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What podcasters are saying about AI & jobs
Summary
In the past 30 days, 74 speakers on 32 finance podcasts discussed AI & jobs in 102 views. Chorus has followed AI & jobs since September 16, 2026: 105 views from 77 speakers on 33 shows.
Who talks about it most
- Ethan Mollick · 5
- Eric Basmajian · 4
- Robert Kaplan · 3
- Paul Kedrosky · 3
- Luke Gromen · 2
- Ben Carlson · 2
- Mark Cuban · 2
- Gary Gensler · 2
- Patrick Harker · 2
- Naveen Rao · 2
The latest views
Newest first. Every quote is checked against the episode's transcript.
Nela Richardson · ADP
AI's employment impact is modest overall but about 3% a year for early-career AI-exposed white-collar jobs.
Richardson's ADP Canaries dashboard, built with Stanford, tracks AI's employment impact monthly. Its finding is that the effect is not widespread, but it is about 3% a year for early-career workers in AI-exposed white-collar and IT jobs. Job gains are coming from health care, leisure and hospitality, while IT and information sectors are only about 2% of the labor market. The impact is concentrated at early career stages, since later-career workers are seeing more income and employment.
“It's actually been very modest, but for early career in AI exposed fields in white collar jobs and IT, yes we're seeing an impact of at about 3% per year. It's meaningful impact”at 17:16
Bloomberg Surveillance: Bloomberg Surveillance TV: October 30th, 2026 ·
Scott Galloway · NYU Stern School of Business
AI will create more jobs than it destroys over time, though current job creation is uneven.
Galloway says he is an AI optimist and believes AI over time will create more jobs than it destroys. He cites The Economist's estimate that AI has so far created about a million jobs and destroyed about 100,000. He also notes that the best earnings calls now show headcount cuts, such as Meta growing 23% with 20% fewer employees, which concerns him. He thinks AI will create more jobs than it steals even though the current pattern looks uneven.
“And granted, I do think that AI over time will create more jobs than it destroys.”at 1:08:25
Prof G Markets: Josh Brown: If This Is A Bubble, It’s Pathetic ·
Luke Gromen · Forest for the Trees (FFTT)
AI-driven white-collar layoffs will be hard to reabsorb, with displaced workers unlikely to find equal-wage jobs.
Gromen cites recent layoffs: Kroger cutting about 37% of its corporate workforce, American Express and Barclays each firing 5% of workers because of AI, and Microsoft buying out 27% of its workforce. AI is hitting finance, tech and white-collar work at the same time. Laid-off workers are therefore unlikely to find another job easily or at the same wage. He says the job-loss argument has gone from debate to real evidence in the last couple of weeks.
“the side saying that AI is going to create a lot of white collar job loss has started to strike some serious body blows to the side that everything is gonna be fine for white collar jobs.”at 20:56
MacroVoices: MacroVoices #556 Luke Gromen: US Midterms & Beyond ·
Luke Gromen · Forest for the Trees (FFTT)
AI job displacement will spark accelerating US and Western political unrest, starting to be litigated in 2027.
Gromen argues that the US, unlike China, Japan and Korea, has a growing, heterogeneous population. If AI removes large numbers of good jobs (he cites Microsoft's 27% figure) in five to ten years, he expects the strain to produce social unrest. He cites elite overproduction and extreme wealth inequality, drawing on Peter Turchin's work, as the historical pattern. He expects this to start being litigated in 2027 through rising political instability in the West and US as AI displaces work. He acknowledges the view is dark and that it is a judgement about history rather than a forecast with data.
“if AI does what I think it's gonna do, I think it's gonna start getting litigated in 2027”at 39:01
MacroVoices: MacroVoices #556 Luke Gromen: US Midterms & Beyond ·
Eric Basmajian · EPB Research
AI-driven white-collar layoffs are not yet big enough to trigger a broad recession.
Historically, all recessions have been caused by construction and manufacturing downturns. Those sectors shed jobs first, and the stress then spreads downstream to services and white-collar jobs, which are laid off only once distress is already significant. Someone arguing that white-collar job losses will drive this recession is making a 'this time is different' case. Basmajian says it may be right, but he finds no evidence yet that white-collar losses are large enough, or have enough multiplier effect, to create a broad recession. He acknowledges that white-collar job changes are visible.
“I would take the case that this time is not going to be different and any significant labor market stress would still emanate from construction and manufacturing.”at 9:33
The David Lin Report: Microsoft AI Jobs Shock: 60,000 Buyouts, Who's Next? | Eric Basmajian ·
Eric Basmajian · EPB Research
AI productivity gains are emerging in adopting sectors, with 80-85% of them going to corporate profits.
A preliminary Census Bureau AI-adoption survey shows the top three adopting sectors (information technology, finance and professional services) are about 15% of the workforce. Their real output per worker shows a clear upward inflection from late 2022, while non-adopting sectors stay on their normal trend. That step change gives credence to real AI productivity, though some of the rise may be post-2022 over-hiring being corrected. Basmajian estimates 80-85% of the gains are going to corporate profits, not wages, which is normal early in a productivity cycle because wages lag. Firms appear to be reinvesting those profits in more AI. Construction, manufacturing, education and health care are expected to adopt more slowly, so productivity there may come later.
“I estimate about 80 to 85% of the productivity gains are accruing to corporate profits, and the remainder is accruing to real income gains in the sectors that are generating productivity.”at 15:06
The David Lin Report: Microsoft AI Jobs Shock: 60,000 Buyouts, Who's Next? | Eric Basmajian ·
Eric Basmajian · EPB Research
AI job displacement is structural, but new jobs should eventually replace those lost, though politically hard to say.
Basmajian separates the unemployment types. Cyclical unemployment is driven by the business cycle, frictional by job switching, seasonal by weather. AI-related unemployment is structural, meaning the jobs disappear. He argues that if the technology delivers real productivity, jobs will be displaced in some sectors, but new jobs will be created, as with the historical shift from agriculture. The transition is painful because creative destruction moves gains to different sectors and creates frictional unemployment before new demand appears. People cannot yet see the new jobs, which makes the message hard to sell politically. He says the economy has automatic stabilisers for the transition.
“If this technology does yield legitimate productivity, jobs will be displaced in those sectors, but new jobs will be created in the future.”at 20:58
The David Lin Report: Microsoft AI Jobs Shock: 60,000 Buyouts, Who's Next? | Eric Basmajian ·
Eric Basmajian · EPB Research
AI is automating junior, repetitive roles first, letting one skilled worker replace several juniors.
Basmajian says early evidence suggests AI tools are automating junior roles where tasks are repetitive and automated first. A highly skilled worker using an AI tool can do the work of several junior people, so entry-level roles are the first to disappear. He ties this to weak hiring that disproportionately hurts younger workers, and to the broader problem of young graduates struggling to get the experience that later roles require.
“Again, is all early evidence, but the jobs that tend to be automated away first are what seems like more of the junior roles where the tasks are more automated and repetitive, versus someone that may come in with a high degree of skill that using an AI tool can do the job of several junior people with one person.”at 37:25
The David Lin Report: Microsoft AI Jobs Shock: 60,000 Buyouts, Who's Next? | Eric Basmajian ·
Gary Cohn · IBM
AI productivity gains will compound across finance, healthcare, transport and logistics.
Cohn argues AI creates efficiency for companies that actually do things, driving productivity and economic growth, and that this time the build-out is much bigger than past capex waves. He sees efficiency gains in financial services, healthcare, transportation, infrastructure and logistics that could compound across the economy, though winners and losers remain unclear.
“What does AI do? It creates efficiency. For the companies that actually do everything. Productivity, economic growth.”at 29:06
Squawk Pod (CNBC Squawk Box): Gary Cohn & Chris Sununu: The Fed, AI, & the Midterms 10/29/26 ·
Vincent Daniel · Seawolf Capital
An AI productivity boom implies job losses, making AI a major political issue into 2027-2028.
Vincent says he has long argued that a productivity miracle from AI cynically implies an employment problem, because a productivity miracle cannot occur without shedding jobs. He points to Microsoft's reported layoffs of 60,000 people as a shot across the bow, and says a trend of such layoffs would tie into Amodei's memo from February. If that trend develops, he expects AI-driven job losses to become a very heightened political issue in 2027, going into the 2028 election.
“a productivity miracle associated with AI cynically tells you that we're gonna have an employment issue. ... you don't get a productivity miracle without shedding jobs.”at 25:43
On The Tape with Danny Moses: Lessons From The Great Financial Crisis | "Clear Takes" with Vincent Daniel and Danny Moses ·
Ed Elson · Prof G Media
Microsoft's 27% buyout would leave headcount below pre-pandemic levels, a structural AI effect rather than an overhiring correction.
Microsoft is offering voluntary buyouts to 27% of its global workforce, after nearly 5,000 layoffs in July, while its capex keeps rising. Microsoft added almost 60,000 employees in the two years after COVID, so a cyclical overhiring correction is one explanation. But if 27% of staff actually leave, total headcount would fall below pre-pandemic levels. That looks structural and tied to AI, whether AI is replacing workers directly or through the cost of AI spending. Elson concedes AI's effect on the overall US job market has been negligible, but says it is beginning to have an impact in tech.
“If Microsoft actually eliminates 27% of its workforce like they're suggesting, then their total headcount will actually be lower than what it was before the pandemic... That actually looks like a structural consequence of AI.”at 34:43
Prof G Markets: Microsoft Rises, Google Tanks: Why Investors Are Polarized On Big Tech ·
Jason Lemkin · SaaStr
Layoffs will accelerate as companies fund AI infrastructure and cope with endless competition, with no stability.
He cites Cloudflare cutting 20% of staff while its growth accelerated, with no visible business downside. He says SaaS companies used to reach a stable plateau, but now there is none, and competition from new startups is constant. He sees layoffs 2.0 and 3.0 coming, both to pay for AI infrastructure and to escape the performative AI environment.
“There's no planes of stability at all... So I just think layoffs are just gonna accelerate because we have no choice.”at 20:21
20VC: 20VC: Anthropic Files S1 Ahead of $2TRN IPO | Instinct's Rumoured $30 Billion Fundraise | Microsoft Laysoff 27,000 While Meta Taps Equity Markets for $95 Billion Capex Spending Spree ·
Gita Gopinath · Harvard University
AI agents can do much economic analysis, but AI translates poorly where human judgment is needed.
Gopinath agrees that a lot of analysis can be done from a desktop with AI agents pulling information. However, she says you still need judgment about which indicators matter and who says what. As a test, she used AI to translate an IMF report and found it did a pretty bad job, because so much meaning sits between the lines. She thinks there is still a lot of need for humans.
“I've used AI to translate an IMF report. It does a pretty bad job because there's so much between the lines, and you need to know what, you know, what actually is being said.”at 11:20
Bloomberg Surveillance: Bloomberg Surveillance TV: October 28th, 2026 ·
Dominic Konstam · Mizuho Americas
AI job cuts are reabsorbable as productivity rises; bigger risk is income and capital distribution.
The workforce is shrinking, yet the economy still adds enough jobs to hold unemployment flat, and Microsoft's cuts may reflect AI-driven change. Past productivity events were followed by labor demand recovering and workers being reabsorbed as productivity expands, so he is not afraid of permanent mass unemployment. The real issue is income and capital distribution: labor may be reabsorbed on less favorable real-wage terms, which hurts people's ability to own pensions and houses. That K-shaped outcome is where policy has to act.
“I wouldn't be afraid of this sort of Luddite sort of idea that, we're forever gonna create a mass unemployment that somehow can't be reabsorbed. I think the bigger issue is actually income and capital distribution.”at 13:06
Ethan Mollick · Wharton School, University of Pennsylvania
Organizational productivity lags individual AI gains because companies haven't adapted their structures to AI yet.
Individual workers can produce far more code with AI (a 100x gain is cited), but organizations run on sprints, coordination with marketing, and standups, so the gain does not translate. Mollick cites a study showing huge jumps in coding output but only about 30% more products shipped. He argues AI is a single-player experience while organizations are multiplayer, so the gains stall until processes are redesigned.
“Produce a 100 times more code than you did before, and that's great if you're a solo entrepreneur producing a lot of code. If you're in an organization that's doing two week long sprints... that 100 times productivity gain is actually... Can be a barrier.”at 3:25
Big Technology Podcast: This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick ·
Ethan Mollick · Wharton School, University of Pennsylvania
AI is forcing companies to break up teams and redo projects, cutting costs dramatically.
Mollick says real transformation requires structural change: pulling apart existing teams, dissolving role boundaries (coders doing design, designers coding), and reassessing projects from scratch. His example is a company that renegotiated a $200 million mainframe data migration plan down to $20 million, with the CTO thinking it could be done for about $2 million. He argues most organizations have lost the muscle memory for this kind of organizational experimentation.
“Thinking about structural change, which takes years for a lot of organizations to do... pulling apart organization teams... went from a $200,000,000 data migration plan... to a $20,000,000 plan.”at 15:03
Big Technology Podcast: This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick ·
Ethan Mollick · Wharton School, University of Pennsylvania
Expects AI won't deliver the 10% GDP growth some predicted, though broad transformation will still come.
Mollick is skeptical of the aggressive macro forecasts, including 10% GDP growth, and calls them outside any reasonable expectation. He still expects organizations to transform over the next five or ten years as the capability overhang gets filled, with large socioeconomic effects, so the disagreement is about the size of the productivity effect rather than whether it arrives.
“I don't think we're gonna see some of the insane numbers predicted of 10% growth, but, you know, who knows? ... But we will see transformation happen one way or another.”at 28:52
Big Technology Podcast: This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick ·
Ethan Mollick · Wharton School, University of Pennsylvania
Coding jobs have changed radically in two years; the best coders no longer write code themselves.
Mollick argues that for anyone with access to modern AI tools, coding is no longer the same job. The best coders he knows are not writing code anymore, which is his evidence that disruption is already here. He says the debate among economists about whether there will be more or fewer coders is unresolved, and that he cannot predict whose job is replaced, augmented, or where value goes.
“Any coders who are listening to this, their job is radically different than it was two years ago... The best coders I know are not writing code anymore.”at 29:26
Big Technology Podcast: This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick ·
Ethan Mollick · Wharton School, University of Pennsylvania
Senior developer demand is rising as AI expands output, while programmers' work shifts toward managing code.
Mollick says the debate over coders is a good example of how AI changes jobs. Right now demand for senior developers is rising, because AI lets a small organization with one coder produce work that once needed a team of 20. Programming jobs are also transforming from writing code to managing AI-written code. He hedges: maybe there are more programming jobs, but 'we don't really know,' and he says jobs will be invalidated, transformed or grown in ways we cannot predict.
“So right now, we are seeing more demand, at least for senior developers, because there's now more coding you could do.”at 1:01:42
Big Technology Podcast: This AI Expert Argues We're Underestimating AI's Productivity Impact — With Ethan Mollick ·
Robert Kaplan · Goldman Sachs
AI adoption will shift job mix: fewer programmers, more client-facing roles; narrowly defined jobs are at risk.
Kaplan says that he sees this among clients, in Goldman's own business, and among small businesses. He declined to comment on any single company. He expects fewer programmers, with more people covering clients, building relationships, and focusing externally. He argues that individual workers who define their jobs narrowly will find it tough, and that they will need to be flexible and able to read, write, communicate, debate, and build relationships.
“I think the AI adoption phase will change the mix of businesses... There are going [to] be fewer programmers, but I think you're going to have more and more people covering clients, building relationships, externally focused.”at 8:11
Bloomberg Talks: Goldman Sachs Vice Chair Robert Kaplan Talks Fed Meeting ·
Mark Cuban · Cost Plus Drugs
AI does not replace jobs; people who know how to use it replace those who don't.
Cuban argues that entry-level roles cannot simply be cut, because models are always behind the latest research and people need to stay in the loop, provide context and grow with the organization over time. He says the bigger risk is workers who do not learn to use AI, and that companies need to educate their C-suites on how models, agents and open versus closed models work before they can adopt AI well.
“AI doesn't replace jobs. People who know how to use AI replace the jobs of people who don't know how to use AI.”at 28:28
a16z Podcast: Mark Cuban’s Plan to Make Healthcare Affordable ·
Michael Batnick · Ritholtz Wealth Management
AI labor impact is not yet visible in data, but calling the fears overblown is premature.
Michael agrees that layoffs and claims remain low and AI has not yet shown up in the data. He thinks it is premature to call the fears overblown. He cites a Goldman finding that AI adoption among US firms now shows a statistically significant negative correlation with employment growth, which he reads as a sign the impact is spreading beyond tech.
“all of the AI fears overblown, not happening. I still think that is way premature.”at 30:35
Animal Spirits: Why Baby Boomers Have All the Money (EP. 488) ·
Ben Carlson · Ritholtz Wealth Management
Surprised AI is not yet showing in labor data; the job market is still very strong.
Ben cites an unemployment rate of 4.2%, a level never seen in the 1980s and not seen in the 1990s until 1999. Job openings are higher than in all of the 2010s, and initial claims are near record lows. Given where AI models are and the predictions made about them, he finds it surprising that AI is not yet showing up in labor data.
“I am still really surprised by these labor market numbers. If you think about where the models are and the predictions people made, it is surprising that we're not seeing more of this.”at 30:47
Animal Spirits: Why Baby Boomers Have All the Money (EP. 488) ·
Ben Carlson · Ritholtz Wealth Management
AI productivity gains show up in company revenue per head but not yet in aggregate US productivity data.
Carlson says companies are seeing productivity gains because revenue is growing faster than headcount, so they are doing more with the same staff rather than more with less. He notes this is still not visible in general economic productivity statistics. He argues the economy adjusts like a slow-turning battleship, pointing to how quickly remote work spread, so AI's economy-wide effect will take longer than people expect. He thinks people keep pushing the timeline out and suspects the payoff may be a 2030s story.
“It's more with the same. You are seeing productivity boost because revenue is growing faster than headcount... it's really not showing up in the general economic productivity numbers yet.”at 33:58
Animal Spirits: Why Baby Boomers Have All the Money (EP. 488) ·
Mark Cuban · Cost Plus Drugs
AI will not replace doctors, but will create jobs as translators between AI output and patients.
Cuban says he will never replace doctors and that trying would be a mistake. Latency and the cost of processing, even as compute gets cheap, mean patients still need someone who knows which questions to ask and which variables matter. A human with all five senses can read context, such as a crying family member, that a robot on video cannot. He expects medical school training to change, with doctors learning to use tools like OpenEvidence and to translate a patient's DNA data and the model's output into something the patient understands. He also expects a new job category of AI translators who extract the novel data a patient's model needs and make the AI's output valid for an individual.
“But I'd rather have a human there with all five senses being able to take a look and ask questions... And so I don't think ever that we'll replace doctors and we shouldn't even try.”at 40:52
a16z Podcast: Mark Cuban’s Plan to Make Healthcare Affordable ·
Julie Yoo · Andreessen Horowitz (a16z)
Cheaper AI care advice will increase demand for physicians, who will shift toward physician-scientists.
Yoo argues that as care advice becomes more abundant, more people will demand real-life healthcare services, so the country will need more doctors. She says today's doctor role is largely rote, such as checking quality measures, and that personalized drugs could be one of the most disruptive forces for care delivery. In her view, the job could become that of a physician-scientist who collects novel data and generates insights at the edge of knowledge about how individuals respond to therapies. She also expects longitudinal wearable monitoring, such as daily blood pressure, to deepen that individual data.
“I think we're gonna need more doctors in the future because as care advice becomes more abundant, more people are gonna demand healthcare, actual, like real life healthcare services.”at 43:53
a16z Podcast: Mark Cuban’s Plan to Make Healthcare Affordable ·
Gary Gensler · MIT Sloan School of Management
More optimistic about AI productivity gains over 5-10 years, though data centers may be overbuilt.
Gensler says some at MIT think AI will bring only modest productivity gains and significant labor disruption. He is more optimistic and expects productivity gains over the next five to ten years. He qualifies this by noting that the buildout could still mean some data centers have been overbuilt, so the productivity upside does not rule out an investment bust.
“Some think there's only gonna be modest productivity gains and there'll be significant labor disruptions. I'm more optimistic about the productivity gains over the next five to ten years”at 14:28
Bloomberg Talks: Former SEC Chair Gary Gensler Talks AI Boom & More ·
David Solomon · Goldman Sachs
AI automates tasks but mainly makes skilled workers more productive; new jobs should emerge over a decade or two.
Solomon accepts that AI will disrupt and automate work, and the open question is the pace. He argues the US economy is dynamic, creating and destroying about 30 million jobs a year and generating a net gain of about a million, with many jobs coming from small businesses. He says AI mostly makes smart people more productive rather than eliminating their roles, so white-collar work changes rather than disappears. He points to his own early career and to Goldman's analysts today, who do different work and are far more productive without being fewer in number. He expects new jobs to offset losses over the next decade or two. He flags a near-term risk: if the pace of change is fast, the gap between jobs lost and jobs created could widen, and policy action may be needed to soften the disruption.
“a lot of what this technology does is it makes smart people more productive. So when people talk about white collar jobs, just because the technology makes them more productive, it doesn't mean the job goes away.”at 7:20
Goldman Sachs Exchanges: Goldman Sachs Chairman and CEO David Solomon on AI: Implementation, Accountability, and Jobs ·
Daryl Fairweather · Redfin
Big Tech firms like Amazon and Microsoft are cutting headcount as AI reduces reliance on workers.
Amazon has mostly halted hiring, and Microsoft is offering buyouts to 60,000 employees. She reads this as legacy tech downsizing in the AI era and trying to reduce reliance on workers. This contrasts with San Francisco's AI companies, which are not hiring much but are enriching their employees and investors. Seattle's legacy-tech housing demand has therefore faded.
“Amazon has halted hiring for the most part, and Microsoft just announced that they were going to try to buy out 60,000 employees. So they are downsizing in the age of AI trying to figure out how AI can reduce their reliance on workers.”at 19:11
The David Lin Report: Housing Shock: Biggest Seller/Buyer Gap In History | Daryl Fairweather ·
Robert Kaplan · Goldman Sachs
AI lets firms grow revenue 50% with the same headcount, shifting the mix of people rather than cutting them.
Kaplan says AI is giving CEOs more confidence to plan for 30-50% higher revenues. Firms will redeploy existing people or hire new ones to cover more clients, and they may cut some internal functions. He expects revenue to be 50% higher in five years with the same number of people, maybe not fewer people but a different mix. He argues that face-to-face relationship and flexibility skills will become more valuable, and that people who view their careers narrowly will face more challenges.
“...five years from now, we're gonna have 50% more revenue with the same number of people. Maybe not less people, but a different mix of people.”at 28:32
Bloomberg Surveillance: Bloomberg Surveillance TV: October 27th, 2026 ·
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