One of our panels during the gathering in Maine focused on AI. Two experts contributed, and Eric Hale moderated with aplomb and élan. The Q&A and the continuing post-panel conversation were fierce. There is a report on the panel, along with the associated survey; and in it there can be found 16 AI usage recommendations.
We are making that report freely available. Here’s the link: kotokreport.com/PDF/Camp-Kotok-AI-Panel-Report-Aug-2026.pdf
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I want to thank Barry Norton and Eric Schlesinger for their lively and comprehensive participation and Eric Hale, who masterfully herded the 50 cats in the room. Lastly, Eric Hale serves in a leadership role with the Global Interdependence Center (GIC). I expect future GIC events will include sessions on AI usage as part of the agenda, with both applications that lead to good outcomes and applications that lead to evil outcomes under discussion. For GIC details see www.interdependence.org.
I asked one question that did not receive an answer from the room of 50 highly skilled professionals. I noted that predicted AI capital investment in 2027 is estimated to $1.2 trillion. That is a single-year capex applied in the US economy, which is estimated at $32 trillion GDP. I am ignoring the huge non-US, rest-of-world capex even though it is a competitive force. If we use a low-rate-of-return, utility-type model and estimate something like 8%, whether on equity or to amortize debt, that capex needs $100 billion per year for the classic inter-temporal period of 30 years to fully complete the investment journey.
Hyperscaler Free Cash Flow Projection chart. Source: Nomura Vol (www.nomura.com)
So I asked where the panelists or the financial players in the room saw the reliable sourcing of that required future revenue. No one offered a cogent long-term answer. Markets are starting to ask that question, too. Credit default swaps on a company like NVIDIA have doubled from about 40 basis points to about 80 basis points.
Leases like that with Meta have clauses on the renewals. Hat tip to the Shanaka Anslem Perera Substack column for an excellent technical dissection of that lease. Note that this is a footnote item on a balance sheet. Those clauses depend on what the value of the property is sometime in the future. So, a 4-year lease with multiple 4-year options may suggest 20 years but only if the future delivers the revenue. Otherwise, a huge building becomes empty, and some chips that are no longer the most current model become cheapened collateral. There’s a reason the S&P rates a bond issue A- even though the company is presently very profitable.
Does anyone remember the rapid buildout of bowling alleys, or canals, or Atlantic City casinos? I do. For fun, spend ten minutes and search the history of the Taj Mahal Casino in Atlantic City. Then you decide if that is a metaphor for today. Note that there are many ways to examine that metaphor for lessons applicable to today.
AI is exciting. I use it daily. I hope the report from the Maine gathering at Leen’s Lodge is helpful to you.
– David
Further reading:
Shanaka Anslem Perera’s “The Clocks on One Building” examines the different timelines embedded in Meta’s Louisiana data-center arrangement: four-year initial leases, renewal options extending to twenty years, sixteen years of residual-value support, and debt running to 2049. Perera’s analysis helps separate the lease commitment from the longer-term financial exposure.
Eric Schlesinger’s “Camp Kotok, AI, and the Questions That Matter” considers why AI’s most important contribution may not be supplying answers, but helping people ask better questions and challenge their assumptions. Drawing on Camp Kotok discussions about semiconductors, infrastructure spending, employment, and business adoption, Eric asks where durable advantage will come from when intelligence itself becomes increasingly commoditized. His article is a useful reminder that human judgment becomes more important, not less, as AI grows more accessible.
Eric Hale inspires Rick Newman with “Notes from Camp Kotok: 10 Ways to Exploit AI” where it turns the experiences of Camp Kotok participants into practical advice for getting better results from AI. Drawing on an attendee survey organized by Eric, these notes explain how users can improve their prompts, invite disagreement, red-team their assumptions, limit AI to trusted sources, and automate recurring research. The collection matters because it treats AI not as an oracle, but as a tool whose usefulness depends on human judgment, careful verification, and thoughtful use.
Dave Nadig’s “Camp Kotok: An AI Counterinsurgency?” explores a revealing paradox among investment professionals who readily use AI but still place a high value on unassisted human expression. Camp Kotok participants debated AI spending, competitive advantage, originality, and regulation, yet their strongest applause came when a local speaker said he had written his remarks without AI. Nadig’s article matters because it reminds financial advisors that AI can improve their work, but trust and personal judgment remain central to client relationships, and some clients may prefer that AI play no part in them.
Rick Newman’s “Notes from Camp Kotok: The AI Boom Is Just Getting Started” examines whether today’s massive investment in chips and data centers represents the beginning of a lasting technological shift or another period of costly overbuilding. Drawing on discussions among Camp Kotok participants, Newman considers parallels with the dot-com era, the risk of a cyclical “tools downturn,” and the energy and cooling limits facing data centers. The article matters because it separates confidence in AI’s long-term growth from the harder question of whether every company, project, and investor financing the buildout will earn an adequate return.
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