Public transcript

Former Google CEO On The Importance Of Human Expertise In An Increasingly Automated World

By: Forbes
Length: 29 min
Language: English
Text from: the video's captions
Transcribed: 14 October 2026

Read the full transcript Open on YouTube

Notes in English.

Summary

This Forbes conversation features former Google CEO Eric Schmidt and Deloitte CEO Joe Ucuzoglu answering audience questions about artificial intelligence, business, and careers. Schmidt argues the agentic period is the best investment opportunity, estimates China is six to 12 months behind the US, and frames AI as the historic arrival of nonhuman intelligence. Ucuzoglu stresses that domain expertise and cross-functional teams are key to enterprise AI adoption, and both agree the technology will not be stopped.

Key points

Larry Page's PhD subject was AI, and Google's first real internal use of AI was improving ad system performance.
Schmidt says the best way for an average person to make money on AI is to found an agentic AI company that builds an agent to do something.
America needs an estimated 80 gigawatt of capacity for AI data centers in the next 3 to 5 years, with 1.5 gigawatt being the size of a nuclear power plant.
Job loss from AI is showing up in customer service and entry-level software programming.
China is judged to be six to 12 months behind the US, with models like Qwen and DeepSeek near the top of rankings and a full self-sufficient hardware and software stack.
Deloitte's CEO argues AI works best when technologists are paired with business people who understand the function and industry.
Google's 20% time worked as a balance of power between creative engineers and management.
Schmidt calls this the moment in history when a nonhuman intelligence arrived as a competitor to humans, and how we shape it will determine the outcome.

Questions it answers

00:00Google's AI origins

How did Google get into AI, and why did Henry Kissinger co-author an AI book?

Larry Page's PhD subject was AI, and Google's first real use was improving ad system performance. Kissinger, who had studied Kant, was drawn to AI because Demis's presentation made him worry about its impact on human consciousness.

Kissinger was interested in AI's effect on consciousness, not the technical side
Deloitte's 500,000 employees all leverage AI in some way

01:40Investing in AI

How can an average investor make money on AI?

Schmidt says it's late for Magnificent 7 gains and startups are too highly valued at launch; the easy path is to found an agentic AI company that builds an agent to do something, since the next year or two is the agentic period.

The agentic period means everyone will build and compete on agents
Better agents can build one incredible company

03:30Data centers and jobs

Where is AI hitting the economy most right now?

AI contributes more than 1% of US GDP via the data center buildout; hyperscalers request 1 to 10 gigawatt each, and America may need 80 gigawatt in 3 to 5 years, versus 1.5 gigawatt for a nuclear plant.

Schmidt started a data center company
Deloitte's headcount is higher than a year ago despite displacement

05:30AI vs. the internet

Is AI bigger than the internet, and where are job losses showing up?

Deloitte's CEO says AI is more accelerated over 3 years but harder to deploy in large, bureaucratic enterprises, requiring end-to-end process change. Job loss evidence exists in customer service and entry-level programming.

Diffusion from Silicon Valley to the heartland takes time
The internet's 30-year impact was larger to date

07:10Next wave and China

What's the next big wave, and how close is China?

The next wave is still AI, moving from language to action through agents, with reasoning models at graduate-level MIT/Stanford quality. China is six to 12 months behind, with strong models like Qwen and DeepSeek and a self-sufficient stack.

China targets AI everywhere in society rather than AGI
Deep research, OpenAI R3 and DeepSeek V3 reasoning power is frightening

10:00Warfare and careers

How is AI changing warfare?

The Pentagon's Maven program began with drone video surveillance, and the US is now learning from Ukraine with a big drone adoption program for land, sea, and air.

Most soldiers' work is watching, which is the first AI use

13:00Learning AI

How should a non-technical 40-year-old learn AI?

MIT and Stanford should teach a freshman prompt engineering course; the 40-year-old can use these tools directly, as they produce working systems for non-technical people.

Every student's whole life will involve prompting
Detection software for AI-written work has false positives

14:20Big tech moat and hiring

Can small companies still become giants, and do humanities majors get hired?

Big companies grow because of capital and data centers, making it harder for small players. Deloitte hires humanities majors as 'best available athletes' who acquire tech skills while providing domain understanding.

Deploying tech built in a lab into an enterprise generally fails
Cross-functional teams are needed for fit-for-purpose design

Notes

Google's AI roots and investing advice

Larry Page's PhD subject was AI, and Google's first real AI use was improving ad system performance.
Henry Kissinger co-authored the AI book because studying Kant led him to worry AI would affect human consciousness.
For average investors, the best play is not the Magnificent 7 or highly-valued startups, but founding an agentic AI company that builds an agent to do something.

Infrastructure and jobs

AI contributes more than 1% of US GDP, largely via data center buildout; hyperscalers are asking for 1, 5, and 10 gigawatt, and the industry may need 80 gigawatt in 3 to 5 years.
Real job losses are appearing in customer service and entry-level software programming.
Deloitte's Joe Ucuzoglu says 500,000 headcount is higher than a year ago; great professionals with domain expertise unlock the technology, and each prior wave created more jobs than it disrupted.

Competition with China

Chinese models like Qwen and DeepSeek rank near the top, and China builds a fully self-sufficient stack including its own chips.
China is not chasing AGI but AI used everywhere in society, especially on the edge; Schmidt judges them six to 12 months behind.

Careers and enterprise adoption

The best skill set integrates disciplines: baseline technology understanding plus knowledge of the business problem.
The 40-year-old humanities grad should learn prompt engineering; the tools are remarkably powerful for non-technical people.
Deloitte hires 'best available athletes,' and the generalist still has a big role.

Google history and culture

Google is a misspelling of googol, 10 to the 100th; the trademark was taken.
PageRank, invented in Larry's Stanford dorm room, made Google's ranking better.
Free food came from treating the company like a family; 20% time served as a balance of power between engineers and managers.
An engineer named Omid squatted in Schmidt's office, listened to his calls, and gave the true revenue number, 140 versus the sandbagged 115 million.

The big picture

The technology will not be stopped; it can be used for healthcare, drugs, and energy, but also oppression, war, and addicting youth.
This is the historical moment when nonhuman intelligence arrived as a competitor; alignment and how we shape it will determine the outcome.

Text from the video's own captions. Summary and notes written by AI from the transcript, so check anything important against the recording.