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

Discussion of how AI represents a fundamental shift beyond all previous technology revolutions (PC, Internet, mobile, cloud). Sternfels emphasizes that organizational speed now matters more than strategy, while Taneja highlights the compression of value creation - companies like Anthropic reaching $8-10B run rates in 2-3 years versus Stripe's 12-year journey to similar scale.

• •AI's impact will dwarf the combined effect of PC, Internet, mobile, and cloud computing revolutions
• •CEOs are focused on organizational speed over strategy - the pace of change is 'warp speed' compared to previous decades
• •Anthropic grew 10x year-over-year twice consecutively, reaching $8-10B run rate - fastest value creation in venture capital history
• •Technology is now central to every industry vertical, not a side consideration - evidenced by 150,000+ attendees at CES 2026

Sternfels reveals the critical tension in large enterprises between CFOs demanding ROI proof and CIOs pushing for rapid AI adoption to avoid disruption. While IT spending has increased significantly and companies are deploying AI at scale, realizing enterprise value in non-tech companies is proving harder than expected, creating 'pilot purgatory' for many organizations.

• •Large enterprises face a fundamental conflict: CFOs want to pause spending without clear ROI, CIOs warn of existential disruption risk
• •Non-technology companies are struggling to realize value from AI at scale despite significant investment increases
• •Companies are stuck in 'pilot purgatory' - need to rethink organization structure and get out of endless testing
• •The path forward requires bringing CFO and CIO perspectives together as allies rather than adversaries

Taneja explains General Catalyst's unprecedented $9B fund and strategy of acquiring declining businesses (hospitals, call centers, BPO companies) not for PE returns, but to provide market access for portfolio startups and demonstrate AI transformation at scale. This represents a new asset class focused on transformation rather than optimization.

• •Acquired Summa Health System in Ohio to create a real-world laboratory for AI healthcare transformation
• •Buying declining-value businesses (call centers, BPO) with important customer bases to accelerate startup adoption
• •Strategy is about compressed value creation - getting founders direct access to customers and proving transformation models
• •This is not private equity - it's a new asset class focused on transformation of incumbent entities, not optimization

Sternfels reveals McKinsey's unprecedented organizational restructuring: growing client-facing consultants by 25% while reducing non-client-facing staff by 25% with 10% output increase. The firm saved 1.5M hours in search and synthesis work, redeploying consultants to higher-value problem solving. This represents the first time in McKinsey's history that growth is decoupled from total headcount.

• •25% growth in client-facing consultants doing more complex, higher-value work enabled by AI
• •25% reduction in non-client-facing roles with 10% increase in output - unprecedented efficiency gains
• •Saved 1.5 million hours in search and synthesis tasks, redeployed to solving more complicated problems
• •First time in firm history that business growth is decoupled from total headcount growth
• •Deploying 40,000 personalized AI agents - targeting 1:1 parity with humans by end of 2026

Discussion of the fundamental shift in hiring where training new employees takes longer than building AI agents, creating a crisis for new graduates. The advice: skip traditional resume routes, demonstrate value through spec work, show chutzpah and passion. The focus shifts from solving problems to asking the right questions and radical collaboration.

• •Hiring and training new employees now takes longer than building an agent - creating hiring freeze for entry-level roles
• •Graduates must bypass traditional resume processes - email CEOs directly with spec work demonstrating value
• •Skills needed shift from problem-solving to creativity, asking right questions, and radical collaboration
• •Startups are using AI to write job descriptions and sort resumes - entire HR blocking and tackling functions being automated
• •The 'typing pool' and 'mail room' moment is happening for HR and legal departments

Both guests argue the 22-years-learning, 40-years-working model is broken. The future is lifelong colleges with continuous reskilling as technology evolves. ROI on employee skills training has halved from 7 years to 3.6 years in 30 years. Education must shift from mastering subjects to teaching continuous learning, resilience, and how to leverage AI agents.

• •The 22-year learning, 40-year working model is obsolete - need lifelong learning institutions
• •ROI on employee skills training dropped from 7 years to 3.6 years over last 30 years, continuing to shrink
• •Education system built 700 years ago around high fixed costs (libraries, professors) no longer fits modern needs
• •Must teach aspiration-setting, judgment, and creativity - skills AI cannot replicate
• •Focus should shift from which university you attended to demonstrable skills (GitHub profiles over degrees)

CES 2026 dubbed 'self-driving CES' with 2027 predicted as 'robotics CES.' Discussion covers the global race in autonomous vehicles (US innovation vs. Chinese manufacturing cost advantages), the critical need for AI-driven manufacturing to compete, and the transformative potential of humanoid robots like Tesla's Optimus, which could reach 1:1 ratio with humans.

• •2026 is 'self-driving CES,' 2027 will be 'humanoid robotics CES' - physical AI is accelerating rapidly
• •US has self-driving innovation advantage, but China has manufacturing cost advantage - critical competitive dynamic
• •Major contract manufacturer has 50,000 unfilled US manufacturing jobs - robotics is the only solution for resilient supply chains
• •Tesla's Optimus robot will be more transformative than Tesla cars - prediction of 1 billion units and 1:1 human ratio
• •Korea leads in robots per worker (1:10), Germany and China tied for second, US is distant third

Interactive segment examining past CES innovations (brick phones, Google Glass, BlackBerry, Palm Pilot, Sony Discman, pagers) to identify patterns of technology evolution. Key insights: Google Glass was ahead of its time (AR glasses still not viable), health wearables are in transition phase toward continuous monitoring, and LLM hallucinations may be this generation's 'unreliable technology' that gets solved.

• •Google Glass failed but AR glasses remain the 'today's version' of premature technology - form factor improved but utility still lacking
• •Health wearables (Oura, Whoop, Eight Sleep) are transition technology toward continuous monitoring and personalized medicine
• •Theranos concept was sound - nano-device manufacturing technology wasn't ready, but AI may enable it within 10 years
• •LLM hallucinations compared to Sony Discman's skipping - unreliable intelligence that will be solved in next generation
• •Pagers enabled 'always-on' work culture; now seeing reversal with millennials buying flip phones and digital cameras to disconnect