AI in recruiting: How Semiconductor Forecasts, Tariffs and Talent Shifts Will Shape Hiring

I joined Bloomberg Technology to unpack a surprising week in semiconductors: Applied Materials’ cautious sales forecast that rattled investors, the upbeat tone from Lam Research, and the broader debate about whether tariffs and economic uncertainty are slowing purchases across the industry. In this article I’ll walk you through what executives told us, why big customers like TSMC and Samsung are pausing some spending, what it means for reshoring to the U.S., and why smart talent strategies — including AI in recruiting — are already becoming part of the solution for companies navigating this environment.

Where we are: a market caught between optimism and caution

There’s a clear divide in the market right now. On one hand you have companies like Lam Research that sounded “buoyant about future growth and revenue.” On the other hand, Applied Materials delivered a sales forecast that disappointed investors and sparked immediate concern. The key common threads are twofold: weakening demand in China for certain equipment refresh cycles, and a pause from a handful of very large customers who are sitting on the sidelines amid uncertainty.

Investors and sell-side analysts are debating: Is Applied losing share to peers, or is this a macro pause affecting everyone? The answer the company gave was deliberate — two separate categories of customers. In China, many chipmakers recently completed upgrades and aren’t buying additional equipment right now. But the larger, strategic customers that are delaying are primarily TSMC and Samsung, and their hesitation appears linked to trade policy uncertainty and tariffs.

Tariffs, trade policy and the ‘why now’ question

Executives used a simple, blunt phrase on calls: “tariffs is the big word we heard.” The current administration is negotiating trade deals and pushing for more domestic manufacturing. That policy stance merits a lot of attention — but it also creates timing headaches for companies that are planning multi-billion-dollar factory and equipment purchases.

As one of our guests put it bluntly: “Why do you wanna make a multibillion dollar commitment right now?” Put another way, manufacturing and equipment vendors are asking buyers to forecast demand and commit capital in an environment where the path of trade policy, subsidies, and cross-border tariffs is unclear. When you combine that with mixed macro data and cautious corporate sentiment, the result is a rational pause.

“Companies are holding off purchases. They're not sure exactly what the economic picture looks like in six months.”

China refresh cycles vs. global strategic customers

Understanding the difference between the China refresh cycle and strategic large-scale customers is essential. In China, chipmakers often follow refresh cycles of equipment — upgrade here, buy there — and the recent wave meant less immediate buying. That’s largely cyclical and can rebound.

By contrast, TSMC and Samsung are strategic global manufacturers. When they delay, it reflects larger strategic decisions, such as where to place capacity, how to plan supply chains, and how to react to geopolitical incentives. Applied Materials highlighted both dynamics in their discussion with investors: routine cyclical softness in China and a pause from large customers that is more policy-driven.

The U.S. manufacturing push: promise, but not immediate revenue

There’s another narrative that’s been getting louder: the political push to bring more semiconductor manufacturing to the United States. The administration’s agenda — through incentives and public statements — is to increase domestic capacity. Applied Materials and other equipment vendors talk about being involved with these plans. But the numbers on the table are instructive.

• Several firms and governments have discussed multibillion-dollar investments to bolster domestic capacity.
• Applied Materials, in conversations, has pointed to “hundreds of millions” in commitments linked to U.S. projects so far, not the multibillion-dollar figures some headlines imply.
• Applied still derives roughly 80% of revenue from abroad, and a full shift of revenue base to the U.S. will be gradual if it happens at all.

In short, the administration can influence where factories get built through subsidies and policy, but the actual dollars and timelines that translate into near-term revenue for equipment vendors are less dramatic than the political rhetoric might suggest.

What investors care about: bookings, visibility and the next few quarters

For public-market investors, the immediate concern is visibility. When a company like Applied revises its near-term outlook, it affects sentiment across the sector. Analysts are fielding multiple sell-side reports, trying to parse whether a forecast miss is company-specific or indicative of a wider demand slowdown.

Key metrics investors watch:

1. Bookings and backlog: Are orders coming in that haven’t yet been recognized as revenue?
2. Customer segmentation: Are the delays concentrated among a handful of top customers or spread broadly?
3. Geographic mix: How exposed is the company to China vs. Taiwan vs. the U.S.?
4. Capex guidance and commitments: Are customers committing to long-term factory builds or deferring?

How the talent question intersects with trade and manufacturing shifts

All of this — tariffs, reshoring, delayed purchases — has a human side. Building fabs, integrating new equipment, maintaining advanced process nodes: these tasks require skilled engineers and technicians. When countries and companies commit to creating new capacity, they often find the limiting factor isn’t just capital, it’s talent.

That’s where recruitment strategies matter. Firms expanding capacity or pivoting to new geographies need to hire quickly, often for highly specialized roles. Traditional hiring pipelines can be slow and brittle, especially in tight labor markets. To accelerate hiring without compromising quality, companies are turning to technology-powered approaches — most notably AI in recruiting.

AI in recruiting can surface passive candidates, automate initial screening, and match skill profiles to job requirements far faster than manual methods. For an equipment vendor or a new U.S. fab, that speed can be the difference between meeting a timeline and missing a critical ramp-up window.

Practical ways AI in recruiting is being used in the semiconductor ecosystem

Here are concrete examples of how “AI in recruiting” is finding its way into hiring plans for manufacturing and high-tech firms:

• Automated skill matching: AI parses resumes and technical profiles to find engineers with experience in, say, lithography, deposition, or process control systems.
• Cultural and retention predictions: Machine learning models can help predict which candidates are more likely to stay past the crucial first year in high-pressure ramp environments.
• Speeding up qualification: AI-driven chatbots handle initial candidate screening, freeing senior engineers to focus on higher-value interviews.
• Localization and relocation optimization: For firms shifting operations to the U.S., AI models can identify regions with clusters of relevant talent and forecast relocation likelihoods.

These tools won’t replace human judgment, but they augment capacity and reduce time-to-hire — a vital advantage when building out critical manufacturing capabilities under political timelines.

Risks and caveats: AI in recruiting isn’t a magic bullet

It’s important to be realistic. AI in recruiting brings benefits but also risks. If models are trained on biased datasets, they can perpetuate inequities. If companies use AI to push hiring faster without cultural fit or adequate onboarding, retention suffers. And when roles require rare domain expertise, nothing substitutes for domain-savvy interviewers.

So the recommendation to executives is simple: use AI in recruiting to scale the front end of hiring and surface candidates, but preserve rigorous technical evaluation processes and invest in onboarding. That combined approach preserves quality and accelerates ramp-up.

Scenarios for the next 12 months

Based on the current signals — cautious forecasts, policy-driven reshoring talk, and cyclical softness in China — I see three plausible scenarios:

1. Quick rebound: Tariff fears moderate, large customers resume capex, and companies that paused orders restart. Demand normalizes and the equipment supply chain ramps smoothly. Talent demand spikes modestly; AI in recruiting helps meet needs.
2. Prolonged pause: Uncertainty persists. Customers delay new builds, revenue growth stalls, and suppliers push more conservative guidance. Hiring freezes could spread, and investment in talent slows.
3. Reshoring surge with talent gap: Policy incentives accelerate U.S. builds, but talent shortages create bottlenecks. Firms that had invested early in hiring infrastructure and AI in recruiting gain an advantage in staffing new fabs.

What should leaders do now?

For executives at equipment makers, chipmakers, and policy teams advising on reshoring, the short list of priorities is practical and straightforward:

• Maintain close customer dialogue. Understand which delays are tactical vs. strategic.
• Be conservative in near-term guidance but transparent about backlog and bookings.
• Invest selectively in U.S. projects where incentives and customer commitments exist, but don’t expect an immediate revenue sea change.
• Build hiring playbooks that combine human expertise and technology: upskill internal recruiters, partner with universities and vocational programs, and deploy AI in recruiting to scale candidate discovery and screening.

Conclusion: uncertainty isn’t paralysis, it’s preparation

Applied Materials’ forecast rattled markets because it highlighted both cyclical and structural forces at work: China refresh cycles fading in the near term, and large strategic customers pausing amid trade policy uncertainty. The administration’s push for more U.S. manufacturing is real, but translating commitments into immediate revenue will take time and depends on where money and talent flow.

That’s why the human element matters so much. Whether firms face a quick rebound, a prolonged pause, or a reshoring surge, the ability to hire the right people quickly will determine who wins the next phase of semiconductor expansion. In that context, AI in recruiting is not a silver bullet — but it is a practical, high-impact tool to reduce time-to-hire and connect scarce talent with high-priority projects. Companies that combine policy awareness, disciplined capital allocation, and modern hiring practices will be best positioned to navigate whatever comes next.

If you want to discuss specific hiring strategies or how to evaluate AI in recruiting vendors for technical hiring, I’d be glad to dig deeper — these are the operational decisions that will determine whether policy announcements turn into thriving manufacturing footprints or just headlines.