Photo by Steve Johnson on Unsplash

In the 1989 Academy Award–nominated film Field of Dreams, the lead character Ray Kinsella (played by Kevin Costner) hears a mysterious voice whisper, “If you build it, he will come.” Acting on blind faith, Ray builds a baseball diamond in the middle of his Iowa cornfield, risking financial ruin. Against all logic, the field draws a flood of visitors.

Today, a similar “field of dreams” is being built—not with corn, but with data centers. Instead of baseball players, it is artificial intelligence (AI) models, applications, and users who are coming.

The Market’s AI Momentum

The AI boom has already reshaped markets with all three benchmarks hitting record highs. Last month, the S&P 500 climbed +1.9%, while the NASDAQ rose +1.6% and Dow Jones Industrial Average surged +3.2%. Year to date, the indexes are up +10%, +11%, and +7%, respectively.

Behind this surge lies an unprecedented wave of AI infrastructure investment. Hyperscalers—Amazon.com (AMZN), Microsoft Corp. (MSFT), Google-Alphabet (GOOGL), Meta Platforms (META), and others—are pouring hundreds of billions into AI, much of it flowing directly to NVIDIA Corp. (NVDA), the undisputed leader in GPUs (Graphic Processing Units) powering the world’s AI engines. How large is the spending? NVIDIA CEO Jensen Huang estimates $3 trillion to $4 trillion will be spent this decade to fuel the AI revolution.

Source: Visual Capitalist

The Scale of AI’s Buildout

To put this into perspective:

• Amazon is projected to spend over $100 billion in 2025 alone, more than its cumulative capital expenditures from 2000–2020 combined.

Meta is constructing its $10 billion+ Hyperion data center in Louisiana—a sprawling 4 million sq. ft. complex across 2,250 acres, powered by a $4 billion natural gas plant. The footprint is so gargantuan it could cover much of Manhattan (see graphic below).

• xAI’s Colossus, a 750,000 sq. ft. data center in Memphis, Tennessee was completed in just 122 days—equivalent to building 418 homes in half the time it normally takes to construct one house (see slide below).

Source: BOND (Global Technology Investment Firm)

This breakneck pace of spending underscores the urgency and competitive pressure driving the global AI arms race.

The Origin of the AI Floodgates Opening

The spark was lit on November 30, 2022, when OpenAI released its LLM (large language model) called ChatGPT. Within two months, it amassed 100 million users.

Today, ChatGPT’s metrics have blasted much higher (see slide below):

• 800 million weekly active users
• 20 million paid subscribers
• $3.7 billion in revenue (as of April 2025)

Source: BOND (Global Technology Investment Firm)

But OpenAI is far from alone. Google (Gemini), xAI (Grok), Anthropic (Claude), Meta (LLaMA), Amazon (Titan), Perplexity, and DeepSeek are all competing with their own LLMs. In total, over 1 million machine learning models now exist (see slide below) — each requiring costly compute power and pricey data centers.

Source: BOND (Global Technology Investment Firm)

Bubble or Productivity Breakthrough?

With trillions flowing into AI, a natural question arises: Is this a bubble?

Even OpenAI CEO Sam Altman admits we’re in an AI bubble :

“When bubbles happen, smart people get overexcited about a kernel of truth…Someone is going to lose a phenomenal amount of money… and a lot of people are going to make a phenomenal amount of money.”

Both realities can be true:

1. Yes, hyperscalers are spending like “drunken sailors.”
2. Yes, AI demand and productivity benefits are real and growing exponentially.

Consider the trajectory of global cloud revenues: from nearly $0 a decade ago to $300 billion today—a +37% CAGR (see chart below).

Source: BOND (Global Technology Investment Firm)

And the primary reason for cloud growth can be attributed to AI productivity benefits. A recent SAP survey found that workers using AI save nearly one hour per day on average. That’s transformative for companies: higher productivity without needing proportional hiring. 

AI Use Cases Expanding Aggressively

AI’s applications now span nearly every sector (see slide below):

• Technology – software engineering, code generation
• Customer Service & Marketing – customer support and call centers
• Transportation – autonomous vehicles and logistics
• Healthcare – drug discovery and development
• Supply Chains – precision manufacturing and optimization
• Automation – multi-purpose robotics
• Cybersecurity – threat detection and prevention
• Education – personalized lessons and curriculums
• Energy – grid optimization and demand forecasting

  (Click on image to enlarge)

Source: BOND (Global Technology Investment Firm)

The New Field of Dreams

Throughout history, every great leap—printing press, steam engine, electricity, internet—has required massive upfront investment before the payoff arrived. AI is following the same path. Today, we are in the midst of building a new AI Field of Dreams. However, now, the data centers are the new baseball fields. And as with Ray Kinsella’s diamond, the masses are indeed coming.

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