Nvidia's AI Deals and "Circular AI" Fears

Bloomberg's Businessweek Daily podcast discusses Nvidia's AI deals, market concerns, and the future of work with AI.

Bloomberg Businessweek Daily podcast cover art featuring a microphone.
Bloomberg Podcast
Visual TL;DR
Nvidia AI DealsCore
Bloomberg podcast discusses Nvidia's significant AI deals and market implications
From the article 8 mentionsIn a recent Bloomberg Business Week Daily podcast, Carol Masser and Tim Stenovec delved into the complex world of AI investments, focusing on the significant deals Nvidia has been making.
Circular AI ConcernDriver
From the article 2 mentionsThe conversation highlighted concerns about "circular AI" fears, with Jim Chenos reportedly criticizing companies for funding a substantial portion of their own hardware sales within reported AI deals.
Schiffman Bullish OutlookContext
Robert Schiffman maintains a bullish outlook despite market concerns and criticisms
From the article 2 mentionsDespite these concerns, Robert Schiffman, a Senior Technology Credit Analyst at Bloomberg Intelligence, expressed a confident, bullish view.
Future of AIContext
podcast also explores the broader implications of AI on work and economy
From the article 2 mentionsIn a separate segment, reporter Kat Doherty discussed the introduction of single stock futures, a new tool allowing investors to hedge or speculate on over 50 major U.S. companies.
Market TechnicalsContext
discussion includes market technicals and liquidity impacting AI investments
From the article 5 mentionsSchiffman emphasized that while markets naturally experience fluctuations, the underlying fundamentals for companies like Nvidia are strong, with evidence of sustained and growing demand.
Inflated SalesEffect
From the article 3 mentionsThe core of the criticism, as brought up by Masser, is that companies might be artificially inflating their sales figures by essentially buying their own products.
True Demand QuestionedDriver
From the articleThis practice, where roughly two-thirds of hardware sales costs are bankrolled by the company itself in reported AI deals, raises questions about the true demand and the financial health of these ventures.
Investor NervousnessOutcome
From the article 3 mentionsInvestors are reportedly growing more nervous about these tightly linked companies, where investments often translate into purchasing their own manufactured goods, such as chips.
Contents(4)

In a recent Bloomberg Business Week Daily podcast, Carol Masser and Tim Stenovec delved into the complex world of AI investments, focusing on the significant deals Nvidia has been making. The conversation highlighted concerns about "circular AI" fears, with Jim Chenos reportedly criticizing companies for funding a substantial portion of their own hardware sales within reported AI deals.

The "Circular AI" Concern

The core of the criticism, as brought up by Masser, is that companies might be artificially inflating their sales figures by essentially buying their own products. This practice, where roughly two-thirds of hardware sales costs are bankrolled by the company itself in reported AI deals, raises questions about the true demand and the financial health of these ventures. Investors are reportedly growing more nervous about these tightly linked companies, where investments often translate into purchasing their own manufactured goods, such as chips.

Robert Schiffman's Bullish Outlook

Despite these concerns, Robert Schiffman, a Senior Technology Credit Analyst at Bloomberg Intelligence, expressed a confident, bullish view. He noted that Nvidia's stock has seen a thousand percent increase over the last five years and remains up 5% year-to-date, performing comparably to the S&P and NASDAQ. Schiffman emphasized that while markets naturally experience fluctuations, the underlying fundamentals for companies like Nvidia are strong, with evidence of sustained and growing demand.

The full discussion can be found on Bloomberg Podcast's YouTube channel.

Nvidia’s $750 Billion in Deals Reignite Circular AI Fears | Bloomberg Businessweek - Bloomberg Podcast
Nvidia’s $750 Billion in Deals Reignite Circular AI Fears | Bloomberg Businessweek, from Bloomberg Podcast

"I'm pretty confident in my bullish views," Schiffman stated. "I'd love to be the voice of reason at least for 30 seconds. If you take a step back, so Nvidia is in the news today, most read article. The sky is falling. What has Nvidia done over the last 5 years? Its stock, I'm a credit guy, its stock is up a thousand percent. Its stock is still up 5% year to date. S&P is up six, seven percent. NASDAQ's up six or 7%. We don't go up every single day in equity markets. We don't go tighter every single day in credit markets. So, we're going to be a little bit bouncy. But that being said, what gives me my bullish viewpoint is quite frankly the fundamentals, the evidence that growth is here and it's only getting bigger and better and it's going to stay hasn't gone away. And the evidence is it's only getting bigger and better."

Schiffman acknowledged that the financing aspect of these massive investments can be daunting, as it requires significant upfront capital with returns not seen for several years. He pointed to Alphabet Inc. (NASDAQ:GOOGL) reporting cash flow negative last week as an example of the financial strain, even as its cloud AI growth was reported at 82% in the quarter.

Market Technicals and Liquidity

The conversation also touched upon shifts in market structure, particularly concerning corporate bond trading desks. Schiffman noted that banks are now less willing to take on risk by holding large inventories of bonds, leading to more exaggerated spread movements when sellers emerge. He also mentioned "deal fatigue" from the constant stream of long-dated bond deals, which could increase the cost of doing business.

However, Schiffman remained optimistic about the availability of cash in the market, citing Alphabet's substantial cash reserves and unused equity issuance capacity. He also highlighted Nvidia (NASDAQ:NVDA)'s projected free cash flow of $200 billion next year, characterizing the company as the "rich uncle" distributing funds.

The Future of AI and Work

Looking ahead, Schiffman predicted a return to a state where hyperscalers generate significant excess cash flow, likely leading to increased stock buybacks. He anticipates this inflection point to occur around late 2028 or 2029. The discussion also acknowledged that AI will fundamentally change jobs, making efficiency and adaptability crucial for the workforce.

In a separate segment, reporter Kat Doherty discussed the introduction of single stock futures, a new tool allowing investors to hedge or speculate on over 50 major U.S. companies. Doherty highlighted the potential for increased retail participation, noting that even if investors couldn't secure allocations in oversubscribed IPOs like SpaceX, they could now gain exposure through these futures.

The conversation also featured insights from KPMG US's Rousan Shear, who discussed research on AI and jobs. Shear’s findings suggest that workers who learn to effectively collaborate with AI, rather than simply delegate tasks, will be the ones to thrive. She categorized individuals into "Amplifiers" (those exceeding AI baselines), "Delegators" (those performing at baseline), and "Apprentices" (those with skills but lacking AI application knowledge), emphasizing that learning to use AI as a thought partner is key.

Finally, the segment on climate risk and data center heat risk, featuring Bloomberg Opinion columnist Mark Gong, underscored the growing challenges of cooling the massive data centers required for AI, including their significant water consumption in certain regions.

© 2026 StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. Bulk reproduction or model training requires a license. See our terms.
Daniel Singer

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.

More from Daniel Singer