Excess Returns — "$1 Trillion AI Bet. $10 Billion in Profits | Bob Elliott on the AI Income That Isn't Coming"

Date: November 14, 2025
Guest: Bob Elliott (Unlimited Funds)
Hosts: Jack Forehand, Justin Carbonneau, Matt Zeigler

Episode Overview

In this episode, Bob Elliott, CEO and CIO of Unlimited Funds, returns to discuss the current macroeconomic landscape and the disparity between financial market optimism and real economic weakness—especially in relation to the AI investment boom. The conversation dives into inflation, the Fed’s challenging position, asset price dynamics, the realities of AI-driven profits, and the quality of private investments offered to the masses. The latter half explores Unlimited’s new hedge-fund replication ETFs and the evolving role of alternative assets in investor portfolios.

Key Discussion Points & Insights

1. Late-Cycle Macro Environment: Market Optimism vs. Economic Weakness

• Disconnect Identified: Bob points out a clear divergence: financial markets (especially equities) are pricing in continued strength, while “the real economy is weakening, probably the weakest of which is in the labor market.” (01:00)

• Quote [Bob, 01:00]:

  “If you ask the techno optimist, they'll say, ‘Hey, this is going to cut a huge amount of jobs and lead to great margins.’ And then you ask them, ‘Okay, well, when those people lose their jobs and they don’t have any more money, who's going to spend on the company's outputs?’ And … they have no answer.”

• Labor Market & Policy Impact:
  The labor market is soft; growth has slowed due to post-COVID tightening and recent negative-growth policies (immigration & tariffs).

• Late-Cycle Risks:
  Navigating heightened expectations versus economic “malaise”—the “slow session” (14:55, 15:00–16:30).

2. Inflation, Tariffs, and Fed Response

• Sticky Inflation:
  Inflation hovers around 3%, above the Fed’s 2% target, due to recent tariffs offsetting disinflationary forces (07:19).
• Tariff Effects:
  Tariffs act as a hidden “tax” on consumers, not a cataclysmic drag, but enough to curb spending—about “1 to 1.25% of GDP.” Much of the tariff cost passes to US households. (08:59)
• Quote [Bob, 08:59]:

  “It’s taken time to flow through to actual prices that households are seeing. Probably the most direct effect, households are absorbing about 60% of the tariff increase and US business about 40%, and foreigners zero.”

• Fed Cuts & Dilemma:
  Post-Jackson Hole, Fed signals shifted to prioritize the labor market over inflation in rate-cut decisions—leading markets to price in aggressive cuts, but December cuts now seen as less likely. (11:41–13:33)
• Quote [Bob, 11:41]:

  “The challenge is repeating that is very difficult for asset markets because … you have to have easing that is greater than what is priced in.”

3. The “Income-Driven” Slowdown & the Myth of an AI-Led Boom

• Not a Debt Cycle:
  The cycle is driven by real income, not credit: “It’s been income-financed spending… as those things adjust, that’s what leads to adjustment in the overall growth rate.” (14:55)
• AI Boom: Limited Macro Impact:
  Despite the hype, the actual AI investment boom is a minor contributor to GDP (~1%), incapable of sustaining growth long-term. (15:00–16:30)

  “Overall that [AI] spending represents 1% of the economy. So it can influence GDP for a quarter or two, but it’s not going to drive the whole economy over time…” (15:00)

4. Fed Policy and the Quantitative Tightening (QT) Narrative

• QT's End Overblown:
  The end of QT is not a crisis—liquidity adjustments by the Fed are minor compared to the scale of banking assets. (23:06)

  “The difference between $5 and $0 [billion] is literally a rounding error in markets that are $30 trillion in size.” (23:06)

• Bank Constraints:
  Banks’ lending limits are about demand, not reserves or liquidity—liquidity risks are not a systemic concern. (27:30)

• Fed's Tactical Challenges:
  Hosts and Bob discuss the difficulty of Fed forecasting (“they don't have any skill in predicting, predicting…”) and the knife’s edge between proactive easing and holding firepower. (20:50–22:42)

5. Stock Market: AI Mania Masks Real Economy Weakness

• Narrow Breadth:
  The rally is driven almost entirely by “AI-oriented” mega-caps, while average S&P stocks are flat—reflecting actual economic stagnation. (30:00)

  “What that highlights is basically all of this rally is coming from a small number of large cap stocks, tech stocks, mag7, etc. That are basically driving the whole rally on what I'd call AI mania.” (30:00)

• Profitability Questions:
  Fundamental AI-driven profits are dubious when compared to the scale of investment.

  “OpenAI … claims that they need $1 trillion of investment … and right now they're earning $10 billion a year. Like how the heck are they going to off a trillion dollars of investment if they're earning $10 billion a year?” (32:05–35:54)

• Historical Analogies:
  Hosts reflect on prior infrastructure build-outs (railroads, Internet) where infrastructure builders saw poor returns; consumer surplus doesn’t equate to macroeconomic impact.

6. AI and Macroeconomic Productivity: The “Income That Isn’t Coming”

• GDP and Income, Not Consumer Surplus:
  AI efficiencies may create “consumer surplus”—time saved, more leisure, lower prices—but unless it translates into higher income, it doesn’t enhance GDP or profits. (37:39)

  “The only thing that matters to GDP is making more money. … You could use ChatGPT to save you some time… That’s consumer surplus. But … not GDP beneficial.” (37:39)

• Techno-Optimist Fallacy:
  If AI eliminates jobs, but those people don’t find new ones, aggregate spending and company revenues fall.

  “If you ask the techno optimist … ‘This is going to cut a huge amount of jobs and lead to great margins.’ … When those people lose their jobs and don’t have any more money, who's going to spend on the company's outputs? … No answer.” (41:14)

7. The Risks of Mainstreamed Private Assets

• Don’t Fall for Private Market Hype:
  Elliott stresses: “Rich people aren't making any money” in private asset classes. “Returns were negative, net of fees, relative to public market comps.” (43:04)

  “Rich people aren't even making money. So are we really sure we want to be bringing it to people with more moderate incomes?” (43:04)

• Dangerous Information Asymmetry:
  Private asset ETFs pose risks due to hidden, non-public information. “Creates such a market for grifters…” (43:04–46:30)

  “Such a good example of … institutional grift, known, known institutional grift that exists in the market.” (47:01)

8. Unlimited’s ETF Innovations: Democratizing Hedge Fund Strategies

• New ETF Lineup:
  Unlimited has launched equity long/short, global macro, and managed futures ETFs, targeting “equity index-like risk” for higher cash efficiency, using advanced (“third generation”) Bayesian machine learning for real-time replication of institutional hedge fund strategies. (50:29–55:28)

• Advantage Over Hedge Funds:
  Focus on manager diversification and radically lower fees; the key to durable outperformance is “cheaper than other folks.” (60:31)

  “The best way to outperform the index in hedge fund space is lower fees. … That is what we call a durable alpha.” (60:31)

• Customization & Transition:
  Advisors are moving from classic 60/40 to approaches including 20% alternatives—Unlimited’s products address their desire for both diversification and risk-targeted, liquid alternative strategies. (53:41)

Notable Quotes & Memorable Moments

• AI’s Economic Limits:

  “My guess is you'd look at it and you'd say, nope, I'm not making more money. I'm not making more money from this.”
  — Bob Elliott [39:30]

• Exposing the “Abundance” Fallacy:

  “If it [OpenAI] ends up being Netflix, who cares? … It's not a macroeconomically significant driver of productivity in the economy.”
  — Bob Elliott [37:39]

• Private Asset Warnings:

  “Just, just so that we're all clear on that, like, if you compare … private equity, venture capital … the returns were negative, net of fees. Just remember—negative returns relative to public market comps. So rich people aren't even making money.”
  — Bob Elliott [43:04]

• Institutional Grift in Private Credit Products:

  “Apollo could choose crap assets and sell them to the ETF at elevated prices … and if that product got into trouble, they could have an off-market low bid and basically take advantage of investors to create the liquidity.”
  — Bob Elliott [47:01]

Key Timestamps

• 01:00: Disconnect: Market optimism vs. soft real economy
• 03:31: Late cycle macro summary
• 07:19: Inflation trend and tariff effect
• 11:41: Fed's current stance and policy outlook
• 14:55: Income-driven vs. debt-driven cycle; “slow session”
• 23:06: QT’s actual (minor) impact on banking & liquidity
• 30:00: Stock market’s AI-mania and narrow rally
• 32:05–35:54: Economics of AI capex — “$1T bet, $10B in profit”
• 37:39: AI, GDP, and the limits of consumer surplus
• 41:14: Macro fallout of job-displacing AI
• 43:04–47:01: Risks and grift in new private asset ETFs
• 50:29: Unlimited's new ETF lineup and strategy replication
• 53:41: Advisors’ portfolio shifts and customization with alternatives
• 60:31: The “durable alpha” of low fees vs. manager selection

Final Thoughts

Bob Elliott delivers a candid, data-driven skeptical counter to AI euphoria and private asset hype, urging investors to focus on income and discern the real macro impact versus narrative. His ETF innovations at Unlimited aim to harness hedge-fund-like returns for all investors—without the high fees, opacity, and liquidity problems pervading much of the alternatives space.

Useful Links:

• Unlimited ETFs
• Excess Returns Podcast