On September 19, 2025, President Donald Trump imposed a $100,000 one time additional petition fee on new H-1B visa applications, effective from 12:01 a.m. Eastern Daylight Time on September 21, 2025, as part of non-tariff barriers (NTBs) designed to curb outsourcing and prioritise American workers. The new fee is set at $100,000 per petition. It is a one-time payment that must accompany or supplement the Form I-129 Petition for a Nonimmigrant Worker when filing for H-1B status. Despite some initial media reports suggesting it could be an annual or recurring fee (e.g., for the duration of the visa’s validity, such as three or six years), the official proclamation text indicates it is tied directly to the petition filing process, making it a single payment per applicable petition. Employers are required to remit this payment and retain documentation proving it has been made, which must be submitted with the petition.

This measure targets perceived abuses by IT firms and disproportionately affects India, which accounts for 71-73% of H-1B visas. Coupled with potential tariffs on foreign remote work, it could reshape global tech and services sectors by prompting operational reallocations, job shifts, and resource realignments.

Drawing from independent sources such as Reuters, the International Labour Organization (ILO), World Bank reports, academic papers, and expert critiques, this article examines the policy’s feasibility, sectoral effects, the role of AI and U.S. talent, balanced impacts on both nations, and a critical examination of the “brain gain” narrative for India—including the role of programs like MGNREGA in addressing underemployment.

Sectoral Impacts And Worker Vulnerabilities

Indian workers hold a dominant share of U.S. H-1B roles, with 20-25% of the 2.1 million Indian immigrants in the labor force dependent on these visas. The IT sector faces the highest exposure, with 30-50% of roles affected, followed by healthcare (10-20%), education (5-15%), and other services like finance and administration (15-25%).

Historical data from 2014 to 2025 shows IT (computer-related occupations) claiming 60-66% of H-1B approvals, healthcare around 4%, education 5-6%, and other services 24-31%. Projections for 2025 indicate this trend will persist, highlighting India’s IT-centric presence.

Reallocation—such as shifting work offshore, expanding remote setups, or diversifying operations—is highly feasible in IT (50% share), thanks to digital tools and India’s advanced infrastructure in hubs like Bengaluru and Hyderabad.

However, it’s largely impractical for non-IT sectors like healthcare, education and other services (50% share), which require physical presence for tasks such as patient care, licensing, or on-campus instruction. While partial remote options like telehealth exist, they cannot fully replace in-person roles.

Reallocation Strategies And Profitability

In the IT outsourcing industry as of 2025, the presumption that Indian companies like TCS and Infosys solely bear the brunt of H-1B visa sponsorship and related fees—now inflated by a $100,000 annual fee under the Trump administration—is oversimplified, as these costs are partially absorbed by the firms but often indirectly passed to US clients through higher billing rates, contract renegotiations, and onshore-offshore pricing models, potentially eroding Indian margins by 6-7% while increasing client project costs by 5-10%.

For instance, while Indian firms handle direct expenses like filing and legal fees (totaling hundreds of millions annually for thousands of approvals), they mitigate impacts by paying lower wages to H-1B workers and taking cuts from billable hours, though rising fees have prompted a 20-30% reduction in H-1B reliance and shifts toward remote work, which bypasses these burdens entirely and could boost margins by 10-20% through labor arbitrage (Indian salaries 30-50% below US equivalents).

However, this remote bypass faces significant risks from emerging US non-tariff barriers (NTBs), such as the proposed HIRE Act’s 25% excise tax on outsourced services and bans on tax deductions, which could make remote contracts 25% more expensive for US clients, diminish India’s cost edge by 10-15%, and threaten 20-30% of its $138-250 billion outsourcing revenue, particularly given US clients’ dominance (60%+ market share); additional NTBs like data localisation or security audits further undermine benefits, flipping presumed opportunities into potential threats of work starvation if legislative bans or far-right influences prevail.

Reallocating work to India amid these US curbs is far from cost-free or seamless, entailing 6-12 months and 5-10% of project value in setup costs for infrastructure, training, and compliance, plus ongoing inconveniences like time-zone differences, cultural gaps, and data security issues, making it challenging despite feasibility through captive centers, with demand potentially shifting to non-US markets but limited in scale due to America’s 50-60% revenue share for firms like TCS.

Furthermore, the reallocation claim overlooks how US policies inadvertently boost nearshoring to Mexico and Canada, which offer comparative advantages in hybrid models—such as tariff-free trade under USMCA, minimal time-zone issues, easier TN visas without lotteries, and 20% lower costs than India in some services—leading to a 20-30% boom in Mexican IT/manufacturing nearshoring from 2024-2025, reducing India’s appeal for diversified approaches amid geopolitical risks.

Overall, while strategies like offshore shifts and remotes could yield 20-30% savings and 1-2 year ROI through efficiency and arbitrage, these benefits primarily accrue to Indian firms (10-15% margin gains) and US clients (lower costs) but are tempered by mass layoffs (e.g., 42,000 jobs cut by top firms from 2023-2025 due to AI automation, potentially displacing up to 500,000 more) and heavy US dependency, making net manpower additions unlikely as companies prioritise reskilling and AI over expansion; if NTBs like the HIRE Act pass, savings could halve, favoring domestic or nearshore alternatives and challenging the reallocation and profitability options that ignore transition costs, shared burdens, and broader economic disruptions.

Leveraging AI And The U.S. Workforce

Of the $250-260 billion in combined outsourced and H-1B-related work (primarily IT), AI could automate 25-30% ($62.5-78 billion) through tasks like coding and data analysis. The existing U.S. workforce might handle 15-20% ($37.5-50 billion) despite talent shortages, with short-term training (3-6 months) adding 20-30% capacity and one-year programs contributing another 30-40% ($75-100 billion combined).

By 2025-26, the U.S. could achieve 70-90% self-sufficiency ($175-225 billion) via AI integration, existing skills, and reskilling efforts, reducing dependence on foreign labor.

Short- And Long-Term Effects On India And The U.S.

Short-Term (1-2 Years)

(a) India (Predominantly Negative): Remittances could decline by $10-20 billion (with the U.S. accounting for ~30% of India’s $100+ billion total), leading to 200,000+ job losses or worker returns. IT firm margins may erode by 5-10%, and GDP could dip by 0.5-1%, with non-IT sectors exacerbating migration disruptions.

(b) U.S. (Mixed): Companies may experience hiring delays and innovation slowdowns, but the policy could enhance local employment in entry-level roles. Persistent tech shortages might increase costs.

(c) Positives: India could see an initial “brain gain” from returning talent, accelerating local AI adoption; the U.S. benefits from lower outsourcing expenses.

Long-Term (3+ Years)

(a) India (Shifting Positive): Retained talent might add $10-20 billion to GDP through domestic innovation and infrastructure improvements. Outsourcing could strengthen, offsetting $5-10 billion in annual remittance losses via expanded operations.

(b) U.S. (Mixed): Greater self-sufficiency through AI and training could drive competitiveness and job growth (e.g., 17.9% in software roles), but talent gaps risk stifling expansion if global skills are lost. Tariffs may raise costs if they backfire.

(c) Positives: Both countries gain from economic diversification—India through robust local ecosystems, the U.S. via focused domestic workforce development.

These NTBs reflect a protectionist shift, favoring IT’s adaptability while straining non-digital sectors. Short-term challenges hit India harder, but long-term resilience could foster mutual benefits with cooperative trade policies.

Examining The “Brain Gain” Narrative In Depth

The policy’s potential to repatriate Indian talent has sparked optimism about a “brain gain,” including GDP boosts of $10-20 billion from retained skills and outsourcing growth offsetting remittance losses.

However, independent analyses from sources like Reuters, ILO, World Bank, Observer Research Foundation (ORF), BBC, and academic studies (e.g., IIT Madras reports, PubMed, Yale) suggest this is overstated.

Domestic challenges such as underemployment, limited innovation support, service-focused startups, AI’s job-displacing effects, and persistent reasons for emigration make seamless absorption unlikely. India remains less “lucrative” for dream jobs without systemic reforms.

Mass Underemployment in India

Official unemployment stands at 4-5% in 2025 (per ILO/World Bank models), but over 70% of economists in a Reuters poll deem it inaccurate, failing to capture underemployment.

Reports from The Wire indicate 28 million educated youth job-hunting and 100 million “discouraged workers” (mostly women). Youth unemployment reaches 15-20%, with educated individuals often in mismatched roles. All returning H-1B holders (e.g., AI engineers or others for whatsoever reason) could intensify competition in saturated white-collar markets, risking further frustration rather than job creation.

Limited Support For Innovation And Startups

India boasts the world’s third-largest startup ecosystem (159,000 firms by early 2025), but critiques highlight bureaucratic hurdles, short-term funding, and uneven infrastructure. Government schemes like Startup India offer limited seed capital (up to ₹50 lakh), but follow-on investment is scarce, with foreign VCs prioritising quick returns over R&D. Urban hubs thrive, but Tier-2 areas lag, limiting the ecosystem’s depth for returning talent.

Focus on Services Over Global Innovation

Most Indian startups emphasise service delivery (e.g., fintech, e-commerce) for rapid profitability in a consumer market, rather than innovative products like AI hardware or biotech. As noted by Piyush Goyal and analyses on Reddit and Medium, this stems from rote education and risk aversion. Exceptions like Freshworks or Ather exist, but the economy favors consumption over industrial R&D, hindering a shift toward global breakthroughs.

AI’s Role In Managing Demand

AI could automate 40-50% of white-collar jobs in India (per IMF, Research and Information System for Developing Countries (RIS), and entrepreneur reports), enabling firms to operate with fewer employees. While it may create 20 million new skilled roles by 2025, adoption is uneven, potentially displacing more jobs than it generates. Outsourcing via global capability centers (GCCs) offers growth, but remains service-oriented.

Why Indians Emigrate—And Why India Lags

Professionals leave for 3-5x higher pay, advanced R&D, better quality of life, and networks (per PubMed, CNBC, Yale studies). Due to inflated and fictitious 6% GDP growth (actual GDP of India is 4%) and despite tech hubs, infrastructure and opportunities obviously fall short. The fee hike may deter new H1-B Visa applicants from India and may force many of the existing ones to return under certain circumstances, but without reforms like easier re-entry and R&D incentives, talent could redirect elsewhere, turning “brain gain” into “brain pain.”

The Role Of MGNREGA In Addressing Underemployment

Amid discussions of returning talent and underemployment, the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), launched in 2006, serves as a key safety net. It guarantees 100 days of unskilled wage employment annually to rural households, focusing on asset creation like water structures and roads. Rolled out in phases (200 districts in 2006, nationwide by 2008), it addresses rural poverty and seasonal joblessness but faces criticism for implementation flaws, corruption, and masking broader economic issues.

Benefits include daily wages (linked to state minimums), worksite facilities, and unemployment allowances if work is denied within 15 days. No pensions or long-term security are provided. Minimum days can be as low as 1 (counting toward employment stats), with a maximum of 100 (or 150 in disaster areas). In national surveys like the Periodic Labour Force Survey (PLFS), even one day qualifies as “employed,” distorting underemployment figures. MGNREGA expenditure (0.3-0.4% of GDP) boosts government consumption and investment, but critics argue it inflates economic metrics without sustainable impact.

Women and marginalised groups (SCs/STs) participate disproportionately (women at ~60% by 2023-24), yet average days remain below 50 nationally due to rationing and delays. Real wages have stagnated since ~2014, often below market rates.

Inflation Of Numbers And Distorted Economic Narratives

Critiques from The Wire, Reuters economist polls (over 70% questioning data accuracy), BBC (2024), UNU (2024), and studies by Drèze & Somanchi reveal how MGNREGA inflates figures to portray a rosy economy, masking underemployment (15-20% youth joblessness per ILO) and structural issues.

(a) Fake Job Cards And Ghost Workers: Millions of bogus cards (e.g., 7.43 lakh deleted in 2022-23) overreport employment by 20-30%, enabling fund siphoning (e.g., UP scams in 2023-25).

(b) Bogus Work-Days And Unfinished Assets: Padded person-days include incomplete works (30-40% per audits), boosting totals artificially.

(c) Manipulation Of Unemployment Figures: Loose counting (1-day work as “employed”) hides distress, including 100 million discouraged workers, allowing claims of low 4-5% unemployment.

(d) GDP And Economic Distortion: Phantom expenditures inflate growth metrics, supporting “fastest-growing economy” narratives despite jobless growth, AI displacement, and stagnant wages.

While MGNREGA empowers women and builds rural resilience, reforms—such as combating corruption, increasing days to 200, and integrating skills training—are essential for genuine impact rather than PR-driven metrics.

The Road Ahead

President Trump’s imposition of a $100,000 one time additional petition fee on H-1B visa applications after 21st September, 2025, represents a pivotal escalation in U.S. protectionist policies, ostensibly aimed at prioritising American workers and curbing outsourcing abuses, but with profound ripple effects that extend far beyond immediate visa sponsorship costs. This measure, embedded within a broader framework of non-tariff barriers (NTBs) such as potential excise taxes on remote work and restrictions on tax deductions, underscores a strategic shift toward economic nationalism, disproportionately impacting India as the primary beneficiary of H-1B visas (71-73% share) and reshaping the global tech and services landscape in ways that demand nuanced evaluation.

As examined through independent lenses from Reuters, the ILO, World Bank, academic critiques, and expert analyses, the policy’s feasibility hinges on sectoral adaptability: the IT industry, comprising 50% of H-1B approvals, emerges as relatively resilient due to digital tools enabling offshore reallocation and remote setups, potentially yielding 20-30% cost savings and margin boosts for Indian firms like TCS and Infosys, albeit tempered by transition costs (5-10% of project value), time-zone challenges, and emerging NTBs that could erode India’s competitive edge by 10-15%.

In contrast, non-IT sectors such as healthcare, education, and finance—accounting for the remaining 50%—face insurmountable barriers to relocation, given their reliance on physical presence, licensing, and in-person interactions, exacerbating vulnerabilities for the 20-25% of Indian immigrants in the U.S. labor force dependent on these visas.

The interplay of AI and U.S. workforce development further complicates the narrative, with projections indicating that automation could displace 25-30% of outsourced IT tasks ($62.5-78 billion annually), while reskilling initiatives might enable the U.S. to achieve 70-90% self-sufficiency in these roles by 2025-26 through short-term training (adding 20-30% capacity) and longer programs (30-40%). This dual force not only mitigates U.S. talent shortages but also amplifies job displacement risks in India, where AI’s uneven adoption threatens to automate 40-50% of white-collar positions without commensurate new opportunities.

Short-term ramifications tilt negatively for India, with potential remittance drops of $10-20 billion (U.S. contributing ~30% of India’s $100+ billion total), 200,000+ job losses or repatriations, and GDP contractions of 0.5-1%, compounded by eroded firm margins (5-10%) and migration disruptions in non-IT fields. For the U.S., outcomes are mixed: while fostering local entry-level employment and reducing outsourcing dependencies, it risks innovation slowdowns, hiring delays, and cost hikes amid persistent tech gaps. Long-term prospects, however, offer glimmers of resilience—India could harness returning talent for domestic innovation, adding $10-20 billion to GDP through ecosystem enhancements and offsetting remittance losses via diversified outsourcing; the U.S. stands to gain from heightened competitiveness, with software job growth projected at 17.9% and economic diversification bolstering self-reliance.

Yet, the oft-touted “brain gain” for India warrants skepticism, as dissected through sources like ORF, BBC, Yale studies, and IIT Madras reports. Far from a seamless boon, repatriation confronts entrenched underemployment (15-20% youth rate, with 28 million educated job-seekers and 100 million discouraged workers), a startup ecosystem hampered by bureaucratic red tape, scarce R&D funding, and a service-oriented focus that prioritises quick profits over groundbreaking innovation.

Emigration drivers—3-5x higher salaries, superior quality of life, and global networks—persist, rendering India less “lucrative” without sweeping reforms like enhanced re-entry incentives, infrastructure upgrades, and a pivot toward product-driven entrepreneurship. AI’s job-displacing potential further undermines absorption, potentially transforming anticipated gains into “brain pain” as talent redirects to alternatives like Canada or Europe.

Integral to this discourse is MGNREGA’s role as a rural safety net, guaranteeing 100 days of unskilled work and aiding marginalized groups (women at ~60% participation), yet its flaws—corruption via fake job cards (20-30% overreporting), padded work-days, and lax employment metrics (one day counting as “employed”)—distort national narratives, inflating unemployment figures to a misleading 4-5% while masking structural distress. Critiques from The Wire, Reuters polls (70%+ economists doubting data accuracy), and UNU studies highlight how such manipulations bolster “fastest-growing economy” claims amid jobless growth, stagnant real wages, and AI-driven disruptions. Reforms, including anti-corruption measures, expanded days (to 200), skills integration, and transparent audits, are imperative to evolve MGNREGA from a PR tool into a genuine bulwark against underemployment, particularly for non-urban returnees.

Ultimately, this policy exemplifies the double-edged sword of protectionism: while safeguarding U.S. interests in the short run, it risks global talent fragmentation, higher costs for American firms (5-10% via passed-on fees), and unintended boosts to nearshoring in Mexico and Canada under USMCA advantages. For India, it signals an urgent call for diversification—reducing U.S. dependency (60%+ outsourcing revenue), investing in AI ethics and upskilling, and fostering inclusive growth to mitigate vulnerabilities. Both nations stand at a crossroads: collaborative frameworks, such as bilateral talent mobility pacts or joint AI R&D initiatives, could transmute these tensions into mutual prosperity, ensuring that protectionism does not devolve into isolationism but instead catalyzes equitable global innovation. As the dust settles, the true measure of success will lie not in visa denials or tariff walls, but in whether these measures propel sustainable workforce evolution or perpetuate cycles of displacement and disparity.