September 18, 2026 - US Business News

Lorraine D’Alessio on Why the First 30 Days After Identifying a Candidate Matter

US Business News Staff on September 18, 2026

By: Santiago Miller

The difference between a company that approaches immigration strategically and one that treats it as a compliance function is not most visible in the quality of the legal filings or the experience of the attorneys involved. It’s most visible in what happens in the first 30 days after a candidate is identified, before any offer has been extended, before any visa application has been initiated, before any of the formal legal process has begun.

In that early window, the decisions that will shape everything downstream are either being made consciously or being left to default. Lorraine D’Alessio has spent her career watching how that period unfolds differently depending on whether a company has integrated immigration into its talent strategy or left it to surface only when a formal request arrives at the legal department’s desk.

What Strategic Companies Do Immediately

The biggest observable difference is that a company with a strategic approach to immigration starts asking immigration questions immediately rather than waiting for an offer to be accepted or a start date to be set. As soon as a candidate is identified as a serious prospect, the analysis begins. What are this person’s qualifications? What is the proposed role and how is it structured? Where will the work be performed? What is the timeline the business is working toward? What immigration pathways exist given those facts, and which is most likely to serve both the business and the candidate well over the relevant time horizon?

That early analysis changes the entire trajectory of what follows. It can reveal that the most straightforward pathway requires a timeline adjustment that the business can accommodate if it knows early enough. It can identify that a particular candidate’s circumstances open options that wouldn’t be available to someone with a different background, which might affect how the role is structured or what the offer looks like. It can surface potential complications early enough to address them before they become constraints on a business decision that has already been committed to.

Where the Advantage Compounds

The benefit of early immigration analysis doesn’t stay contained to the individual hiring decision. It compounds across every international hire the organization makes, building institutional knowledge and decision-making capability that improves over time. A company that consistently asks the right questions at the beginning of a hiring process develops an organizational fluency with international talent strategy that competitors who approach it reactively simply cannot match.

That fluency shows up in retention. International employees who see that their immigration path was thoughtfully considered as part of the organization’s planning for their future respond differently than those who discovered their status was managed as an afterthought. It shows up in candidate attraction. Strong international candidates who have options will gravitate toward organizations that demonstrate they understand what it takes to support someone building a career across borders. And it shows up in the ability to move talent where the business needs it, which in a globally operating organization can be one of the most significant competitive capabilities available.

The Ten-Year Picture

Lorraine argues that if American businesses consistently adopted this approach to immigration strategy, the US workforce would look meaningfully different within a decade. Fewer strong candidates would be lost to preventable immigration problems that nobody thought to anticipate. International employees would have clearer long-term paths and stronger connections to the organizations they chose to build their careers with. And the institutional knowledge required to navigate an increasingly complex global talent market would be built into the way American companies make decisions rather than outsourced to specialists who operate outside the business context where those decisions get made.

That future is available to any organization willing to treat the first 30 days differently. The investment required is not primarily financial. It is a shift in timing, in the questions that get asked, and in whose responsibility it is to ask them.

The first 30 days set everything else in motion. The Global Advantage by Lorraine D’Alessio is available now on Amazon.

Disclaimer: This article is for general informational purposes only and does not constitute legal or immigration advice. Immigration requirements vary by case and may change. Employers and candidates should consult a qualified immigration attorney regarding their specific circumstances.

Impostor Syndrome in Tech Is More Complicated Than You Think. Ines Pavon Eternod Has Coached Through Both.

US Business News Staff on September 18, 2026

By: Dar Dowling

Psychologists Pauline Clance and Suzanne Imes coined the term “impostor phenomenon” in 1978: a persistent belief that you’re less competent than others perceive you to be, despite clear evidence of your accomplishments, paired with a fear of eventually being exposed as a fraud.

That’s the version almost everyone recognizes. A high performer who has earned their credentials and their role, who has the evidence of their own capability right in front of them, quietly believes they don’t really belong there. That they got lucky. That eventually someone will see through it.

That version is real and common, and Ines works with it regularly in her coaching practice. But she has also encountered a version that reaches past the original definition, one that has nothing to do with discounting evidence of competence. It rarely gets called impostor syndrome at all but does just as much damage.

Two of the Versions She Has Seen

Two patterns stand out from the several Ines has encountered through her coaching work with Tech professionals, worth walking through side by side because they look almost nothing alike.

The first is the familiar kind: doubting your own skill despite the evidence in front of you. A client she calls Fernando was a Cloud Solutions Consultant who felt there was nothing out there for him beyond the sales-hunter roles he’d held for more than 15 years. He compared himself unfavorably to peers in Tech and believed he lacked the experience for the Account Manager work he was drawn to, which centered on relationship building, solving client pain points, and ongoing partnership.

When Ines looked at how Fernando actually worked, the evidence told a different story. His sales approach already mirrored Account Manager skills. The resume they eventually drafted together, framed around relationship building, collaboration, roadmap discussions, and client advocacy, reflected work he had already been doing. He had been discounting evidence that contradicted the story he was telling himself about what he was and wasn’t capable of.

The second is subtler, and it rarely gets called impostor syndrome at all: a belief about yourself that isn’t built on missing evidence, because there was never any evidence to begin with. A client she calls Swati felt she could never turn down work or ask for anything she needed, from peers, stakeholders, managers, or leadership, because it felt selfish. Ines pulled up the dictionary definition of selfish: concerned excessively or exclusively with oneself, seeking one’s own advantage without regard for others. When she asked Swati if that applied to her, Swati immediately said no. So the question became, if not selfishness, then what is it.

At first Swati couldn’t name it. Over time, she traced the belief back to something more specific, the conviction that being paid for her work meant she owed everyone a yes and had no right to ask for anything in return. That belief was not true. It had never been true. But it had been operating in the background of every professional decision she made.

The Tool That Starts Shifting the Pattern

Whichever version is at play, Ines encourages her clients to try the same simple daily practice to start shifting it, one that takes less than five minutes but tends to build something significant over time. At the end of the day, either in writing or just mentally, a client asks themselves one of three questions. What went well today? What impact did I have? What am I proud of?

The point is not gratitude journaling for its own sake. It is building an evidence base. After a couple of months of that practice, the more important question becomes available: Is there evidence I have been ignoring or mislabeling? That question is where the real work happens. Fernando had years of evidence he’d been discounting. Swati had a belief she’d never actually tested against reality. The practice creates the conditions to finally look at both honestly.

What This Has to Do With Tech Specifically

Ines works primarily with Tech professionals for a reason that goes beyond her own background. The Tech industry has specific conditions that make impostor syndrome both more common and harder to name. High performers surrounded by other high performers. Environments where moving fast and appearing certain is rewarded. Cultures where asking for what you need can feel professionally risky. And a job market right now that is genuinely difficult, where a lot of people find themselves hiring for their own team while also quietly job hunting themselves, and where there is no silver bullet for finding a new role despite what a lot of LinkedIn content would have you believe.

Ines doesn’t pretend otherwise. That honesty, about what is hard and why, is part of what her clients describe as most useful about working with her.

If either version, doubting evidence you already have, or carrying a belief about yourself that was never true to begin with, is quietly running the background of your professional decisions, Ines offers a complimentary intro call at coachwithines.com. What happens after that first conversation is entirely up to you.

AI Data Center Cooling Drives PFAS Production Expansion

US Business News Staff 2 on September 18, 2026

Major PFAS producers are expanding capacity as AI infrastructure increases demand for chemicals used in data-center cooling, semiconductor manufacturing and battery materials. Companies including Chemours, Daikin and Arkema are expanding PFAS-related operations, while some newer cooling systems use fluorinated chemicals to manage heat from high-performance computing equipment.

Key Takeaways

ChemSec identified data-center cooling, semiconductor manufacturing and lithium-ion battery materials as major sources of PFAS demand.
Chemours is developing PFAS-based products for data-center cooling and expanding production of PFAS refrigerants.
Daikin plans to triple its PFAS capacity in response to semiconductor demand, according to ChemSec’s report.
Arkema is expanding PFAS production in North America and Asia.
ChemSec says some newer cooling systems use fluorinated chemicals instead of water to remove heat from data-center equipment.

AI Data Center Cooling Increases Demand for PFAS

ChemSec’s analysis identifies AI data-center cooling as one of three demand sources contributing to expanded PFAS production. Semiconductor manufacturing and lithium-ion battery materials are the other two uses identified in the report.

PFAS, or per- and polyfluoroalkyl substances, are a large group of fluorinated chemicals. Their resistance to heat and chemical breakdown makes some PFAS useful in industrial applications, including cooling systems and semiconductor manufacturing.

The cooling application relates to the amount of heat produced by high-performance computing equipment. Newer liquid-cooling approaches can use fluorinated chemicals in systems designed to remove heat from servers while reducing the amount of water used for cooling.

ChemSec said the world’s largest PFAS producers are increasing capacity in response to demand connected with AI infrastructure. The organization’s September analysis examined the production plans and PFAS exposure of major chemical manufacturers.

The connection between AI infrastructure and PFAS production does not apply only to data-center cooling. ChemSec’s analysis also identifies semiconductor production and battery materials as significant applications, making the reported capacity increases relevant to several parts of the technology supply chain.

Recent investment in semiconductor capacity has also been tied directly to AI computing demand. U.S. semiconductor manufacturing expansion has included facilities and technologies serving data-center and specialized computing applications.

Major Chemical Producers Expand PFAS Capacity

Chemours is among the companies identified in the ChemSec analysis. The U.S. chemical manufacturer produces and uses multiple PFAS substances, and ChemSec estimates that between half and two-thirds of the company’s $5.8 billion in revenue comes from PFAS production.

Chemours is also developing products intended for data-center cooling while expanding production of PFAS refrigerants, according to the report. The company launched additional refrigerants in August as it continued developing products for cooling applications.

Daikin is another major producer included in the analysis. ChemSec reported that the Japanese company plans to triple its PFAS capacity in response to semiconductor demand. The reported expansion therefore covers semiconductor applications in addition to data-center infrastructure.

Arkema is also expanding production, with activity planned in North America and Asia. The company is a major materials manufacturer whose fluorinated products are used in industrial and technology applications.

The capacity plans identified by ChemSec differ by company and application. The report links them collectively to demand from data centers, semiconductor manufacturing and battery materials rather than attributing every planned expansion exclusively to AI cooling.

The capacity additions also fit into a larger buildout of technology infrastructure. Intel, for example, has reported increased investment in manufacturing capacity connected to enterprise demand for AI-related data-center processors.

Fluorinated Cooling Systems Reduce Reliance on Water

Some data-center cooling systems use fluorinated chemicals in place of water. The approach is associated with two-phase cooling, in which a liquid absorbs heat and changes into vapor before condensing back into liquid.

PFAS-based two-phase cooling remains a specialized application rather than the dominant cooling method across data centers. ChemSec said most data centers still rely primarily on air cooling, while single-phase liquid cooling that does not use PFAS is also widely deployed.

Single-phase systems can circulate liquids such as water, glycol or synthetic fluids through cooling equipment without requiring the fluid to evaporate. Direct-to-chip systems are one example, with liquid moving through sealed channels around server components to carry away heat.

Two-phase systems use the heat-transfer properties of low-boiling-point fluids. ChemSec said fluorinated chemicals can be used in these systems because they evaporate at relatively low temperatures, allowing them to absorb heat directly from equipment.

The different cooling approaches mean that PFAS demand cannot be equated with overall data-center cooling demand. The ChemSec report connects PFAS production increases to the cooling segment, while its technical analysis says PFAS-based cooling is still a niche technology.

Water consumption is one factor in cooling-system selection. Data-center projects also require large amounts of supporting infrastructure, including electrical equipment and power capacity.

Semiconductor Manufacturing Adds to PFAS Demand

Semiconductor manufacturing represents another source of PFAS demand identified by ChemSec. Fluorinated materials are used in semiconductor production because their chemical and thermal properties support manufacturing processes involving advanced electronic components.

Daikin’s planned capacity increase is specifically linked in the ChemSec report to semiconductor demand. The company plans to triple its PFAS capacity, making chip manufacturing an important part of the reported expansion.

The report also identifies lithium-ion battery materials as a third major demand source. That means the production capacity being added by chemical manufacturers can serve multiple technology industries rather than a single AI application.

AI Data Center Cooling Drives PFAS Production Expansion

Photo Credit: Unsplash.com

ChemSec’s analysis therefore connects PFAS manufacturing with several parts of the technology supply chain. Data-center cooling provides one application, while semiconductor production and battery materials create separate industrial requirements for fluorinated chemicals.

The distinction is relevant to companies assessing chemical supply requirements. A manufacturer’s capacity expansion may support several end markets simultaneously, making it difficult to attribute a particular production increase solely to data-center construction or AI computing. ChemSec’s report identifies the combined sources of demand rather than assigning all additional capacity to one industry.

The semiconductor connection is also visible in U.S. manufacturing investment. Companies such as GlobalFoundries and Intel have reported investments tied to computing and semiconductor capacity, while memory manufacturers are expanding facilities and research connected to AI hardware.

Those projects require more than chip fabrication equipment. Semiconductor facilities also depend on specialized chemicals, materials, power systems, water systems and other industrial infrastructure. PFAS therefore represents one component of a much larger manufacturing supply chain.

Data Center Cooling Creates New Chemical Supply Requirements

ChemSec’s findings place cooling chemicals alongside servers, chips and other physical components required for AI infrastructure. The organization says major PFAS producers are expanding capacity as demand develops across data centers, semiconductors and batteries.

For data-center operators, the choice of cooling system determines the type of fluid and equipment required to remove heat from computing systems. Air cooling, direct-to-chip liquid cooling and two-phase immersion cooling use different technical approaches and materials.

Chemours has specifically developed products for the data-center cooling market. The company has described its cooling products as part of its effort to supply systems used by data centers and other facilities requiring cooling equipment.

The use of PFAS in cooling has also prompted scrutiny of the chemicals involved. In July, 17 environmental organizations asked the Environmental Protection Agency to reject Chemours’ application to fast-track Opteon 2P50, a PFAS chemical proposed for data-center cooling. The groups cited concerns about potential health and climate risks.

Chemours disputed those concerns, according to the report, saying the cooling system operates as a closed loop and that the amount of gas escaping during operation is low. The company has continued developing and introducing refrigerants for cooling applications.

ChemSec has also pointed to alternatives to PFAS-based cooling. Its technical analysis says single-phase PFAS-free liquid cooling is already widely used and identifies water, glycol and other fluids as alternatives. It also describes natural refrigerants including carbon dioxide, ammonia, isobutane and propane as commercially available options for certain cooling applications.

The cooling market therefore includes multiple technologies with different fluid requirements. PFAS-based systems represent one specialized approach within that market, while other cooling methods are already deployed across data-center infrastructure.

The physical infrastructure required for data centers also extends beyond cooling equipment. Financing assessments increasingly include technical, environmental and construction considerations, alongside conventional financial analysis.

For chemical manufacturers, the reported capacity expansions connect PFAS production to several technology markets at once. For data-center operators, the available cooling systems include both fluorinated and non-fluorinated approaches, each requiring different equipment and materials.

Frequently Asked Questions

What is AI data center cooling?

AI data center cooling refers to systems used to remove heat generated by high-performance computing equipment. These systems can use air, direct-to-chip liquid cooling or immersion-based approaches, depending on the facility and equipment.

Why are PFAS chemicals used in data center cooling?

Some PFAS compounds have properties that make them suitable for two-phase cooling, including relatively low boiling points and resistance to heat. These systems can use fluorinated liquids to absorb heat from computing equipment.

Which companies are expanding PFAS production?

ChemSec identified companies including Chemours, Daikin and Arkema among major PFAS producers expanding capacity. The reported expansions serve multiple applications, including data centers, semiconductor manufacturing and battery materials.

How are data centers using fluorinated cooling systems?

Some data centers can use fluorinated liquids in two-phase cooling systems. The liquid absorbs heat from computing equipment, evaporates and then condenses back into liquid within the cooling system.

What industries besides data centers use PFAS?

ChemSec identifies semiconductor manufacturing and lithium-ion battery materials as additional sources of PFAS demand. These applications contribute to the production-capacity increases reported among major PFAS manufacturers.

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