The One AI Development That Matters Today
Today's Brief: Big Tech is pouring an unprecedented $650 billion into AI infrastructure this year, yet most of them are seeing little to no direct profit from it. The real winners are the companies building the picks and shovels of the AI gold rush. We'll show you how to follow the money.
The $650 Billion Paradox
Microsoft, Alphabet (Google), Amazon, and Meta are collectively spending over $650 billion on AI capital expenditures in 2026. This staggering sum, representing 15-20% of their combined annual revenue, is being funneled into building out the massive data centers and compute power required to train and run advanced AI models. Alphabet alone forecasts a spend of $175-$185 billion as it doubles down on its Gemini models and Google Cloud's Vertex AI platform.
However, a surprising trend has emerged: the companies making these colossal investments are not the ones reaping the immediate financial rewards. A recent PwC survey found that 56% of companies report getting nothing from their AI investments, and RAND research shows that over 80% of corporate AI projects fail to move beyond the pilot stage.
So, where is the profit going?
The Real Winners: The AI Infrastructure Gold Rush
The immense profits are flowing to the companies that provide the essential infrastructure for the AI revolution. These are the modern-day equivalents of the merchants who sold picks, shovels, and Levi's jeans during the California Gold Rush:
Nvidia (NVDA) — Designs the GPUs that are the workhorses of AI. Stock has soared, becoming a dominant force in the market.
Comfort Systems USA (FIX) — Builds and maintains the data centers that house the AI hardware. Reported a 42% year-over-year revenue increase.
Vertiv (VRT) — Provides critical power and cooling solutions for data centers. Riding the $650B hyperscaler AI spending surge.
This trend highlights a critical insight for investors and business leaders: the most immediate and reliable profits in the current AI landscape are in the infrastructure layer, not the application layer.
The Playbook: How to Profit from the AI Infrastructure Boom
For the individual business leader, the takeaway is not to build a data center, but to understand where the value is being created and how to align with it.
Identify Bottlenecks in Your Own Operations: Before chasing complex AI applications, identify a simple, repetitive data entry or analysis task in your business. The goal is to find a small, contained problem that can be solved with a simple script or automation.
Use a Free AI Code Generator: Leverage a free tool like OpenAI's Codex or a similar AI code generator to write the script. Prompt it with clear, simple instructions (e.g., "Write a Python script that reads a CSV file of customer emails and identifies all duplicate entries").
Test and Refine: Test the script on a small scale, refine the prompt, and ensure it works reliably. This small win will demonstrate the power of AI-assisted coding and open the door to more ambitious projects.
This approach mirrors the success of the infrastructure players: focus on a tangible, high-value problem that can be solved reliably and efficiently. By starting small and focusing on a clear ROI, you can avoid the 80% of AI projects that fail and begin to build real, measurable value.
In Other News
OpenAI is entering the hardware market, with plans for a smart speaker, smart glasses, and a smart lamp, backed by a $6.5 billion acquisition of former Apple designer Jony Ive's startup.
Agentic AI is transforming retail, with major players like Walmart and Target partnering with Google to create autonomous AI systems that can execute complex tasks like creating a shopping list from a handwritten recipe and automatically purchasing the items.
AI's impact on the job market is becoming clearer, with a Morgan Stanley report indicating that AI contributed to 11% of jobs being eliminated in the past year, and another 12% not being backfilled.