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Microsoft Ai Jobs Shock: 60,000 Buyouts, Who's Next? | Eric Basmajian

https://www.youtube.com/watch?v=RCWt_zVSl0o

TLDR The labor market has low layoffs but weak hiring, leaving job seekers—especially young workers—with fewer opportunities and little wage growth. AI is lifting productivity in some industries, but it’s unclear whether gains will raise incomes or lead to fewer jobs. Strong construction and manufacturing activity currently keeps near-term recession risk low, though uncertainty, weak housing, and potential Fed tightening could change that.

Key Insights

1. Read the labor market beyond the headline layoff numbers

Low layoffs do not necessarily mean the job market is easy to enter or navigate. Hiring and quits are also weak, so people who lose a job may take longer to find another, while workers have less leverage to negotiate higher pay. Companies may also shrink through retirements, buyouts, and attrition rather than formal layoffs. Job seekers should track hiring trends and time-to-find-work alongside unemployment and layoff figures.

2. Watch construction and manufacturing for early recession signals

Construction and manufacturing have historically shown stress early in many downturns, so they are useful sectors to monitor. Current non-residential construction and durable-goods manufacturing are receiving support from AI and data-center investment, while residential construction remains a weaker area. This mix suggests near-term recession risk is relatively low, but conditions could change if housing, construction, and manufacturing weaken together. Focus on activity and employment in these industries rather than home prices alone.

3. Treat early AI productivity gains as promising but uncertain

Preliminary data indicate productivity has improved since late 2022 in some sectors with substantial AI adoption, including information technology, finance, and professional services. The evidence is not conclusive: gains may partly reflect corrections to earlier overhiring, and these sectors account for only a portion of the workforce. Businesses should evaluate whether AI improves output and service quality in their own operations instead of assuming broad gains will follow. Workers can build practical AI skills while continuing to develop expertise that complements automation.

4. Track who benefits from productivity growth

Productivity gains do not automatically translate into higher wages or more secure jobs. The discussion estimates that most recent gains have flowed to corporate profits, with a smaller share reaching workers’ real incomes, while companies reinvest some profits in AI. If businesses produce the same output with fewer employees, displacement may occur before new jobs emerge. Workers and employers should therefore watch both output per worker and income per person, as well as hiring and wage trends.

5. Make job plans that account for structural change

AI-related displacement can differ from a typical business-cycle slowdown because workers may not find new roles in the same industry or location. New occupations and demand may take time to develop, making the transition especially difficult for new graduates and people in repetitive entry-level jobs. Young workers can improve their options by developing AI-related capabilities and considering opportunities in construction and manufacturing. When weighing jobs, also account for practical constraints such as student debt, starting pay, and the experience needed to advance.

6. Use real wages and affordability to understand consumer sentiment

People can feel financially squeezed even when they are employed and nominal wages are rising. If wage growth of roughly 3–4% is largely offset by inflation near 3%, real income gains remain modest and may fall short of what households expect. Over time, that gap can make housing, cars, and other major purchases feel less affordable. To assess household conditions, compare wage growth with inflation and consider how cumulative price increases affect everyday budgets.

7. Build flexibility into small-business hiring and investment

High policy and economic uncertainty can lead businesses to delay hiring, expansion, and capital spending. Small firms may have fewer resources than large companies to manage changing tariffs, supply-chain disruptions, or regulatory decisions, and each employee may play a particularly important role. Before committing to new costs, small businesses should assess demand, supplier exposure, and whether proposed automation has demonstrated measurable benefits. At the same time, monitor competitors’ use of AI, since falling behind could create pressure to adapt.

Questions & Answers

What is the current state of the labor market?

The labor market is characterized by low layoffs but especially slow hiring. Workers who lose jobs may take longer to find new ones, and companies are often reducing headcount through retirements, buyouts, and attrition rather than formal layoffs.

Which workers are most vulnerable in the current labor market?

Young people and job seekers are especially vulnerable because hiring is weak. Unemployment among people ages 16–24 rose about 3 percentage points as the labor market slowed, compared with less than 1 point for workers over 25.

Where is a recession most likely to begin, and how high is near-term recession risk?

The speakers say recessions have historically begun with stress in interest-rate-sensitive construction and manufacturing. Those sectors are currently adding jobs, supported in part by AI and data-center construction, so near-term recession risk appears low. Residential construction remains a mild area of weakness to watch.

What do the available data suggest about AI and productivity?

Preliminary Census Bureau survey data suggest productivity has risen since late 2022 in information technology, finance, and professional services, where AI adoption is higher. Trends elsewhere remain closer to historical norms, and the evidence is preliminary and may partly reflect companies correcting earlier overhiring. These sectors represent about 15% of the workforce.

Who is benefiting from productivity gains so far, and what could happen to jobs?

An estimated 80–85% of productivity gains are flowing to corporate profits, with the remainder going to workers’ real incomes. Companies are reinvesting some profits in AI. It remains uncertain whether future gains will raise wages or allow businesses to produce the same output with fewer employees, potentially increasing layoffs.

How could AI affect GDP and unemployment?

AI could raise GDP per worker and GDP per capita if it delivers lasting productivity gains. However, it could also cause structural unemployment if displaced workers cannot readily find jobs in other industries. New jobs and demand may take time to emerge, making the transition difficult even if the economy eventually adapts.

Do low initial jobless claims indicate that a major wave of unemployment is being missed?

The discussion says there is little evidence of that. Low claims appear to reflect genuinely low layoffs, and JOLTS layoff data corroborates the claims data. Surveys suggest most people who do not file expect to find work quickly, though multiple jobholding and part-time work have risen somewhat.

Why is consumer sentiment weak despite low layoffs?

Weak real-income growth and a cautious labor market are weighing on sentiment. Hiring and quits are low, limiting workers’ bargaining power. Wage growth of 3–4% is mostly offset by inflation near 3%, leaving real gains of about 1%—below the roughly 2–2.5% people have come to expect. This erodes perceived living standards and makes housing and durable goods feel less affordable.

What are small businesses reporting about hiring and investment?

NFIB findings cited in the discussion show that 32% of surveyed firms reported job openings, 17% planned to increase employment, and 22% planned capital outlays. Uncertainty was unusually high.

Why does uncertainty affect small businesses especially strongly?

Small businesses generally have less access than large firms to policy insights, lobbying, tariff waivers, and integrated supply chains. Erratic tariff policy adds to the difficulty of making hiring and investment decisions. Small firms may also be less likely to lay off workers preemptively because each employee is important, though competitive pressure from AI-using rivals could change that.

How is uncertainty affecting business decisions?

High uncertainty can cause businesses to pause expansion and hiring. The speakers argue that current economic indicators fit together better than many observers acknowledge, even though uncertainty remains elevated.

What advice was offered to young people entering the workforce?

Young people were encouraged to consider AI-related skills and opportunities in construction and manufacturing. The speakers also cautioned that AI may automate repetitive entry-level tasks, making it harder for new graduates to gain experience, and that student debt can limit their ability to accept lower-paying work.

What could put the economy at greater risk over time?

Continued Federal Reserve tightening could eventually weaken housing, manufacturing, construction, and employment, raising recession risks. The discussion also identifies government debt, deficits, and spending as structural pressures that could weigh on real wage growth.

Why is residential construction important to monitor?

Construction activity is more closely tied to jobs and recessions than home prices. Residential construction is weak, but so far that weakness has not outweighed strength in non-residential construction and manufacturing.

Summary of Timestamps

The labor market is in a weak-hiring, low-layoff environment. Formal layoffs remain below pre-pandemic levels, but slow hiring can make it harder for people who lose jobs to find new ones. Companies are also reducing headcount through retirements, buyouts, and attrition, which can leave younger workers and job seekers especially exposed.

Recent buyouts at Microsoft and a planned workforce reduction at American Express have raised questions about AI-related job losses. However, voluntary departures are not counted as formal layoffs, and it remains uncertain whether white-collar job losses will drive a future downturn. Historically, recessions have more often begun with stress in interest-rate-sensitive construction and manufacturing.

The speakers see near-term recession risk as low because construction and manufacturing are still adding jobs. AI and data-center investment is boosting non-residential construction and creating spillover demand for durable goods, even as residential construction remains a mild area of weakness.

Preliminary Census Bureau survey data indicate that productivity has risen since late 2022 in sectors that are adopting AI heavily, including information technology, finance, and professional services. The speakers caution that the evidence is early, may partly reflect corrections to earlier overhiring, and covers sectors representing only about 15% of the workforce.

An estimated 80–85% of recent productivity gains are going to corporate profits, with the remainder reaching workers through real-income growth. Companies are reinvesting some profits in AI, but it is unclear whether higher productivity will ultimately lift wages or allow businesses to produce the same output with fewer employees.

The conversation distinguishes GDP per worker from GDP per capita. AI could raise both measures if it delivers lasting productivity gains, as earlier technologies did, but that outcome is less reassuring if total output is produced with far fewer workers and average incomes do not rise.

AI may create structural unemployment when displaced workers cannot readily find jobs in the same industries. New roles and demand can take time to emerge, making the transition painful and politically difficult even if the economy eventually adapts. This differs from cyclical, frictional, and seasonal unemployment.

Low initial jobless claims appear to reflect genuinely low layoffs: survey responses and JOLTS data broadly support that reading. Multiple jobholding and part-time work have risen somewhat, but the evidence does not suggest that claims data are missing a major wave of unemployment.

Weak consumer sentiment is linked to modest real-income growth and a cautious labor market. Layoffs are low, but hiring and quits are also subdued, limiting workers’ bargaining power. Wage growth of 3–4% against inflation near 3% produces only about 1% real growth—below the roughly 2–2.5% people have come to expect.

The small-business survey showed that 32% of firms had job openings, 17% planned to increase employment, and 22% expected to make capital outlays, while uncertainty remained unusually high. Small firms may be more exposed to shifting policies because they have less access to lobbying, tariff waivers, and integrated supply chains.

Small businesses may be less likely than large companies to cut staff preemptively for AI, since each employee is important and productivity gains may be uncertain. But firms could face pressure to adopt automation if competitors use AI to reduce costs or win business.

High uncertainty can cause businesses to delay hiring and expansion. Young workers are particularly affected: unemployment among people ages 16–24 rose about three percentage points as the labor market slowed, compared with less than one point for workers over 25. The speakers suggest exploring AI-related skills and opportunities in construction and manufacturing.

Entry-level tasks may be especially vulnerable to automation, potentially making it harder for graduates to gain experience for future roles. Student debt can add pressure by limiting young workers’ ability to accept lower-paying jobs. The discussion also notes that a Federal Reserve rate hike could be manageable in the near term, though prolonged tightening could eventually weaken housing, construction, manufacturing, and employment.

For real wage growth in 2027, Eric points to structural pressures, particularly government debt, deficits, and spending, which he argues may weigh on the private sector. He also identifies residential construction as an important sector to monitor, emphasizing that construction activity—not home prices—is more closely connected to employment and recession risk.

Eric says current weakness in residential construction has not yet outweighed stronger non-residential construction and manufacturing. EPB Research continues to track how these sectors interact and sees some positive cyclical signals. The segment closes with information on following EPB Research and a brief viewer sign-up promotion.