THE BREW – APRIL 2024

AI's Economic Ripple Effect: How Four Phases of Adoption May Shape Industries and Markets

We can think of the adoption of artificial intelligence (AI) into four phases, and these four phases weave together a variety of industries, transforming the fabric of the global economy. Each phase of AI adoption not only marks a step forward in technological integration but also highlights the sectors primed to benefit from these advancements. The journey of AI adoption across industries, as delineated in the "Next Phases of the AI Trade," by Goldman Sachs (published April 16th, 2024), illustrates a transformative path from foundational technologies to broad economic impacts.

Is this a repeat of the Dot Com Bubble?

To start, some pundits have said that the AI boom is a repeat of the early days of the internet bubble and, as a result, that the market as a whole is overvalued. We note that the market is expensive by some measures, but it pales in comparison to the overvalued markets of the late 1990s or during the Covid mania, replete with meme stocks. Consider the nearby graph which illustrates the price to earnings (P/E) ratio of the Russell 3000 index, which is a very broad measure of about 3,000 stocks. The P/E ratio of the Russell 3000, while above that of recent years, is still well below that of the Dot Com Bubble or Covid Mania peaks.

The Four Phases of AI Adoption

AI adoption can be broken down into four phases, each with its unique focus and impact on various industries.

Phase 1: Foundational Technologies

• Semiconductors (e.g., Nvidia)
• Hardware manufacturers (servers and storage solutions)
• Emphasis on computational needs and data-intensive operations

Phase 2: Infrastructure Expansion

• Semiconductors and electronics (specialized chips and components)
• Cloud computing (Amazon, Microsoft, Google)
• Utilities (reliable power sources)
• Data centers and real estate (storage and management solutions)
• Telecommunications (5G technology)
• Renewable energy providers (sustainable power)
• Security (endpoint security)
• Servers and networking (hardware and equipment)

Phase 3: Revenue Enhancement through AI Integration

• Software and IT services (new applications and services)
• Healthcare (diagnostics, personalized medicine, patient management)
• Financial services (algorithmic trading, fraud detection, personalized banking)
• Retail and e-commerce (AI-driven analytics, personalized shopping experiences)
• Media and entertainment (content recommendation algorithms)
• Automotive industry (ADAS, autonomous driving)

Phase 4: Productivity and Efficiency Gains

• Manufacturing (automation, predictive maintenance)
• Professional services (automation of routine tasks)
• Transportation and logistics (routing optimization, supply chain management)
• Agriculture (precision farming, crop management)
• Energy sector (predictive maintenance, grid management)
• Education and training (personalized learning experiences)
• Healthcare delivery (streamlined hospital operations)

Understanding these phases and the industries involved can provide insights into AI's current impact and future trends, guiding investment decisions and portfolio construction. Consult with your SEIA advisor to help navigate this evolving landscape in the context of your investment portfolio and financial plan

To learn more about this topic, read the full article here!

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