The impact of artificial intelligence on the economy and labor market in the USA

New qualifications in demand: The labor market in the age of AI – A comprehensive analysis of the transformation of employment and business models

The introduction and rapid development of artificial intelligence (AI) has triggered an unprecedented transformation of the labor market in the United States, bringing with it both dramatic disruptions and new opportunities. While leading AI experts like Dario Amodei, CEO of Anthropic, warn of a “white-collar bloodbath” and predict that up to 50 percent of all entry-level office jobs could disappear, current data already shows concrete effects: In 2023, for the first time, almost 4,000 jobs were lost in the US explicitly due to AI implementations, while at the same time, job postings in the AI ​​sector have increased by an impressive 68 percent since the end of 2022. This development reveals a fundamental realignment of the economy, in which traditional employment structures are being disrupted, while new, technology-oriented jobs are emerging that require entirely different skill sets.

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The disruption of traditional employment structures

Threat to entry-level positions and career paths

The impact of artificial intelligence is particularly evident in the systematic undermining of traditional career paths for young professionals. Aneesh Raman, Chief Economic Opportunity Officer at LinkedIn, warns of a fundamental disruption of the career ladder, as AI increasingly threatens the types of positions that have historically served as entry points for young professionals. This development is especially worrying because it affects the “bottom rung of the career ladder,” thus disrupting the traditional path into a professional career.

An analysis by SignalFire, which evaluates career data from over 600 million employees and 80 million companies on LinkedIn, already reveals concrete effects: The 15 largest tech companies hired around 25 percent fewer university graduates in 2024 than in the previous year. The number of entry-level employees at startups also declined by 11 percent. The main reason lies in the nature of many entry-level jobs, which consist of simple, repetitive tasks – precisely the kind of work that generative AI can now efficiently perform.

Huy Nguyen, Chief Education and Career Development Advisor at Intelligent, explains that entry-level roles are particularly at risk, as these are the easiest to replace with AI. Many university graduates are typically hired for positions involving information-related tasks such as research, data collection, customer service, and general office support. While these activities are essential for young professionals to gain practical experience, they are also the easiest to automate with AI systems.

Decline in internships and training opportunities

The situation is exacerbated by the systematic decline in available internships, which traditionally serve as a crucial bridge between higher education and professional entry. Of the companies surveyed, 86 percent stated that they continue to offer internships despite technological advancements; however, five percent have already stopped filling internship positions because AI has taken over the interns' tasks. This development is particularly problematic because it creates a frustrating paradox for young professionals: they are not hired because they lack experience, but they cannot gain experience if they are not hired.

Major investment banks like Goldman Sachs and Morgan Stanley are already discussing reducing entry-level positions by up to two-thirds – including salary cuts. This development illustrates how even prestigious industries are rethinking their traditional recruitment models to take advantage of the efficiency gains offered by AI.

Industry-specific impacts and transformations

Technology sector as a pioneer of change

The technology sector is both a pioneer and a major beneficiary of AI-driven transformation. A comprehensive study led by Cisco with members of the AI-Enabled ICT Workforce Consortium—including Accenture, Google, IBM, Microsoft, and SAP—shows that 92 percent of IT jobs will change significantly or moderately due to advances in AI. Entry-level and mid-level IT professionals are particularly affected: 40 percent of mid-level positions and 37 percent of entry-level jobs will change significantly.

In all IT jobs, fundamental AI knowledge and AI ethics will become increasingly important, while certain traditional skills will decline in significance. Jobs such as AI/ML Engineer, Data Scientist, Project Manager, Software Engineer, and UX Designer will undergo the most dramatic changes. At the same time, other skills will become less important, including basic programming and language skills, traditional data management, content creation, documentation maintenance, SQL, and information retrieval.

The paradoxical situation is evident in the fact that while job postings in the AI ​​sector have increased by 68 percent, general job postings have decreased by 17 percent over the same period. The decline is even more drastic for IT positions not directly related to AI: these have fallen by 27 percent.

Finance and consulting industries under pressure

The finance and consulting industries are facing significant upheaval, as many analytical and advisory tasks can increasingly be taken over by AI systems. The World Economic Forum (WEF) identifies classic entry-level office roles such as market research or sales representative as being particularly at risk, with up to 67 percent of the latter's tasks potentially being replaced by AI. This development affects not only simple administrative tasks but also increasingly more complex analytical tasks that were traditionally considered safe from automation.

Legal services and professional services

The legal system is also undergoing a significant transformation through AI technologies. Companies like Prevail are developing AI-assisted platforms for witness testimony management and court reporting, revolutionizing traditional workflows in legal proceedings. These technologies enable AI-powered transcription services, automatic summaries of witness statements, and integrated presentation and evidence management tools, fundamentally changing the traditional roles of court clerks and legal assistants.

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Automation and efficiency improvements in various sectors

Extensive automation potential

Automation through AI is impacting nearly all sectors of the economy to varying degrees. According to McKinsey, between 39 and 73 million jobs could be lost to automation in the US by 2030, particularly in manufacturing, transportation, and administration. The Brookings Institution predicts that approximately 36 million Americans hold jobs with “high exposure” to automation—meaning that at least 70 percent of their tasks could soon be performed by machines using current technology.

Those particularly affected include cooks, waiters and other hospitality workers, short-haul truck drivers, and office assistants. McKinsey estimates that up to 30 percent of current work hours in the US economy could be automated—a trend accelerated by generative AI. This automation will not be evenly distributed: While generative AI improves the way STEM, creative, business, and legal professionals work without directly eliminating a significant number of jobs, other job categories will be more severely impacted.

Safety-critical areas and regulated industries

In safety-critical sectors like aviation, the picture of AI integration is more nuanced. Stefano Bonelli, project coordinator of MAHALO (Modern ATM via Human/Automation Learning Optimisation), explains that despite the potential for better airspace utilization, reduced traffic congestion and delays, and increased safety, current AI models do not yet possess the necessary precision for the stringent safety standards in aviation. The challenge lies in finding the right balance between automation and human oversight.

Neural networks consist of thousands of trainable parameters, making it virtually impossible to inspect and certify each one individually. Training the model itself also presents a challenge, as air traffic control is incredibly complex, and training an AI system would require considering every possible variable and every conceivable scenario.

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New business models and strategic partnerships

Corporate collaborations in the field of AI

The AI ​​revolution has triggered a wave of strategic partnerships between established technology companies and specialized AI providers. SAP, one of the world's largest software providers, has announced comprehensive collaborations with Google Cloud, Meta, Microsoft, Mistral AI, and NVIDIA to integrate generative AI into enterprise solutions. These partnerships aim to leverage AI-enabled technology to rapidly innovate and deliver more diverse outcomes.

Particularly noteworthy is the collaboration between SAP and Google Cloud, which aims to better predict and mitigate risks in supply chains using enterprise AI. The two companies are integrating Joule and the SAP Integrated Business Planning for Supply Chain solution into the AI ​​assistant, based on Google Cloud's Gemini models. This type of integration demonstrates how AI is not only transforming individual jobs but also revolutionizing entire business processes.

Specialized AI solutions for regulated industries

Capgemini, SAP, and Mistral AI have announced an expanded collaboration to provide a trusted environment for custom AI solutions in highly regulated industries such as finance and utilities. This partnership highlights the growing need for specialized AI solutions that meet the stringent compliance and security requirements of regulated industries.

Dassault Systèmes and Mistral AI have announced a partnership to combine virtual twins and sovereign cloud infrastructure with Large Language Models (LLM). This collaboration aims to make advanced AI accessible to industry in a trusted environment while protecting intellectual property. The new Outscale offering, “Large Language Models as a Service” (LLMaaS), delivers Mistral AI’s commercial Large Language Models through Outscale’s sovereign infrastructure, adhering to the highest security and compliance standards.

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Contradictory assessments and differentiated considerations

Optimistic perspectives and adaptability

Despite dramatic warnings of massive job losses, there are also more optimistic assessments of the impact of AI. A KPMG survey in the US shows that half of all employees believe automation helps them in their jobs. Nearly half said that automation brings new career opportunities. These results suggest that employees have overcome initial skepticism and concern about AI and are increasingly recognizing its potential.

John Doel, Principal in KPMG's US recruitment practice, explains that as acceptance grows, people are becoming increasingly familiar with the impact AI will have on their careers. Around seven out of ten respondents said they use automation tools at least weekly, and one in three confirmed using them daily. In comparison, only 28 percent of employees said they feared losing their jobs due to automation.

Productivity increase versus job destruction

Labor economist Melanie Arntz and work scientist Verena Nitsch agree that AI can make us more productive, but will also cost us some jobs. As long as AI only takes over parts of work processes, the new technologies generally lead to increased productivity. AI even creates new jobs: namely, those that make AI tools functional in the first place – for example, in data preparation and processing, data labeling, and data verification.

The World Economic Forum predicts that AI will displace 75 million jobs worldwide but create 133 million new ones. However, the organization Americans for Responsible Innovation (ARI) points out that economists are likely underestimating job losses due to AI because they overlook AI's flexibility to also take over newly created jobs. ARI President Brad Carson warns: “Silicon Valley says they are designing technology that can replace human labor, but many economists are still painting a rosy picture when it comes to America's job outlook.”.

Demographic and regional impacts

Unequal distribution of burdens

The effects of the AI ​​revolution will not be evenly distributed across all population groups. McKinsey predicts that an additional 12 million job transitions could be necessary in the US by 2030. As people leave shrinking jobs, the economy may shift toward higher-paying positions. However, workers in low-paying jobs are up to 14 times more likely to be forced to change jobs than those in the highest-paying positions.

Women are particularly affected, being 1.5 times more likely than men to have to change jobs. This trend could exacerbate existing inequalities and hinder social mobility. Young workers who traditionally enter the workforce through entry-level positions face particular challenges, as these are precisely the positions most affected by automation.

Regional differences and structural impacts

The changes will hit smaller cities particularly hard, especially in the Heartland and Rust Belt states like Indiana and Kentucky. These regions often have less diversified economic structures and more limited resources for retraining and economic transformation. The concentration of AI development and implementation in larger technology hubs could exacerbate regional inequalities.

McKinsey estimates that the net effect of automation will be negative without effective retraining programs, resulting in a loss of 19 to 23 million jobs. However, between 20 and 50 million new jobs could be created in the technology, healthcare, and education sectors. The challenge lies in the fact that many of these new jobs will require specialized skills, making comprehensive retraining essential.

AI and the American Dream: Will technology lead to division or inclusion?

The impact of artificial intelligence on the US labor market paints a complex picture of profound transformation, presenting both dramatic challenges and significant opportunities. The evidence clearly indicates that we are at the beginning of a historic upheaval of the world of work, unprecedented in its scale and speed. While the most pessimistic forecasts speak of a “white-collar bloodbath” and see up to 50 percent of entry-level jobs threatened, more optimistic analyses simultaneously show that AI can also create substantial productivity gains and new employment opportunities.

The central challenge lies in the unequal distribution of the impact: While highly skilled professionals in STEM fields, creative professions, and leadership positions can use AI as a tool to increase productivity, recent graduates and employees in routine jobs face existential threats to their employment prospects. The fact that 25 percent fewer university graduates are already being hired in the tech industry and that traditional career paths are systematically eroding underscores the urgency of proactive political and corporate action.

The emerging strategic partnerships between established companies and AI specialists demonstrate that the economy is already actively responding to this transformation and developing new business models. At the same time, the need for comprehensive retraining programs and a redesign of the education system is becoming increasingly apparent. The US faces the challenge of managing potentially 12 million career transitions by 2030, with particularly disadvantaged groups such as women and those with low qualifications being disproportionately affected.

Ultimately, the success of the AI ​​transformation will depend on whether the benefits of increased productivity can be distributed more broadly while simultaneously mitigating social disruptions through targeted interventions. The next few years will be crucial in determining whether the AI ​​revolution leads to improved job quality and living standards for the majority of Americans or contributes to further polarization of society.

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