← All episodes

Why AI will dwarf every tech revolution before it: robots, manufacturing, AR glasses from CES 2026

| 12 products mentioned
Watch on YouTube artificial intelligence enterprise transformation workforce automation robotics manufacturing self-driving vehicles venture capital

At CES 2026, the All-In Podcast hosts a debate arguing that AI will dwarf every previous technology revolution in its transformative impact on society, business, and manufacturing. The discussion covers how AI-driven enterprise transformation is compressing value creation timelines, reshaping workforce dynamics, and creating entirely new business models—from humanoid robotics to self-driving vehicles—while featuring guest perspectives from McKinsey leadership and General Catalyst on the geopolitical and economic implications of this shift.

Key takeaways
  • AI adoption is accelerating at "warp speed," with companies now releasing products in weeks rather than years, and major enterprises seeing 10x revenue growth—though realizing ROI at scale remains a challenge for non-tech companies.
  • McKinsey is simultaneously growing its client-facing workforce by 25% while shrinking non-client-facing staff by 25%, demonstrating that AI enables productivity gains that free up talent for higher-value work rather than simple replacement.
  • Robotics and humanoid robots (like Tesla Optimus) will be the defining innovation of 2027, with the manufacturing cost curve being as critical as AI capability—the US must match Chinese manufacturing efficiency to maintain competitiveness.
  • The skills economy is fundamentally shifting: employers now need workers who can set aspirations, make value-based judgments, and drive creativity—areas where humans outperform AI—while technical coding ability becomes less valuable as code self-writes.
  • Young people entering the workforce must demonstrate tangible skills through portfolio work rather than relying on traditional training programs, as companies increasingly prefer building AI agents over hiring and training junior staff.
  • Education must transition from a four-year model to lifelong learning, with the half-life of skills shrinking to less than 4 years, requiring institutions to teach continuous iteration and adaptation rather than mastery of fixed knowledge.
  • Venture capital is acquiring declining-value businesses (healthcare systems, call centers) as "platforms for transformation," using them as testbeds to rapidly deploy AI solutions before scaling to entire industries.

Recommendations (1)

Tesla Optimus
Tesla Optimus recommends

"Nobody will remember that Tesla ever made a car. They will only remember the Optimus and that he is going to make a billion of those."

All-In Podcast · ▶ 39:14

Mentioned (11)

Google TPUs
Google TPUs "I remember when Larry and Sergey started walking around with these. Larry came on the dance floor..." ▶ 41:52
ChatGPT
ChatGPT "Compare the last two or three years since ChatGPT was launched to the 30 before it." ▶ 2:55
Anthropic
Anthropic "You look at Anthropic, which we're also investors in, that goes from $60 billion last year to, yo..." ▶ 5:42
Stripe
Stripe "We invested in Stripe in 2010. It became a hundred billion dollar company 12-13 years later." ▶ 5:34
McKinsey
McKinsey "We saved 1.5 million hours in search and synthesis last year, but we're dividending that to solve..." ▶ 18:30
General Catalyst
General Catalyst "Our aspirations in venture capital is to be the best seed firm in the world." ▶ 10:13
Waymo
Waymo "Waymo obviously is leading the pack but then you also have BYD, Alibaba, Pony AI - this is a glob..." ▶ 34:49
Function Health
Function Health "You have Function Health, you have Superpower now doing - getting your blood work done every year..." ▶ 44:08
Oura Ring
Oura Ring "Between your Eight Sleep, your Oura, your Whoop, all of that, your blood work coming together and..." ▶ 48:51
Whoop
Whoop "Between your Eight Sleep, your Oura, your Whoop, all of that, your blood work coming together and..." ▶ 48:51
Eight Sleep
Eight Sleep "Between your Eight Sleep, your Oura, your Whoop, all of that, your blood work coming together and..." ▶ 48:51