*Source: https://www.khan.co.kr/article/202509180600001

● AI Devastates Rookies Entry-Level Jobs Crash

AI Directly Hit ‘New Hires’: A 10-Minute Core Guide Covering Signals, Data, and Policies (Including: Lifetime Initial Wage Risk, Corporate HR Strategy, Policy & Investment Opportunities)

We’ve summarized the meaning and ripple effects of recent research showing a sharp decline in new hire recruitment at AI-adopting companies, all at a glance.This article contains 1) key data and interpretations of employment changes observed from 2015 to 2025, 2) immediate actionable strategies for companies, youth, and policymakers, 3) ‘hidden mechanisms’ and practical countermeasures rarely covered by mainstream media, and 4) opportunities and risks from an investment and economic outlook perspective.In particular, it presents ‘the structural and long-term costs of declining new hires’, ‘companies’ internal logic for preferring experienced hires’, and ‘policy designs immediately applicable as pilot projects’ with specific figures and implementation plans, which are rarely discussed elsewhere.

Timeline Summary — 2015→2025: Observed Changes and Key Data

2015~2021: This was a period of gradual introduction of pre-AI stages and the spread of automation.Companies reduced repetitive tasks through work automation, and routine tasks assigned to new hires began to shrink.2022 (ChatGPT launch, etc.): Generative AI rapidly spread, and the automation of tasks typically assigned to new hires, such as ‘content generation, summarization, and customer response’, became fully fledged.2023~2025: The commonly observed patterns in studies from Harvard, Stanford, KDI, etc., are as follows:Rate of decline in new hire recruitment at AI-adopting companies: From a maximum of 7.7% quarterly (general sample) to an average quarterly decrease of about 40% in some sectors like wholesale and retail.During the same period, experienced (mid-to-high skilled) hiring either increased or remained stable.Age/Job-specific effects: Cases reported of employment for younger individuals aged 22-25 declining by approximately 13% in jobs with high AI exposure.Data sources: Big data from companies, resumes, and job postings (tens of millions of records), transaction-based statistics using payroll processing data (ADP).

Core Mechanism — Why Are ‘New Hires’ Attacked First?

Focus on Task Structuring and Automation TargetsTasks predominantly performed by new hires, which are ‘rule-based, repetitive, and documentable’, are easily replaced by generative AI.Immediate Output vs. Onboarding Costs – A Shift in Corporate CalculationAI generates quick outputs, and the cost advantage of hiring new employees relative to the initial training and mentoring costs has disappeared.Specialization of Supervision and Verification RolesSafely operating AI requires problem-finding and adjustment capabilities, thus experienced personnel are preferred.Signaling EffectCompanies interpreting AI adoption as a signal of ‘proficient internal capabilities’ choose to preserve their internal career ladders while reducing external new hires.Consequently, the ‘preference for experienced hires’ is strengthened, narrowing the organizational entry ladder.

10 Important Points Rarely Covered by the Media

1) Cohort Effect (Lifetime Initial Wage Loss)The lack of initial job experience is highly likely to eliminate accumulated learning opportunities early in one’s career, leading to long-term wage disadvantages.2) Loss of Job Search Experience and Social CapitalA reduction in networks and understanding of work practices gained from entry-level positions curtails subsequent hiring and promotion paths.3) Regional Spillover of Demand ShockA decrease in youth employment triggers localized chain reactions in the housing, consumption, and education industries.4) Deepening Labor Market PolarizationAI-complementary personnel (experienced/skilled) receive a premium, while groups unable to enter early in their careers are likely to be drawn into low-value-added services.5) Corporate HR Redesign CostsInstead of reducing new hires, the costs of attracting and retaining experienced talent increase.6) Direction of Wage PressureSuppression of entry-level wages → rise in mid-to-high skilled wages → potential worsening of income distribution.7) Rising Value of Irreplaceable ‘Learning-Oriented’ JobsTasks requiring experimentation, training, and feedback are still advantageous for humans.8) Delay in Political and Social ResponsePolicies are often reactive, risking delayed responses until the impact on the youth demographic becomes visible.9) Corporate Recruitment Disclosure OpacityIf the correlation between AI adoption and the reduction in new hires is not officially disclosed, market and policy feedback will be delayed.10) Dilemma of Long-term Productivity vs. Short-term Cost SavingsEven if short-term labor costs are saved with AI, long-term innovation capabilities may be impaired due to a weakened future talent pipeline.

Corporate Practical Strategy — 9 HR & Organizational Design Checklist Items

1) Introduce a Mixed Hiring ModelManage the proportion of new hires and experienced hires through policy (e.g., a minimum of 20% new hires) to preserve the future talent pipeline.2) Design ‘Learning-Oriented Onboarding’ Rather Than Automated OnboardingReuse tasks automated by AI as practice data in the onboarding process.3) Secure Human-Verifier LayerDesign the quality verification role for AI outputs as a learning opportunity for early-career individuals.4) Shift Job DesignRedefine jobs as Capability-based (unit of competency) rather than Task-based (unit of work).5) Redesign Internships and ApprenticeshipsConvert simple task-delivery internships into project-based and performance-based learning.6) Expand Internal and External Education PartnershipsIntroduce job-experiential Micro-credentials.7) AI Adoption Disclosure & MonitoringDisclose hiring and job impact indicators quarterly to lower regulatory risks.8) Youth Employment IncentivesIncrease recruitment efficiency through performance-based bonuses or rotation and mentoring systems.9) Redefine KPIsDo not view a decrease in new hires merely as cost savings, but evaluate it as a ‘talent pipeline indicator’.

Policy Design — 7 Realistic and Actionable Proposals

1) Introduce ‘Youth Employment Credit’ for AI-Adopting CompaniesConditions: AI adoption declaration + tax credit for a portion of wages if new hires are maintained for 2 years (e.g., 20% of monthly wages, up to 6 months).2) Youth-Exclusive Job Transition SubsidiesIf companies design intangible skills (on-the-job training) programs for new hires, the government supports a portion of the training costs.3) Mandate Recruitment DisclosureMandate disclosure of AI adoption status, scope, and trends in hiring by age group to enable monitoring.4) Introduce Micro-credentials & Point SystemProvide tools that lower entry barriers for new hires through short-term education linked to public certification.5) Region-Based Youth Job FundAllocate employment subsidies intensively to regions at high risk of youth consumption and housing collapse.6) Strengthen Public Sector ‘First Job’ ProgramsExpand pilot projects where government and local authority hiring compensates for a weakened private sector pipeline.7) Policy Experiment DesignVerify incentive effectiveness based on Randomized Controlled Trials (RCTs) to determine policy scale-up feasibility.

Economic Outlook (Medium-Term) and Macro Risks — 2025~2030 Scenarios

Baseline (Rapid Adaptation):Decline in new hires → short-term consumption slowdown, but adjustment within 2-3 years through re-education and wage compensation.Downside Risk (Cohort Isolation):Long-term unemployment of new hire-deficient cohorts leads to contraction in consumption and housing demand → deepening regional economic stagnation.Upside Risk (Capability Transformation):Increased investment in education and training leads to higher labor productivity and improved medium-to-long-term growth rates.Monetary & Fiscal Policy Implications:Short-term demand shocks should be addressed with fiscal measures (youth unemployment benefits, training investment), and central banks must separate inflation signals from employment indicators for judgment.

Investment & Business Opportunities — Where to Bet

Promising Sectors (Short-to-Medium Term)1) HR-tech & Lifelong Education Platforms: Surging demand for new hire re-education and onboarding solutions.2) Service companies providing apprenticeships and job training.3) AI Governance & Verification Tools: Human verifier tools and quality assurance solutions.4) Youth consumption & housing related recovery funds (regional redevelopment).Neutral & Caution Sectors1) Retail & Wholesale: Persistent restructuring risks due to automation.2) Customer Support & Call Centers: High potential for AI replacement → prepare for employment structure changes.Investment Strategy Tips1) Companies with secured talent pipelines (industry-academia cooperation, advanced internships) are long-term safe assets.2) Consider diversified investment in small and medium-sized enterprises likely to benefit from policies (youth employment credit, etc.).

Research & Data Measurement Proposals — Indicators Policy and Businesses Must Create Immediately

Essential Indicators (Quarterly Recommended)1) New hire ratio by age group (e.g., 22-25, 26-30).2) AI exposure index by job role and new hire change rate.3) AI adoption timing and scope by company (disclosure-based).4) Tracking changes in the new hire-experienced hire wage gap.Data Source Proposals1) Collaboration with payroll processing companies (similar to ADP).2) Job search & recruitment platform data (LinkedIn, JobKorea).3) Social insurance & employment insurance employment history.Recommended Research Design1) Causal verification using Difference-in-Differences (DID) + Instrumental Variables.2) Long-term observation of lifetime effects (earnings trajectory) through cohort tracking.

Practical Checklist — 8 Tips for Youth (Job Seekers), Parents, and Career Coaches

1) Make ‘AI verification and operation capability’ a standard skill in early career.2) Create a project-centered portfolio to position yourself as ‘immediately deployable’ even as a new hire.3) Prove your experience with micro-credentials and formal internships.4) Actively manage your network (mentors, industry connections).5) Prepare for potential job changes by acquiring digital literacy skills.6) Check public and private retraining grants and programs.7) During wage negotiations, base your arguments on ‘AI collaboration experience’ and ‘verification cases’.8) Prioritize the ‘learning value’ of early career from a long-term perspective.

In Summary — 3 Things to Act On Immediately

Companies: Immediately redesign your hiring portfolio.Policy: Pilot the introduction of youth employment preservation incentives upon AI adoption.Individuals: Immediately create an ‘AI proficiency’ + ‘learning proof portfolio’.

< Summary >

The spread of generative AI rapidly reduced new hire recruitment, while experienced hiring remained stable or increased.This phenomenon can lead to a loss of learning opportunities for early-career individuals, long-term wage losses, and regional/sector-specific consumption shocks.Companies must respond with HR redesign and learning-oriented onboarding, while policies should mitigate risks through youth employment incentives, education investment, and AI adoption disclosure.Investors and individuals should pay attention to HR-tech and education platforms, and AI governance solutions.Specific implementation plans (tax credit design, pilot projects, measurement indicators) are detailed in the main text.

[Related Articles…]The Future of Youth Employment Amidst AI Expansion — Policy Alternatives and Regional Impact AnalysisCorporate AI Strategy and Employment Structure Reorganization — A Practical Guide from an HR Perspective

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