5 Reasons AI is Underhyped

Eric Schmidt recently went on the record during Congressional testimony saying, “AI is underhyped.” Let that sink in. One of the most influential tech leaders of our time is sounding the alarm — not that we’re overestimating AI’s impact, but that we’re drastically underestimating it.

He’s right.

AI isn’t just another tech wave. It’s the base layer for a new civilization — transforming the global economy, redefining power through energy, and solving problems we once thought unsolvable.

Let’s break down the top 5 reasons AI is underhyped, and why the biggest opportunities still lie ahead.

1. AI is Creating More Jobs Than It’s Taking

The mainstream narrative is obsessed with fear: “AI is stealing our jobs!” But this ignores the historical truth: every major technology shift creates more opportunity than it destroys.

According to the World Economic Forum’s recent Future of Jobs Report, AI will create 170 million new roles this decade, even as it displaces 92 million. These roles will include everything from big data specialists and big data engineers to autonomous car technicians and internet of things experts. (WEF)

Yes, the transition will be bumpy. But let’s not make the mistake of underestimating how AI unlocks abundance: by removing friction, automating the boring, and freeing up human potential. If you were alive during the industrial revolution and chose to be a horse trainer instead of a factory foreman, you missed the wave. Don’t miss this one.

2. AI’s Energy Demands Will Birth the Next-Gen Power Grid

Goldman Sachs estimates that AI data centers will require 90 gigawatts of additional power by 2030 — equivalent to building 90 new nuclear plants in the U.S. (Goldman Sachs)

Some predictions estimate that total electricity demand for AI by the end of this decade could consume 100% of the U.S.’s current energy output (4.18 billion TWhr).

But instead of viewing this as a bottleneck, we should see it as a once-in-a-generation opportunity to reinvest in infrastructure. We’re at the beginning of a nuclear renaissance. Gen-4 reactors, small modular reactors (SMRs), and even commercial fusion are suddenly economically viable, driven by surging demand from AI.

The AI use case is forcing humanity to acutely focus on new energy sources and infrastructure that will usher in a new energy abundance. Clean, constant, scalable power is no longer a pipe dream, it’s the backend of the AI revolution. The countries and companies that bet on energy innovation today are building the infrastructure for tomorrow’s AI-driven economy.

3. AI is Surpassing Expectations — Fast

In April 2024, OpenAI’s Deep Research model went from scoring 9% to 26.6% on “Humanity’s Last Exam” — a rigorous test of knowledge across 3,000+ university-level questions — in just 12 days. That’s a 183% leap in performance in under two weeks. (Fortune)

Think about that: AI systems are now learning faster than humans can comprehend. What used to take PhDs a decade, AI models now improve in days. For lab scientists, AI has become their most reliable, trusted assistant, helping extend out their brain matter.

In my recent Moonshots podcast episode with Palmer Luckey, he described how he is building Anduril products with the expectation and design paradigm that AGI is not only possible, but inevitable. We need to upgrade our expectations.

4. AI is Accelerating the Frontiers of Human Knowledge

Beyond writing code and delivering engaging content, AI is about to supercharge human intellect and augment scientists, allowing them to drive new breakthroughs in physics, chemistry, biology, and mathematics.

In much the same way that DeepMind’s AlphaFold enabled a game-changing algorithm for predicting protein structures, landing John Jumper, PhD and Sir Demis Hassabis, PhD the 2024 Chemistry Nobel Prize, we’re about to see a tsunami of new Nobel-quality work done as AI plus humans (“centaurs”) join forces to explore the unknown. AI will soon connect the dots and build new insights. This is how we transition from linear science to exponential science, and humanity wins big.

5. Most Companies Are Too Risk-averse to Go Big on AI

Here’s the hard truth: many of the world’s largest companies are structurally incapable of leveraging AI. Why? Because their leadership is trapped in the short-term incentive cycle: quarterly earnings, institutional shareholder pressures, risk mitigation.

As a result, most boards are terrified to take bold bets on AI. They’re slow-walking transformation while nimble AI-native startups and fearless founders sprint ahead. During my Moonshots podcast with Palmer Luckey, he also recounted how Facebook was contemplating a chance to take a majority position in NVIDIA just 10 years ago.

But fortune favors the bold. The companies willing to bet big on AI today — to rethink their products, retrain their teams, and rebuild their infrastructure — will become the new industry titans of the next decade.

Final Thoughts

You’re missing the bigger picture if you still think AI is about flashy demos and talking assistants. This is a civilization-scale leap. A once-in-a-generation transformation in how we work, learn, create, and solve.

You don’t need to be an AI expert. But you do need to engage. Learn. Apply. Build.

The future is being written in real time, and those working on AI are holding the pen.

Until next time,
Peter