5 Stocks for the Next Triple Digit AI Boom

Key Concepts

• AI Profit Drivers: Five key areas identified as significant sources of profit and growth within the Artificial Intelligence sector.
• The Bazooka: Massive capital expenditure by major tech companies on AI data centers.
• The Crunch: A significant supply-side shortage of energy required to power AI data centers.
• Resources: The critical raw materials needed for AI development, with a focus on domestic supply chains.
• Application Layer: The development and deployment of AI software and services that enhance productivity and quality of life.
• Embodiment/Physical AI: The integration of AI into the physical world through robotics, self-driving cars, and automation.
• Capex (Capital Expenditure): Spending by companies on acquiring or upgrading physical assets like property, industrial buildings, and equipment.
• Gawatt: A unit of power equal to one billion watts.
• Nano Reactor: A small-scale nuclear reactor designed for rapid deployment.
• Rare Earths: A group of 17 chemical elements with unique properties essential for many modern technologies, including AI.
• Magnets: Crucial components in AI hardware, particularly for actuators in robots.
• Actuators: Devices that convert energy into motion, essential for robotic movement.
• Ascending Triangle Formation: A bullish chart pattern in technical analysis, suggesting a potential breakout to higher prices.

AI Profit Drivers and Investment Opportunities

This discussion, featuring Luke Lango from Investor Place at the Stanbury Alliance conference, outlines five key profit-driving forces within the Artificial Intelligence (AI) market and highlights specific stocks poised to benefit. The overarching theme is that AI is not just a future concept but a present-day profit engine, with significant investment flowing into specific areas.

1. The Bazooka: AI Data Centers and Infrastructure

Main Topic: The immense capital investment by tech giants into building AI data centers.

Key Points:

• Major companies like Amazon, Microsoft, Alphabet, and Meta are investing heavily in AI data centers.
• This investment is described as a "bazooka" of billions of dollars being fired into a specific market corner.
• Estimated capital expenditure (capex) from these companies for AI data centers is projected to be $500 billion over the next 12 months, potentially climbing towards $1 trillion by 2028-2029.
• The profit opportunity lies with companies providing components and supplies for these data centers.

Example/Case Study:

• Nebius Group (Ticker: NBIS): Described as the "Ferrari of AI cloud compute."
  • Details: Nebius specializes in AI-only data centers, unlike larger providers that offer multi-purpose cloud services. This specialization caters directly to the high demand for AI-specific computing power.
  • Growth: Despite significant recent growth (revenues up 500% year-over-year last quarter), Nebius is still considered a small and relatively unknown company compared to giants like Microsoft or even other specialized players like Coreweave.
  • Outlook: Lango believes Nebius has substantial runway for growth over the next 12-24 months due to its specialized focus and rapid revenue expansion in a high-demand market.

2. The Crunch: Energy for AI Data Centers

Main Topic: The massive energy demand created by AI data centers and the resulting supply-side crunch on power grids.

Key Points:

• The first profit driver (data centers) directly leads to the second: the need for enormous amounts of energy.
• Existing power grids are already strained, and the addition of numerous AI data centers exacerbates this.
• Data/Statistics: Bank of America estimates a 36-gigawatt (gW) energy shortage on the US grid by 2028, a mere three years away.
• Companies that can fill this energy gap will have significant pricing power and profit potential.

Example/Case Study:

• Oaklo (Ticker: OKLO): A nano-reactor company positioned as a solution to the energy crunch.
  • Details: Oaklo is developing nuclear nano-reactors, which are considered ideal for AI data centers due to their clean, 24/7, and cost-efficient (once built) power generation.
  • Methodology: Unlike traditional large reactors that take 10 years to build, Oaklo's nano-reactors can be operational within 12-24 months from groundbreaking. This rapid deployment is crucial given the imminent energy shortage. The strategy is to build data centers and nano-reactors in tandem.
  • Validation: Oaklo has broken ground on its first nano-reactor in Idaho. The US Energy Secretary, Chris Wright, aims for three nano-reactors to be operational by July 4th, 2026.
  • Notable Statement: Sam Altman, CEO of OpenAI, was formerly the chairman of Oaklo, stepping down to allow the company to pursue broader data center contracts.
  • Outlook: Lango views Oaklo as a "lottery ticket" with the potential to become the energy backbone of AI, suggesting a valuation far exceeding $100 billion, potentially reaching $1 trillion.

3. Resources: Domestic Supply Chains for AI

Main Topic: The strategic importance of securing domestic sources of raw materials essential for AI development.

Key Points:

• AI chips, devices, software, and data centers all require significant raw resources.
• Currently, many of these resources are sourced from China, the US's primary competitor in the AI race.
• The US government, under the Trump administration, is making strategic investments to build a national domestic supply chain for AI raw resources.
• This initiative is seen as a critical move to reduce reliance on a geopolitical rival.

Examples/Case Studies:

• Government Investments: The White House has invested in four companies: Intel, MP Materials, Trilogy Metals, and Lithium Americas.
• Impact on Stocks: These investments have led to significant rallies:
  • Intel: Up 80-90% in two months.
  • MP Materials: Jumped 200% in two months.
  • Trilogy Metals: Increased 200% in a single day.
• Argument: Lango argues that these investments are just the beginning, with the "president's portfolio" likely expanding to 10-15 companies, offering opportunities for substantial gains.

Specific Stock Recommendation:

• USA Rare Earths (Ticker: USAR): Identified as a potential next recipient of government investment.
  • Details: Rare earths are crucial for AI, especially for humanoid robots and physical AI devices, as they are used in magnets.
  • Rationale: China controls 90% of the rare earths market. The US needs multiple domestic suppliers beyond MP Materials. USAR is the next largest rare earths miner with a project in the US focused on producing magnets.
  • Outlook: Lango believes USAR is likely to receive significant investment from the current administration, potentially leading to rapid stock appreciation.

4. Application Layer: AI Software and Services

Main Topic: The development and deployment of AI software and services that create tangible value and improve productivity.

Key Points:

• This layer focuses on the practical uses of AI, such as automating tasks (taxes, movie production, photo editing) and creating real-world value for companies and individuals.
• These applications make AI useful and profitable.

Example/Case Study:

• Tempest AI (Ticker: TEM): Focuses on healthcare AI.
  • Details: Tempest AI is developing personalized healthcare solutions using AI. They are partnered with major institutions like the Mayo Clinic.
  • Argument: Lango considers healthcare AI to be the "last undervalued and undiscovered corner of the AI boom."
  • Rationale: Healthcare is currently inefficient and in need of improvement, which AI can provide. Personalized healthcare, tailored to individual needs, is a key trend that Tempest AI's technology enables.
  • Technical Analysis: The stock has shown an ascending triangle formation, with a technical ceiling around $100, suggesting a potential breakout to $200-$300.
  • Regulatory Environment: While healthcare has regulatory hurdles, Lango notes that the White House is actively cutting red tape for AI development in areas like drug discovery and testing, which should accelerate growth for companies like Tempest AI.

5. Embodiment/Physical AI: AI in the Real World

Main Topic: The integration of AI into the physical world through robotics, self-driving cars, and automation.

Key Points:

• This represents AI becoming tangible and interacting with the real world.
• Examples include self-driving cars (Waymo), warehouse automation (Symbiotic technology at Walmart), and humanoid robots.
• This physical embodiment is seen as an "aha moment" for AI, similar to the iPhone's impact on the internet, leading to exponential growth.
• The US is currently behind China in humanoid robots, making it a critical area for development.

Examples/Case Studies:

• Tesla's Optimus Project:
  • Details: Elon Musk's initiative to develop humanoid robots.
  • Progress: The Optimus robot has been demonstrated serving popcorn at a Tesla diner.
  • Support: The project has support from Nvidia (a key chip provider for robots), the White House (through investments in companies like MP Materials, which supply components for robots), and a strong internal team at Tesla.
  • Outlook: Lango is highly optimistic about Optimus's success, believing it will be a major driver for Tesla's stock, even amidst challenges in EV sales.
• MP Materials (Ticker: MP):
  • Connection to Physical AI: Rare earths from MP Materials are essential for magnets, which are used in actuators for humanoid robots.
  • Government Signal: The White House investment in MP Materials signals a strategic focus on developing humanoid robots domestically.

Conclusion and Takeaways

Luke Lango emphasizes that while many AI-related stocks have already seen significant gains, the underlying profit-driving forces are accelerating, not slowing down. He advocates for letting "winners run," especially those at the epicenter of these trends. The key takeaway is that AI is a multi-faceted growth area, and investors can find opportunities across infrastructure, energy solutions, resource supply chains, practical applications, and the physical manifestation of AI. The identified companies, though some have already performed well, are still considered to have substantial growth potential due to the massive scale of the AI revolution.