Fortune52%

AI’s productivity gains are years away, but if it doesn’t deliver, it could make unsustainable debt levels even worse, Deutsche Bank economist says 51%

By Sasha Rogelberg55%

7/8/2026, 7:00:00 AM

BS Summary: This article contains 27 faulty reasoning types, including Availability Heuristic, Pessimism Bias, and Appeal to Authority, with Negativity Bias as the most egregious example at 28.6% saturation with 189 hits. Analysis detected 2,201 faulty-reasoning hits from 660 analyzed words, generating a BS Score of 50.5% and a BS Rank of 51% (10,544 of 21,176 articles). This article is worse (more manipulative) than 50.20% of the article peer group.

Economists are waiting for data to indicate AI has delivered on its promises of productivity gains, but that moment is likely years away, according to Jim Reid, Deutsche Bank Research Institute global head of macro and thematic research. 
Reid predicted that AI would, indeed, create new jobs and increase workplace efficiency, but said people are being a little overambitious in their timelines of when the technology will have a rippling impact on the economy. 
“In my career I haven’t seen anything like AI in terms of potential for productivity,” Reid told Bloomberg Television on Tuesday. 
“But I would probably caution that it is going to take a number of years for us to properly embed it into enterprises to really get the benefits of that.” 
Multiple economic indicators suggest that despite tech leaders touting AI’s ability to overhaul the workforce, there’s little evidence of its widespread impact so far. 
As of last month, the Yale Budget Lab noted no significant changes in occupational mix or length of unemployment for roles with high AI exposure, leading researchers to conclude no evidence of AI-related labor market disruptions. 
Apollo chief economist Torsten Slok noted in a recent blog post, citing Bloomberg and Macrobond data, that while profit margins for the Magnificent Seven increased from about 15% to 25% between the first quarters of 2023 and 2026, margins for the rest of the S&P 500 index were around 10% over the same period. 
The data suggests that while tech companies are able to more easily integrate new technology into their operations, other industries have been slow to deploy the technology, let alone see its benefits. 
As investors continue to pour money into the Magnificent Seven, there’s increasing concern that AI may not offer quick returns on investment, leading to a “painful repricing” for financial markets that threaten to further decelerate the proliferation of AI, Slok warned. 
“The bottom line is that a mismatch between current earnings expectations and the actual time firms need to generate ROI on AI investments could have significant implications for many AI company valuations today,” Slok said. 
**Reid’s read on the future of AI** 
Reid shares this concern. 
He said that AI will likely be inflationary in the short- and medium-term, and that if the technology fails to deliver on its promises despite hefty investments, it could worsen the already precarious levels of debt around the world. 
He pointed to data published last year by the Federal Reserve Bank of Dallas showing three outcomes for the future of AI: a modest increase in GDP as a result of productivity gains, skyrocketing productivity as AI gains superhuman capabilities, or human extinction as a result of an AI singularity. 
“Everybody knows that debt levels aren’t sustainable for a lot of countries,” Reid said. 
“If you were trying to find hope, you would say that AI is a productivity miracle that you can grow into your debt, that would be the bullish view. 
I suppose the bearish view is that if anything lifts interest rates or long-term interest rates much above current levels, you start to get into kind of debt sustainability levels that just make no sense whatsoever.” 
The economist, however, was optimistic about the eventual impact of AI, arguing humans have been effective at innovation for more than three centuries through a series of industrial revolutions. 
Tech CEOs like OpenAI’s Sam Altman and Anthropic’s Dario Amodei have recently likewise toned down their own promonitions of AI’s mass displacement of white-collar jobs, similarly saying the technology will transform, rather than roil, the nature of work. 
“My view on AI and jobs is slightly skewed by what economic history tells us,” Reid said. 
“At every point of a new breakthrough in innovation, we’ve been really scared about jobs, about new technology destroying jobs, and it has never happened in aggregate.” 
Article reasoning-pattern comparisonThis article: 17.1%Sasha Rogelberg: 4.8%Fortune: 4.2%Confirmation Bias17.1%This article: 8.2%Sasha Rogelberg: 2.8%Fortune: 1.4%Anchoring Bias8.2%This article: 28.3%Sasha Rogelberg: 5.3%Fortune: 3.3%Availability Heuristic28.3%This article: 9.2%Sasha Rogelberg: 0.8%Fortune: 1.4%Representativeness Heuristic9.2%This article: 0.0%Sasha Rogelberg: 1.7%Fortune: 1.1%Hindsight Bias0.0%This article: 5.5%Sasha Rogelberg: 2.1%Fortune: 2.7%Overconfidence Bias5.5%This article: 15.2%Sasha Rogelberg: 7.2%Fortune: 6.7%Framing Effect15.2%This article: 10.8%Sasha Rogelberg: 3.9%Fortune: 0.5%Loss Aversion10.8%This article: 11.2%Sasha Rogelberg: 1.6%Fortune: 0.6%Status Quo Bias11.2%This article: 0.0%Sasha Rogelberg: 0.6%Fortune: 0.3%Sunk Cost Effect0.0%This article: 12.9%Sasha Rogelberg: 3.3%Fortune: 3.3%Optimism Bias12.9%This article: 25.6%Sasha Rogelberg: 7.4%Fortune: 2.5%Pessimism Bias25.6%This article: 28.6%Sasha Rogelberg: 7.7%Fortune: 6.9%Negativity Bias28.6%This article: 0.0%Sasha Rogelberg: 0.8%Fortune: 1.7%Self-Serving Bias0.0%This article: 0.0%Sasha Rogelberg: 0.6%Fortune: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.2%Actor-Observer Bias0.0%This article: 0.0%Sasha Rogelberg: 1.9%Fortune: 0.8%In-Group Bias0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.6%Sasha Rogelberg: 1.3%Fortune: 3.1%Halo Effect0.6%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.0%Horn Effect0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.0%Dunning-Kruger Effect0.0%This article: 13.3%Sasha Rogelberg: 2.3%Fortune: 1.5%Recency Bias13.3%This article: 3.2%Sasha Rogelberg: 0.3%Fortune: 0.3%Primacy Effect3.2%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.0%Blind-Spot Bias0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.7%Ad Hominem0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.2%Straw Man0.0%This article: 22.3%Sasha Rogelberg: 5.1%Fortune: 4.8%Appeal to Authority22.3%This article: 17.4%Sasha Rogelberg: 5.1%Fortune: 2.2%False Dilemma17.4%This article: 19.2%Sasha Rogelberg: 3.2%Fortune: 1.3%Slippery Slope19.2%This article: 5.5%Sasha Rogelberg: 0.4%Fortune: 0.3%Circular Reasoning5.5%This article: 18.9%Sasha Rogelberg: 5.7%Fortune: 6.0%Hasty Generalization18.9%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.2%Red Herring0.0%This article: 7.9%Sasha Rogelberg: 1.0%Fortune: 0.5%Bandwagon7.9%This article: 11.2%Sasha Rogelberg: 4.0%Fortune: 3.0%Appeal to Emotion11.2%This article: 0.0%Sasha Rogelberg: 0.1%Fortune: 1.2%Begging the Question0.0%This article: 14.4%Sasha Rogelberg: 3.5%Fortune: 3.9%Post Hoc (False Cause)14.4%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.1%Tu Quoque0.0%This article: 5.3%Sasha Rogelberg: 0.4%Fortune: 0.3%Burden of Proof5.3%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.2%Appeal to Nature0.0%This article: 9.2%Sasha Rogelberg: 1.1%Fortune: 0.4%Composition/Division9.2%This article: 7.3%Sasha Rogelberg: 3.1%Fortune: 2.4%Anecdotal7.3%This article: 4.1%Sasha Rogelberg: 0.5%Fortune: 0.2%No True Scotsman4.1%This article: 0.0%Sasha Rogelberg: 1.5%Fortune: 2.3%Ambiguity (Equivocation)0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.2%Middle Ground0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.0%Personal Incredulity0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.1%Special Pleading0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.2%Genetic Fallacy0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 1.5%Unattributed Quote0.0%This article: 0.0%Sasha Rogelberg: 0.3%Fortune: 1.3%Quote-first Misdirection0.0%This article: 1.1%Sasha Rogelberg: 1.3%Fortune: 4.4%Biased Writer Voice1.1%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 1.2%Indoctrination0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Sasha Rogelberg: 0.0%Fortune: 1.2%Attempt to Sell a Product or S…0.0%

660 words analyzed.

Speakers

3speakers81%attributed speech128writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 23 words • 0.0% coverageJim Reid • 38 words • 0.0% coverageJim Reid • 36 words • 0.0% coverageJim Reid • 21 words • 0.0% coverageJim Reid • 30 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageYale Budget Lab • 36 words • 0.0% coverageTorsten Slok • 54 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageTorsten Slok • 41 words • 0.0% coverageTorsten Slok • 35 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 4 words • 0.0% coverageJim Reid • 39 words • 0.0% coverageJim Reid • 50 words • 0.0% coverageJim Reid • 14 words • 0.0% coverageJim Reid • 29 words • 0.0% coverageJim Reid • 36 words • 0.0% coverageJim Reid • 29 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageJim Reid • 17 words • 0.0% coverageJim Reid • 27 words • 0.0% coverage
Selected voice

Torsten Slok

100%flagged-word coverage
130 attributed words24% of attributed speech100% writer coverage
0%5.0%10.0%Biased Writer Voice-5.5 ptsWriter: 5.5%Torsten Slok: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.