensive industries appear to benefit, sectors with a high labor dependency and limited automation potential may encounter challenges.

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