Jerry Neumann on the Problem With Investing in AI Right Now
Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Podcast Summary
In this compelling episode of Odd Lots, retired venture capitalist Jerry Neumann challenges the conventional wisdom about AI's wealth-creating potential. Drawing from his decades of experience investing since 1997, Neumann argues that AI represents the culmination of the computer revolution rather than the beginning of a new technological era. He compares the current AI boom to the shipping containerization revolution of the 1960s, where the real value was captured not by early innovators but by companies that later leveraged the technology to expand their market reach and pass efficiencies to consumers. (28:00) Neumann suggests we're at the end of the information computer technology wave, not the eruption phase of a new one, which has profound implications for how investors should approach AI opportunities.
- Core discussion focuses on why AI may not create massive individual wealth, despite being revolutionary technology, and how historical patterns of technological adoption suggest value flows to consumers rather than early investors
Speakers
Jerry Neumann
Jerry Neumann is a longtime venture capitalist who began investing in 1997 and recently retired from active VC work. He is also a professor at Columbia Business School and co-author of "Founder versus Investor: The Honest Truth About Venture Capital From Startup to IPO." Neumann attributes his VC success to being "lucky at starting investing at the right time," having started in both 1997 and 2008 during opportune market conditions.
Tracy Alloway
Tracy Alloway is co-host of Bloomberg's Odd Lots podcast, known for her insightful financial market analysis and interviews with leading investors and economists.
Joe Weisenthal
Joe Weisenthal is co-host of Bloomberg's Odd Lots podcast and a prominent financial media personality with extensive experience covering markets and economic trends.
Key Takeaways
Revolutionary Technology Doesn't Guarantee Investor Wealth
Neumann emphasizes the critical distinction between value creation and value capture in revolutionary technologies. (06:27) While AI is creating enormous value for society, this doesn't mean early investors or even foundation model companies will capture that value. Historical examples like shipping containerization show that revolutionary technologies often benefit consumers and later adopters more than early investors. Companies that used containerization to cut costs and increase margins performed poorly, while those that passed efficiencies to consumers and expanded their market share became massive successes like Walmart and IKEA.
AI Represents the End, Not Beginning, of the Computer Revolution
Unlike popular belief that we're in the "eruption phase" of a new AI revolution, Neumann argues we're witnessing the natural culmination of the computer wave that began decades ago. (29:09) He explains that computers were always built to help humans think better - they're "knowledge machines" - and AI represents the final step where machines become truly smart. This positioning has profound implications for investment strategies, as it suggests AI is completing an existing technological system rather than creating an entirely new one that will generate fresh categories of wealth creation.
Companies Should Use AI to Grow, Not Cut Costs
The most successful approach to AI adoption involves using efficiency gains to expand market share rather than maximize margins through cost-cutting. (33:27) Neumann warns that companies firing people because of AI are "doing it wrong" and should instead use AI to enable their workforce to accomplish more, grow the company, and diversify products. This mirrors how successful companies during the containerization era like Walmart focused on volume over margins, becoming logistics powerhouses that passed savings to consumers while expanding their market dominance.
Investment Success Requires Patience for Knowledge-Intensive Industries
The real AI winners will emerge in knowledge-intensive sectors where the technology can truly transform workflows and customer experiences. (31:52) However, these transformations require fundamental re-engineering of processes, hiring different people, and extensive training - changes that take years to implement effectively. Investors expecting immediate results will be disappointed, as the revolutionary benefits of AI won't materialize for approximately a decade. This patient approach to transformation, rather than quick AI retrofitting, will separate long-term winners from short-term disappointments.
Early Exit Strategy Beats Market Timing
Drawing from his experience during the dot-com bubble, Neumann advocates for the wisdom of selling early rather than attempting to time market peaks. (05:43) He recounts how his former company's CFO challenged him about buying discounted stock in an overvalued company, leading to the insight that if something is overvalued, the smart move is to sell rather than buy more. This philosophy of "better to sell early than late" protected his portfolio before the 2000 crash and reflects a broader principle about taking profits when valuations become disconnected from fundamentals.
Statistics & Facts
- Jerry Neumann began venture investing in 1997 and attributes his success to timing, starting during both the late 90s boom and again in 2007-2008. (20:49) This timing allowed him to buy in during opportune market conditions.
- The first shipping container sailed in 1956, but IKEA didn't become a global powerhouse until the 1970s, illustrating how revolutionary technologies can take 15-20 years to create massive business success. (31:59)
- By the early 1970s, electric knives had achieved adoption in 80% of American households within just three years of introduction, demonstrating how quickly novelty technologies can spread before becoming commoditized and forgotten. (38:08)
