Artificial Intelligence and Job Automation: Challenges for Secondary Students’ Career Development and Life Planning

Abstract

Artificial intelligence (AI) technologies with human-level cognitive abilities are increasingly integrated into workplaces, posing risks of job displacement and redundancy. Understanding AI’s impact on job automation is thus essential, as it helps students understand which occupational roles are likely to be automated. However, there is a lack of coherent understanding of this topic due to the diverse research methodologies deployed, leading to the formation of fragmented and inconsistent insights. This article reviews career literature and global reports from expert sources (e.g., the World Economic Forum) to provide an overview of AI’s influence on job sectors and the skills students need to thrive in a technologically disrupted workplace. The findings emphasize the importance of developing human-centric skills.

1. Introduction

Career guidance holds a strategic position in the educational system by assisting students in making well-informed decisions regarding their future educational and career paths. Effective career guidance helps students recognize their strengths, values, and interests while also providing them with the essential skills needed for a seamless transition from school to the workplace [1]. Effective career guidance can help students develop the skills and knowledge necessary for the future job market, including an understanding of how technological advancements like artificial intelligence (AI)-induced automation affect career opportunities, enabling students to make informed choices and necessary adjustments about their career plans [1].

One primary motivation for students to pursue postsecondary education is to acquire cognitive and vocational skills valued by employers [1]. In some regions, the intense pressure to excel academically can lead to tragic outcomes, including student suicides, as matriculation exam results are often used as the only measurement of a job candidate’s cognitive abilities [2,3,4]. Even though research evidence has already shown that schoolteachers’ career-related care and support can help students thrive in such a stressful situation [5], the availability of career-related teacher support varies across education contexts due to a shortage of staff with knowledge about the world of work [1,6]. The advent of AI is expected to complicate the existing landscape by automating job tasks, thus challenging and displacing the traditional roles of human workers in the workplace [7].

Artificial intelligence refers to systems that demonstrate intelligent behavior by evaluating their environment and acting autonomously. This technology allows computers and machines to emulate human abilities such as learning, problem-solving, decision-making, and creativity [8]. Generative AI, for example, is one type of artificial intelligence technology [9]. The rapid progress of AI is expected to reduce the unique role of human labor in providing cognitive skills. This is because AI now surpasses humans in many cognitive functions, allowing for the automation of numerous tasks traditionally performed by human workers [10,11]. Given AI systems’ powerful learning and content creation capabilities, job automation has become a significant concern, potentially leading to job displacements as AI systems replace human workers as the primary providers of cognitive skills [10,11]. In other words, artificial intelligence will automate jobs and reduce the need for human workers. From this perspective, job automation poses a threat to humans because machines can perform the same tasks that humans used to do. This change necessitates a reevaluation of career development planning and skills development for future employment [12]. In this vein, understanding and managing the risks associated with AI-induced job automation is a crucial agenda for the career development and planning of secondary students [13]. The relevant literature in this topic, however, appears to be focused more on the effects AI-induced disruption has on the career development needs of university students and adult workers [11,13]. The needs of secondary students are less understood. Another weakness of the current literature is that studies investigating the impact that job automation has on career development (e.g., employment) have deployed different methodologies conceptualizing this issue, which often leads to an inconclusive and inconsistent understanding of the subject matter [14,15]. There is an immediate need to re-evaluate how we analyze and address this problem, starting from its core from the perspective of secondary school students. This is because empirical research has already shown that secondary school students are likely to aspire to work in an occupational role that is linked to a high risk of automation [16].

Based on the empirical setting presented above, an overview of how AI disruptive forces could impact the career development of secondary school students is urgently needed given the lack of research in this area [16,17]. This review is a valuable resource, providing consolidated career information to help educators and career guidance professionals identify the skills students need to develop before they enter the future world of work. The first part of this paper reviews research on AI’s workplace impact globally and regionally, while the second part discusses how school-based career guidance and counseling can be enhanced.

2. Empirical Evidence on the Accelerating Impact of AI on Job Displacement Across Various Sectors

Current evidence indicates that AI is replacing human labor, either fully or partially, at a faster pace than anticipated across various job sectors. These roles include voice actors, forex traders in investment banking, news writers, screenwriters, software engineers, coders, data analysts, lawyers, and graphic designers [18]. For instance, industry experts predicted that most outsourced coders in India will lose their jobs within two years due to the rapid advancement of artificial intelligence technology [19]. Additionally, the Writers Guild of America is in legal proceedings with Hollywood studios to limit AI applications, which threatens the job security of screenwriters, actors, and other production staff [20,21]. News outlets like Sports Illustrated and News Corp. have already begun using AI to produce news stories [22,23]. In investment banking, established banks such as UBS are restructuring their workforce, deeming human coders and forex traders redundant as machines can now perform their tasks [24,25]. AI-powered automated mutual fund trading algorithms have proven significantly superior to human traders [26]. Banks like Morgan Stanley are developing large language models to perform research analysts’ tasks, such as summarizing documents and generating investment solutions [27]. Boutique digital financial services firms, such as Betterment, are emerging, offering automated services that rival traditional banks [28]. In the legal field, recent studies indicate that GPT-4 can pass the Uniform Bar Examination with a score near the 90th percentile, greatly surpassing many trainee lawyers and far exceeding the passing threshold [29].

3. Impact of AI on Critical Thinking and Creativity in Students

At the classroom level, some researchers reported that students found AI-powered devices enjoyable to use, fostering creativity and academic success due to their human-like capabilities. For example, in their experimental study involving 123 Grade 10 students, Chiu et al. [30] found that with adequate teacher support, students developed intrinsic motivation to use chatbots for learning. Kim et al. [31] discovered through in-depth interviews with 20 university students that AI applications can improve academic writing skills by serving as both a writing assistant and teacher. Students felt more confident in writing scientific articles with AI support. Marrone et al.’s [32] focus group study examined students’ views on AI and creativity. Students with a higher self-reported understanding of AI were found to be more positive about using AI to enhance their academic engagement and creativity. Chang and Tsai [33] found that design thinking significantly enhanced AI learning, attitudes, and creativity, particularly in novelty, value, functionality, and elaboration. Rong et al. [34] reported that in the context of art education in middle schools, digital technology has transformed traditional teaching. The integration of AI and virtual reality has significantly improved students’ concentration and creativity through deep learning.

It is clear that AI can enhance students’ creativity and critical thinking. However, researchers may have overlooked the fact that it is the AI interface that possesses these abilities but not the students themselves [35]. Recent findings suggest that AI has both positive and negative impacts on student development [36,37]. For instance, Ahmad et al. [38] found that in a sample of 285 students from universities in Pakistan and China, AI significantly impacted decision-making, increased laziness, and raised privacy concerns. Similarly, Abbas et al. [39] showed that ChatGPT usage among 659 university students was linked to higher levels of procrastination and memory loss, especially under high academic pressure. Among primary and secondary school students in Hong Kong (n = 502), a survey study conducted by the Hong Kong Academy for Gifted Education [40] revealed that while students believed that generative AI devices such as ChatGPT could help them to complete school assignments, these devices may negatively influence their problem-solving and critical thinking skills. These findings underscore the need to reassess AI’s suitability in education as it may impede adolescents’ cognitive and behavioral development.

Because of their powerful content creation capability, AI systems are set to disrupt established educational and occupational developmental pathways pervasively. Recent studies have shown that humans are forming emotional dependencies on AI models [10]. Students, in particular, have been using AI to assist with cognitive tasks like writing assignments [41]. Research from the University of Pennsylvania revealed that students who used ChatGPT for test preparation scored lower than those who did not. This raises concerns about over-reliance on AI and its negative impact on cognitive skill development [42]. If students develop reliance on AI without cultivating the underlying essential cognitive skills, it raises questions about their relevance to future employers, especially when intelligent machines can perform much of their work [43]. While students may not fully grasp its impact, AI’s rapid advancement has already sparked fears of job displacement among adults [44]. This is evidenced by the career choices made by the students who had scored a perfect score in the 2023–2024 cohort of the International Baccalaureate Diploma Program examination. Among the 23 students in Hong Kong, China, who have scored a perfect score in the exam, none of them aspired to become an artificial intelligence scientist or work in a field that is related to AI development [45]. Some of them chose to pursue occupational roles (e.g., lawyers and psychologists) that have been suggested by experts as being highly exposed to risks of job displacement due to AI-induced job automation [7,46], which is very similar to the trend that had been earlier reported in England [16]. This worrisome situation challenges our theoretical and practical approaches to preparing students for future employment. This is because elite students often perpetuate established norms and choose careers (e.g., Lawyer, Investment Banker, and Medical Doctor) that are associated with social prestige and wealth [47,48], without considering the risks of technological disruptions [16,46]. Experts have warned that this trend could signal issues for policymakers, as academic success does not necessarily lead to economic and technological growth, especially with a shortage of AI talent [49,50].

4. Challenges Faced by Secondary Students in Career Planning in the Age of Automation

From a practical standpoint, the global expansion of higher education makes it harder to ensure quality employment outcomes for secondary students after they have completed their university education/vocational training [51]. Furthermore, secondary students worldwide face considerable challenges due to the inconsistent quality of school-based career-related teacher support [6,52,53]. Frameworks such as the Gatsby Benchmarks in England emphasize that adequate career-related teacher support is essential for effective career guidance in schools [54]. Despite its significance, the specific nature and types of this support are often not thoroughly examined [53]. In the context of AI-induced job automation, these frameworks communicated little to no details on how schoolteachers should facilitate their students’ career planning as AI is now powerful enough to replace human workers in both low- and high-skilled roles [7,46].

Empirical research shows that career-related information provided by schoolteachers influences students’ career planning most significantly [1,52,53]. However, valuable career insights are typically derived from industry experience and private professional networks. Companies often keep detailed career information confidential [55]. Consequently, schoolteachers, who spend most of their careers in a school setting, often struggle to provide insightful career information and foresee the challenges students may face in the AI era [6,16,56,57,58,59]. This elucidates why school-based career guidance and counseling programs may not be able to sufficiently equip students to confront the imminent threats posed by AI-induced job automation, which is generating anxiety within the global workforce [44,50]. This issue is apparent in a set of well-established career guidance benchmarks developed over a decade ago in England [54]. These benchmarks no longer adequately address the current career development needs of students, as the structure of the world of work has fundamentally changed following the COVID-19 pandemic and global economic recessions [56]. This is exemplified by the real-life employment situations in the United Kingdom, where students are encountering significant difficulties in securing graduate jobs [58]. Despite warnings from the UK Department of Education [46] and the European Parliament [50] about the clear threat of AI-induced job displacement, these benchmarks have not been updated to address the imminent risks associated with AI-driven job displacement and the evolving skills requirements in the global workplace. Recent research suggests that one possible cause of this is the inability of schoolteachers to keep pace with the development of the world of work [1,52,53,60].

Globally, the survey results of a study conducted by the Organization for Economic Co-operation and Development (OECD) [47] on the occupational expectations of 15-year-olds around the world. These occupational expectations were then matched with the expert analysis performed by Frey and Osbourne in 2013 [7] and the Department of Education in 2023 [46]. As shown in

Table 1. Occupational expectations of 15-year-olds around the world and their exposure to job automation.

Occupation 1	Other Relevant Occupational Roles	AI Exposure Frey and Osbourne [7]	AI Exposure Department of Education [46]
Doctors	Physician and Surgeon	Low	No data
Teachers	Elementary School Teacher, Preschool Teacher, Special Education Teacher, and Instructor	Low	No data
Business Managers	Purchasing Manager, Financial Analyst/Advisor/Auditor/Manager, Credit Controller, and Accountant	Moderate to high	High
Engineers	Civil Engineer, Mechanical Engineer, Electrical Engineer, and Software Engineer	Low overall. High for Software Engineer, Locomotive Engineer, Stationary Engineer, and Rail Engineer	High for Civil Engineer
Lawyers	Paralegal, Solicitor, and Legal Assistant	Low for Lawyer. High for Paralegal and Legal Assistant	High overall
Police Officers	Patrol Officer, Detective, and Criminal Investigator	Low	Low
ICT Professionals	Network and Computer Systems Administrator, Software Developer, Web Developer, Information Security Analyst, and Computer Network Architect	Low	High
Nursing and Midwives	Licensed Vocational Nurse	Low	Low
Designers	Graphic Designer	Low	High
Psychologists	Mental Health Counselors and Substance Abuse Counselor	Low	High
Architects	Landscape Architect	Low	No data
Veterinarians	Veterinarian Assistant	Low	Low
Actors 2	Voice Actor and Screenwriter	Moderate	No data
Motor Vehicle Mechanics	Mobile Heavy Equipment Mechanic	Moderate	No data
Musical 2 Performers	Music Directors and Composer	Low	No data

¹ These are the most popular occupational expectations of 15-year-olds around the world, derived from the 2018 Programme for International Student Assessment (PISA) survey. The information is sourced from the report Dream Jobs? Teenagers’ career aspirations and the future of studies published by the OECD in 2020. ² Recent research compiled by CVL Economics in 2024 [20] suggests that these roles are under serious threats of AI-induced job displacement.

, Frey and Osborne [7] initially classified only a few of these desired job roles as having a high risk of automation. However, a decade later, roles once deemed low-risk in 2013, such as psychologists and lawyers, are now highly susceptible to AI-induced job automation. This change is likely due to major advancements in AI technologies, especially in natural language processing and machine learning, which greatly enhance AI’s capability to handle complex tasks involving sophisticated rules and human emotions [46,61]. Additionally, it is crucial to recognize that creative roles like voice actors and screenwriters were initially considered to have low exposure to AI. However, as AI technology rapidly progresses, these roles, exemplified by the situation in Hollywood, are now at significant risk of AI-induced job displacement [20,21].

Additionally, the quality of school-based career services is significantly influenced by school management support [62]. Teachers are often overwhelmed by teaching and administrative duties, making it difficult for them to allocate time to support their students’ career planning [63]. When teachers attempt to organize career guidance activities, they may face scrutiny from administrators who are concerned about these activities disrupting academic learning [64]. Additionally, teachers seeking professional development often face administrative hurdles, such as the requirement to reschedule all their classes to attend training sessions [65].

To further exacerbate these problems, massification of higher education has raised concerns about training quality [51], thus reducing the value of academic credentials as indicators of skills competency [66]. Skills-based hiring now dominates, necessitating continuous skill updates due to rapid technological advancements [67]. Consequently, traditional university degrees are becoming less relevant indicators of a worker’s capabilities [66]. Additionally, adolescents often struggle with mental health and social interactions due to excessive internet and social media use [68]. As AI technologies advance, adolescents face increased risks of misinformation and fake news, yet interventions to promote critical thinking skills are scarce and under-researched [69].

Early studies indicate that AI has both positive and negative impacts. While it enhances productivity, it also increases susceptibility to procrastination, memory loss, and poor decision-making among students and professionals [70,71]. Additionally, AI can generate highly convincing fake information due to algorithmic flaws, undermining trust in reliable sources [72,73]. This complicates career planning for students, as they struggle to verify the authenticity of career information due to their limited knowledge about the world of work. Furthermore, students’ ability to clearly express their thoughts, understandable by both humans and machines, significantly impacts their effectiveness in prompting AI [74]. Therefore, developing high proficiency in English is crucial, as it is the global lingua franca and the primary language AI systems are designed to respond to [75,76].

5. Theoretical Weaknesses

At the theoretical level, there is a notable divide between researchers in vocational psychology and general psychology, as vocational psychology continues to establish its own independent research agenda [77]. Concepts in vocational psychology, such as John Holland’s RIASEC model [78], career adaptability [79], career capability [80], and the recently proposed self-regulation model of career competencies [81], share several common theoretical weaknesses.

First, these concepts often overlook the interpersonal, affective, and emotional aspects of work. With AI’s rapid advancement, the notion that humans are the sole providers of cognitive skills is increasingly challenged. Industry experts now emphasize the need for developing emotional and affective skills like leadership, persuasion, and communication to highlight human uniqueness in an automated environment [82,83,84]. The concept of career adaptability is particularly deficient, lacking an interpersonal perspective despite the essential nature of collaboration [17]. Only recently, “cooperation” has been proposed to address this critical flaw [85]. Likewise, some scholars have attempted to apply Amartya Sen’s Capability Approach to explain career behaviors. However, in the context of career guidance and counseling, this approach exhibits significant limitations due to its egalitarian principles, inherent subjectivity, insufficient theoretical foundation, and challenges in measuring and comparing capabilities [86]. This underscores the urgent need to reassess these career concepts in light of AI job disruption. As AI outperforms humans in cognitive tasks [87], the industry now prioritizes human-centric skills such as empathy, persuasion, openness to new ideas, and creativity, which are uniquely human attributes [82,83,84].

Second, career theories often assume that career decision-making is a one-dimensional process guided by a few universal principles [88]. Consequently, the specific factors mediating career development in real-world contexts are often not clearly identified [89,90,91,92]. For instance, the super short form of the Career Adapt-Abilities Scale [93] contained four items, which are “Planning how to achieve my goals”, “Keeping upbeat”, “Exploring my surroundings”, and “Solving problems”. These items are so universal and unspecific that their ability to provide meaningful explanations of career development issues in the real world is highly uncertain [55,94]. Furthermore, the item “Solving problems” specifically relates to the measurement of confidence, but this non-specific measurement contradicts with the original conceptualization of self-efficacy. According to Albert Bandura [95,96], the predictive power of self-efficacy is valid only when assessed in relation to specific tasks within a particular context. This example questions the validity of career adaptability [97] and highlights the researchers’ bias in pursuing only statistical significance without considering conceptual and clinical/empirical implications [98,99,100,101,102].

Lastly, recent research in adolescent career development has shifted from traditional job-matching and employability enhancement to framing career problems as if they were mental health issues, explored through positive psychology. These studies employ quantitative methods to investigate the relationships between positive psychology concepts such as courage, career constructs (e.g., career adaptability), and mental health variables (e.g., well-being) (see e.g., [103]). This approach shares the criticisms of positive psychology research. That is, these studies often lack real-world applicability and practical insights about career development [104,105]. The study of positive psychology itself is criticized for subjective definitions, weak theorizing, and promoting unrealistic positivity, leading to pathologization of negative emotions [104,106,107]. In fact, as revealed in Lee et al.’s study [108], employees’ levels of career adaptability positively influenced their turnover intentions when experiencing lower levels of supervisor and coworker support, suggesting that career adaptability can be a negative construct [106].

Considering the extensive impact of the current AI disruption, it raises doubts about whether the current theoretical foundation in adolescent career development research can effectively guide educational and counseling professionals in preparing adolescents for the future workforce. Given that the current generation of AI (e.g., GPT-4) is already capable of replacing human intelligence [109,110], a comprehensive overview of how AI could affect the career transitions of secondary students is urgently needed. This information will be crucial for secondary students’ career planning.

6. Methods

The main objective of conducting a systematic literature review is to improve the replicability of research, allowing other researchers to use the same methods and confirm the results [111]. However, not all literature reviews are systematic; their nature depends on the research purpose [111]. Narrative reviews, for instance, are more flexible and interpretative. They aim to synthesize and discuss the literature rather than strictly replicate quantitative findings, offering a broad overview of a topic and highlighting gaps or inconsistencies in the existing research [112,113]. A narrative review is most suitable when the literature review is designed to examine the theoretical conceptualization of a research topic, focusing on its overall theoretical meaning rather than the statistical significance of the findings [114]. Due to the use of inconsistent research methods in studying the impact of AI-induced job automation on adolescents’ career development, our understanding of this topic is thus fragmented, inconsistent, and incomprehensive. It is, therefore, necessary to conduct a narrative review on this topic to identify gaps and inconsistencies in the existing literature [14,15]. Such a process is crucial for improving the scientific rigor and replicability of future research on this topic [111].

This review does not aim to be comprehensive; instead, it seeks to provide an overview of the current developments of AI-induced job automation and how it could impact the workforce, which in turn influences the career planning of secondary students. The advantage of this approach is that it emphasizes surveying the literature and highlighting the existing knowledge base on the subject [14,114,115].

6.1. Literature Search and Inclusion Criteria

Keyword searches were conducted on major academic databases (e.g., EBSCO), online academic search engines (e.g., Google Scholar), and official websites of international thinktanks, governmental organizations, and expert panels (e.g., World Economic Forum, European Parliament, International Labor Organization, International Monetary Fund, and OECD). The materials published by these experts are included in the literature search because these informants are well-established global organizations that have exerted significant influence on educational, social, technological, and economic policy decisions worldwide [116,117,118,119].

Keyword searches were also conducted in major academic journals that specialized in career development. These are, for example, the International Journal for Educational and Vocational Guidance, the British Journal of Guidance and Counseling, the Journal of Career Assessment, the Journal of Vocational Behavior, and the Journal of Career Development. Keywords, or a combination of keywords in English such as “AI job automation”, “artificial intelligence workforce”, “generative AI student work”, and “AI work report”, were used to identify and locate relevant materials. The identified articles, papers, and reports were then downloaded from the internet.

6.2. Data Synthesis and Analysis

Following the classification and presentation styles used in state-of-the-art expert reports produced by expert informants such as the World Economic Forum [120,121,122]. The information identified in the selected research studies was categorized according to their geographical locations and job sectors. Only published peer-reviewed materials and reports published by expert informants and global/governmental organizations (e.g., UNESCO) were included. Nonpeer-reviewed materials were all excluded. Articles were included if they met the following criteria: (1) described and explained the mechanism behind technological disruption and its impact on the workforce, (2) assessed the extent of how AI could impact student populations and the workforce, (3) offered predictions and forecasts of the impact and extent of AI disruption could have on education and work, and (4) theoretical and practical frameworks containing any of the keywords. It was found that 270 articles met the criteria presented in the above. After close inspection, 60 articles were finally chosen for further analysis and summarization. Figure 1 presents a flowchart illustrating the process of conducting the literature search and selecting materials for review.

7. Part 1: Reviewing the Status of Job Automation at the Global Level

The recent breakthrough in computer engineering, where graphics processing units (GPUs) replace traditional processors, has finally met the computational demands of AI after a long stagnation [123]. This advancement paves the way for the exponential growth of AI applications in all aspects of life. Jensen Huang, NVIDIA’s CEO, stated that generative AI’s rise means “nobody will have to program”, rendering coding education less relevant [124]. The computerization of cognitive tasks that are typically performed by humans is beneficial for society from an efficiency standpoint, as computers can operate continuously with accuracy and impartiality [7].

Preliminary findings suggest that students may not be adequately prepared to address the risks of job automation before entering the workforce. For example, a university-to-work transition program developed by a Hong Kong university’s English department did not address AI-induced job displacement risks and the related psychological disturbance (e.g., anxiety). The program’s developers interviewed 40 employers and 69 graduates to identify necessary skills that can facilitate students’ transition to the workplace [125,126]. The researchers found that graduates generally lacked soft skills and suggested improvements. However, the validity of these claims is questionable. First, the authors lack training and qualifications in psychology and career guidance. This undermines the validity and reliability of the research. Second, subjective definitions of “soft” and “hard” skills were used, which may reflect researcher bias [127]. Additionally, in terms of research methods, soft skills are often subjectively defined and overlap with each other [128]. This creates measurement problems that can lead to wrongful interpretation of the subject matter [5]. These issues highlight the biases or misinformation that can arise when researchers lack relevant expertise, potentially leading to the wrongful pathologization and medicalization of career problems [129,130]. Insufficient knowledge may also lead to ethical breaches and result in interventions that are ineffective or even potentially harmful to students, despite being well-intentioned [131,132].

In the empirical workplace, a Harvard Business School study with Boston Consulting Group [133] examined AI’s impact on management consultants’ performance. The study revealed that AI significantly improved productivity and quality for tasks within its capabilities but struggled with more complex tasks. Consultants using AI completed 12.2% more tasks and produced 40% higher-quality results. However, for tasks beyond AI’s capabilities, consultants using AI were 19% less likely to achieve accurate solutions compared to those without AI assistance. These results suggested that AI usage is linked to reduced overall cognitive functioning among humans.

7.1. Progress of Job Automation: Global Level

First, the World Economic Forum’s “Future of Jobs Report” series [120,121,122] examined the interplay between socioeconomic development and technological advancement. To adopt new technologies, companies are employing staff with technological expertise and outsourcing current functions. Concurrently, they are reducing their full-time workforce through automation and enhancing productivity with technology. Retraining and upskilling are common strategies to address skill gaps, with staff lacking new technological skills being strategically reduced. It is estimated that two-thirds of the current global workforce will be affected by this transition [120].

The COVID-19 pandemic accelerated job automation, creating a “double disruption” for workers and exacerbating economic inequality [121]. Lower-wage workers, women, and younger employees have been disproportionately affected by the economic downturn and job displacement. The impact on individuals with lower education levels during this crisis surpasses that of the 2008 Global Financial Crisis, heightening existing inequalities [121].

Globally, AI is projected to replace around 85 million jobs and create 97 million new roles by 2025 [121]. Rapid advancements in computer processing power, high-speed internet, cloud computing, and big data are expected to disrupt approximately 44% of workers’ skills in the coming years [122]. A net contraction of 14 million jobs globally is projected between 2023 and 2027. White-collar roles that are routine-based and adhere to established norms, such as accountants, financial auditors, financial analysts, business administration managers, cashiers, telemarketers, bank tellers, and lawyers, are most impacted by AI automation [119].

Conversely, roles that enhance work automation and digitization, such as data scientists, AI and machine learning specialists, big data specialists, robotics engineers, user experience designers, information security specialists, and software engineers, are expected to grow [122]. Rapid digitization in some job sectors raises new issues concerning employee well-being as remote work increases [120]. To adapt to these changes, employees are expected to acquire technological skills (e.g., deep learning), statistical skills (e.g., regression), and communication skills for accurate self-expression [120]. Additionally, they should strengthen human qualities such as leadership, flexibility, originality, and persuasion and negotiation [120,121]. Psychological well-being and self-management skills, such as resilience, stress tolerance, mindfulness, gratitude, and kindness, are also essential as workers are likely to undergo several job transitions due to automation. It is imperative that they possess the ability to manage their own well-being effectively.

Second, Microsoft and LinkedIn [134] investigated the impact of AI automation on the global workforce through a survey of 31,000 professionals across 31 countries. The findings revealed that 75% of respondents are currently using AI in their daily work, with 46% having adopted it in the past six months to reduce their workload. AI is positively perceived for enhancing productivity and creativity, aiding in time management, prioritizing tasks, and increasing job satisfaction. However, business leaders may resist this change as AI fundamentally alters the workforce and work processes. AI is also reshaping the labor market by increasing the demand for AI skills and changing job roles. Many organizations lack a clear strategy to leverage AI upskilling effectively. Additionally, companies are facing challenges in retaining AI-skilled workers, with 46% of these employees globally considering leaving their current jobs.

Third, PricewaterhouseCoopers in 2024 [44] conducted a global workforce survey with more than 56,000 professionals from 50 countries. The survey revealed that over half of the workers felt overwhelmed by rapid changes at work, with 47% worrying about their job security. The findings also suggested that AI is a double-edged sword. While 73% of the respondents commented that AI would help them to be more creative at work, 52% of the respondents were concerned that the adoption of AI would lead to increased bias and misleading information.

Fourth, the International Monetary Fund’s [135] analysis of the global economy predicted that AI would transform the global economy. Around 40% of jobs around the world are exposed to the risks of automation. In advanced economies, exposure to AI-induced job automation increases to 60% of the workforce. AI is projected to increase productivity, but job automation will also result in the widening of income inequality. College-educated workers are expected to adapt better to the changing work landscape, while older workers, women, and young people face substantial exposure to higher risks of AI-induced job displacement.

Last, a global survey by Goldman Sachs [136] explored the potential impacts of AI adoption on global economic development. AI adoption is anticipated to drive significant labor cost savings and productivity improvements. Nearly two-thirds of current jobs in the United States and Europe are exposed to some degree of AI automation, with up to one-fourth of current work potentially being automated, affecting up to 300 million jobs worldwide. The report suggested that AI-induced job automation could boost annual US labor productivity growth by nearly 1.5 percentage points over a decade following widespread adoption. Globally, AI could increase annual GDP by 7%. However, the actual impact will depend on AI’s capabilities and the timeline for its adoption. The report also indicated that up to 30% of existing job roles in Hong Kong, China, particularly in the finance and insurance sectors, could benefit from automation, that is, the highest ratio among surveyed regions. This suggested that the Hong Kong labor market will be significantly impacted by AI automation soon. These findings aligned with other global survey reports, such as those by Microsoft and LinkedIn [134] and the World Economic Forum [120], indicating that AI-induced job replacement and displacement are becoming evident [137].

7.2. Part 1 Summary

In summary, global surveys indicated that AI will transform work processes and boost productivity. While AI is expected to replace many job roles, it will also create new ones. However, automation may exacerbate inequality and anxiety, particularly among workers with limited access to technology. Women and younger employees lacking in technological proficiency are more vulnerable to job displacement due to automation or a lack of AI skills. Unlike previous technological revolutions, this AI-driven wave will significantly disrupt both skilled blue-collar jobs and cognitively demanding white-collar jobs, which require specialized knowledge obtained through university education. Roles involving repetitive tasks or adherence to pre-existing rules, such as Lawyers, Financial Analysts, and Accountants, are highly susceptible to automation. In contrast, jobs requiring human emotions and creativity, like Schoolteachers and Fine Artists, are less likely to be automated.

8. Part 2: Reviewing the Status of Job Automation at the Regional Level

According to OECD [138], regions with a higher share of tertiary-educated workers, a strong service sector, and a large urban population tend to have a lower risk of AI-induced job automation. Conversely, areas with a higher concentration of routine-based jobs are more susceptible to automation. The chronological evolution of AI automation and regional disparities in AI adoption across different geographical regions are summarized in Table 2 and Table 3.

Overall, AI adoption is rising globally, with new AI technology usage doubling in 2023 [139]. Currently, 65% of organizations around the world regularly use AI at work. Denmark leads in adoption among 11 OECD countries, followed by Belgium, Italy, Portugal, and France. Adoption rates are lower in Israel, Japan, and South Korea [140]. Across geographical locations, a significant “AI divide” exists between the Global North and South due to disparities in infrastructure and readiness [141].

8.1. North America

In Canada, artificial intelligence was perceived to have both beneficial and detrimental effects in the workplace. According to Future Skills Centre [142], 20% of jobs in Canada were significantly vulnerable to automation. Canadian workers are lagging in adopting AI compared to their global counterparts. Only 25% of Canadian respondents use AI tools monthly, versus 36% globally [44]. Another recent report by Deloitte in 2024 [143] revealed that 56% of Canadian employers did not use AI and are not planning to adopt it soon. Only 15% of workers currently use AI, and nearly half of employers believed their employees were unprepared for AI integration.

In the United States, first in their seminal study, Frey and Osbourne [7] developed an algorithm to evaluate the impact of automation on the US labor market, analyzing 702 job roles from the O*Net database. They found that 47% of these roles are highly susceptible to automation (Probability ≥ 0.09). Common characteristics of these jobs included repetitive manual tasks (e.g., Hand Sewers, probability = 0.99) or rule-based activities (e.g., Accountants and Financial Auditors, probability = 0.94; Paralegals and Legal Assistants, probability = 0.94). Conversely, roles such as Psychologists (probability = 0.0043), Fine Artists (probability = 0.0042), Mechanical Engineers (probability = 0.0011), and Secondary Schoolteachers (probability = 0.0078), which require human emotions and creativity to address individual needs, are less likely to be automated due to their non-repetitive nature.

Table 2. Regional disparities in AI adoption.

Study	Year of Study	Region/Country	Key Developments in AI Adoption 1
World Economic Forum [122]	2023	Global	There is a great “AI divide” between the Global North and Global South due to differences in generative AI infrastructure and readiness.
OECD [140]	2023	Global	In 11 OECD countries across the globe, Denmark showed the largest generative AI adoption rate. Belgium, Italy, Portugal, and France also showed increased generative AI adoptions. Adoption rates were lower in Israel, Japan, and the Republic of Korea.
National Bureau of Economic Research [144]	2023	The United States	Across 850,000 firms in the United States, the average adoption rate was 18%. Generative AI was adopted across all industries, with larger firms showing higher adoption rates. A growing “AI divide” was evident.
Department of Education [15]	2023	The United Kingdom	Up to 30% of the UK workforce could be automated. London and the South East face the highest risk of exposure as these places have the highest concentration of job roles that require advanced qualifications (e.g., accounting, finance, and psychology). Regional areas had a lower rate of adoption due to a lack of resources and infrastructure.
OECD [145]	2023	Europe, North America, and Japan	AI technologies are disrupting a wide range of occupations and are still assistive at the current stage of development. AI adoption affects workers and job sectors in a disproportional manner. Older workers, low-skilled workers, office administrative support roles, and occupations associated with risk assessment and mathematical predictions are all highly exposed to automation.
QuantumBlack AI by McKinsey [139]	2024	Global	Generative AI adoptions surged two-fold within 10 months in 2023. Moreover, 65% of organizations now regularly use generative AI. Most organizations believe that generative AI will significantly disrupt their industries soon.
Deloitte [146]	2024	Asia-Pacific	Among 11,900 employees across the Asia-Pacific region, younger employees were found to be early adopters of generative AI compared to older workers.
Reuters [147]	2024	Japan	Slow AI adoption across Japan because of a lack of technological expertise and high costs of implementation.
SAS Institute [148]	2024	China	China is a world leader in AI adoption because of strong government support and active user adoption. Generative AI adoption aided the work of labor-intensive industries across China.
International Monetary Fund [149]	2024	Singapore	Singapore is highly exposed (77%) to AI-induced job automation. Among those exposed, there’s an equal distribution between roles with high and low AI complementarity. High-complementarity roles (managers and professionals) may gain productivity, while low-complementarity roles (clerical and administrative) face higher risks of job replacement. Women and younger workers are more exposed to the adverse effects of job automation.
Broadcast Media Africa [150]	2024	Africa	9% of African media organizations are making extensive use of AI tools, whereas 48% are utilizing them to a very limited extent. The low adoption rate was caused by high implementation costs and a lack of personnel with relevant skill sets. Organizations remained cautious about AI adoption.
HLB [151]	2024	Africa	52% of businesses have not yet integrated any AI tools into their business models, and 44% have not yet finished AI-specific training for their staff.

¹ Findings are summarized from the corresponding expert sources.

Table 2. Regional disparities in AI adoption.

Study	Year of Study	Region/Country	Key Developments in AI Adoption 1
World Economic Forum [122]	2023	Global	There is a great “AI divide” between the Global North and Global South due to differences in generative AI infrastructure and readiness.
OECD [140]	2023	Global	In 11 OECD countries across the globe, Denmark showed the largest generative AI adoption rate. Belgium, Italy, Portugal, and France also showed increased generative AI adoptions. Adoption rates were lower in Israel, Japan, and the Republic of Korea.
National Bureau of Economic Research [144]	2023	The United States	Across 850,000 firms in the United States, the average adoption rate was 18%. Generative AI was adopted across all industries, with larger firms showing higher adoption rates. A growing “AI divide” was evident.
Department of Education [15]	2023	The United Kingdom	Up to 30% of the UK workforce could be automated. London and the South East face the highest risk of exposure as these places have the highest concentration of job roles that require advanced qualifications (e.g., accounting, finance, and psychology). Regional areas had a lower rate of adoption due to a lack of resources and infrastructure.
OECD [145]	2023	Europe, North America, and Japan	AI technologies are disrupting a wide range of occupations and are still assistive at the current stage of development. AI adoption affects workers and job sectors in a disproportional manner. Older workers, low-skilled workers, office administrative support roles, and occupations associated with risk assessment and mathematical predictions are all highly exposed to automation.
QuantumBlack AI by McKinsey [139]	2024	Global	Generative AI adoptions surged two-fold within 10 months in 2023. Moreover, 65% of organizations now regularly use generative AI. Most organizations believe that generative AI will significantly disrupt their industries soon.
Deloitte [146]	2024	Asia-Pacific	Among 11,900 employees across the Asia-Pacific region, younger employees were found to be early adopters of generative AI compared to older workers.
Reuters [147]	2024	Japan	Slow AI adoption across Japan because of a lack of technological expertise and high costs of implementation.
SAS Institute [148]	2024	China	China is a world leader in AI adoption because of strong government support and active user adoption. Generative AI adoption aided the work of labor-intensive industries across China.
International Monetary Fund [149]	2024	Singapore	Singapore is highly exposed (77%) to AI-induced job automation. Among those exposed, there’s an equal distribution between roles with high and low AI complementarity. High-complementarity roles (managers and professionals) may gain productivity, while low-complementarity roles (clerical and administrative) face higher risks of job replacement. Women and younger workers are more exposed to the adverse effects of job automation.
Broadcast Media Africa [150]	2024	Africa	9% of African media organizations are making extensive use of AI tools, whereas 48% are utilizing them to a very limited extent. The low adoption rate was caused by high implementation costs and a lack of personnel with relevant skill sets. Organizations remained cautious about AI adoption.
HLB [151]	2024	Africa	52% of businesses have not yet integrated any AI tools into their business models, and 44% have not yet finished AI-specific training for their staff.

¹ Findings are summarized from the corresponding expert sources.

Table 3. Evolution of AI in different labor markets and job losses.

Year/Period	Study	Region/Country	Key Developments	Estimated Job Losses1
2018	World Economic Forum [120]	Global	Results showed that almost half of the surveyed companies anticipated that automation would reduce their full-time workforce by 2022. Due to automation, 42% of the total work hours were expected to be performed by machines, compared to only 29% in 2018. In total, 133 million new job roles may emerge because of technological advancement.	75 million
2018	McKinsey & Company [152]	Middle East	Progress of job automation was on par with global averages. AI adoption was projected to accelerate in the period 2018–2030.	Up to 45% of the local workforce
2018	McKinsey Global Institute [153]	Global	AI adoption worldwide is projected to accelerate in the period 2016–2030. Up to 50% of the work activities are now automatable.	10–800 million
2020	World Economic Forum [121]	Global	Global job automation was accelerated by the COVID-19 outbreak and global economic recession. Companies expected that by 2025, 85 million job roles would be displaced, and 97 million new roles may emerge.	85 million
2023	Institute for Public Policy Research [154]	The United Kingdom	Widespread adoption of AI across all sectors. Back-office jobs are highly exposed to job displacement.	1.5–7.9 million
2023	ServiceNow [155]	Australia	Increased adoption of AI across all sectors. Jobs in office support, customer service, sales, and food services are most at risk.	1.5 million
2023	Goldman Sachs [136]	Global	Up to 30% of the current job roles could benefit from automation.	Up to 300 million
2023	World Economic Form [122]	Global	Companies estimated that 34% of the tasks are now performed by machines. This means that compared to 2020, the automation adoption rate has slowed down. Employers expected an increase of 69 million job roles, while 83 million jobs were expected to be displaced due to automation.	83 million
2024	CVL Economics [20]	The United States	Increased adoption of generative AI will severely disrupt jobs in Hollywood. Leading to widespread job displacement within the entertainment industry.	204,000 within the industry
2024	International Monetary Fund [135]	Global	AI is disrupting workflows in all sectors. High-income countries are at a higher risk than emerging markets and low-income nations. AI could potentially worsen job market inequality, leading to social tension	40–60% of the global workforce
2024	Microsoft [156]	Africa	AI adoption is slow overall due to a lack of infrastructure and resources. Here, 450 m still remain uncovered by the mobile broadband network.	In millions. No exact number is given.
2024	EY and FICCI [157]	India	The workforce will be employed in completely new roles that currently do not exist. Some of these positions require significantly different skills.	9–37% of the workforce needs to be reskilled

¹ Findings are summarized from the corresponding expert sources.

Table 3. Evolution of AI in different labor markets and job losses.

Year/Period	Study	Region/Country	Key Developments	Estimated Job Losses1
2018	World Economic Forum [120]	Global	Results showed that almost half of the surveyed companies anticipated that automation would reduce their full-time workforce by 2022. Due to automation, 42% of the total work hours were expected to be performed by machines, compared to only 29% in 2018. In total, 133 million new job roles may emerge because of technological advancement.	75 million
2018	McKinsey & Company [152]	Middle East	Progress of job automation was on par with global averages. AI adoption was projected to accelerate in the period 2018–2030.	Up to 45% of the local workforce
2018	McKinsey Global Institute [153]	Global	AI adoption worldwide is projected to accelerate in the period 2016–2030. Up to 50% of the work activities are now automatable.	10–800 million
2020	World Economic Forum [121]	Global	Global job automation was accelerated by the COVID-19 outbreak and global economic recession. Companies expected that by 2025, 85 million job roles would be displaced, and 97 million new roles may emerge.	85 million
2023	Institute for Public Policy Research [154]	The United Kingdom	Widespread adoption of AI across all sectors. Back-office jobs are highly exposed to job displacement.	1.5–7.9 million
2023	ServiceNow [155]	Australia	Increased adoption of AI across all sectors. Jobs in office support, customer service, sales, and food services are most at risk.	1.5 million
2023	Goldman Sachs [136]	Global	Up to 30% of the current job roles could benefit from automation.	Up to 300 million
2023	World Economic Form [122]	Global	Companies estimated that 34% of the tasks are now performed by machines. This means that compared to 2020, the automation adoption rate has slowed down. Employers expected an increase of 69 million job roles, while 83 million jobs were expected to be displaced due to automation.	83 million
2024	CVL Economics [20]	The United States	Increased adoption of generative AI will severely disrupt jobs in Hollywood. Leading to widespread job displacement within the entertainment industry.	204,000 within the industry
2024	International Monetary Fund [135]	Global	AI is disrupting workflows in all sectors. High-income countries are at a higher risk than emerging markets and low-income nations. AI could potentially worsen job market inequality, leading to social tension	40–60% of the global workforce
2024	Microsoft [156]	Africa	AI adoption is slow overall due to a lack of infrastructure and resources. Here, 450 m still remain uncovered by the mobile broadband network.	In millions. No exact number is given.
2024	EY and FICCI [157]	India	The workforce will be employed in completely new roles that currently do not exist. Some of these positions require significantly different skills.	9–37% of the workforce needs to be reskilled

¹ Findings are summarized from the corresponding expert sources.

Second, The White House [158] assessed AI’s economic impact on US workforces, noting that despite low overall adoption, AI will significantly transform industries, workflows, and productivity. However, it also poses challenges like job displacement, increased inequality, and the need for workforce reskilling. AI technologies can now automate non-routine tasks by using algorithms trained on examples rather than explicit rules, potentially replacing and outperforming educated workers in roles requiring significant education and experience.

Third, Pew Research Center’s analysis of federal data in 2023 [59] revealed that 19% of the US workforce are working in jobs highly exposed to AI. Occupations requiring analytical skills, such as critical thinking, writing, science, and mathematics, are more susceptible to job replacement. The study also highlighted that jobs requiring higher education and analytical skills are more susceptible to AI integration. Women, Asian, university-educated, and higher-paid white-collar professionals are being more affected. These job roles are, for example, Web Developers, Tax Preparers, Lawyers, Financial Auditors and Budget Analysts. In contrast, 23% of the workforce are working in jobs with low AI exposure. These jobs are such as Barber, Firefighter, and Dishwasher. Younger workers and persons with less formal education were also found to be less exposed to the risks of AI automation. Despite concerns about the potential threats of AI automation, many workers in AI-exposed industries remain optimistic about AI’s impact on enhancing their productivity. However, schoolteachers have expressed their concerns about the imminent widespread adoption of AI. About 25% of US K-12 teachers believed AI tools could cause more harm than good in education, while 32% see a balance of benefits and drawbacks [159].

Fourth, a survey by the National Bureau of Economic Research [160] revealed that AI technology was utilized across all job sectors among 850,000 US companies. However, the overall adoption rate was low, with fewer than 6% implementing any AI-related technologies. Adoption was highest among larger firms and among more educated and younger workers.

Last, McKinsey Global Institute [161] predicted that by 2030, up to 30% of current work hours could be automated, particularly affecting office support, customer service, and food service roles due to AI-induced job automation. The American workforce will have to undergo substantial job-related transitions as automation continues to progress. It is predicted that workers working in lower-wage jobs are 14 times more likely to change jobs or face job redundancy when compared to higher-wage workers. As AI systems now have the capability to rival human intelligence, traditional merit-based academic credentials may not serve as an appropriate indicator when it comes to employee selection. Employers are encouraged to focus on skills-based hiring and workforce reskilling to navigate through the changes brought about by technological disruption.

8.2. Latin America

According to a recent study conducted by the International Labor Organization and the World Bank, AI adoption could eliminate up to 5% of jobs in Latin America. The integration of AI in various sectors, such as manufacturing, retail, agriculture, legal services, and marketing, is transforming traditional roles, optimizing processes, and enhancing customer experiences. This widespread adoption signifies a transformative trend, empowering professionals to excel in decision-making and thrive in a rapidly evolving landscape. At the same time, AI adoption gives rise to inequality issues, with women and younger workers being more vulnerable to job loss due to automation [162].

8.3. Europe

In the United Kingdom, the Department of Education of the UK government [46] conducted an extensive analysis to assess the scale of disruption AI adoption could bring to the UK workforce. The study reveals that 10–30% of jobs could be automated by AI and large language models, with finance, law, and business management roles being particularly vulnerable, especially in accounting and finance. London and the South East face the highest exposure, correlating with higher qualifications. The report identifies roles like Psychologists, Management Consultants, Business Analysts, Accountants, Civil Engineers, Actuaries, Statisticians, and Economists as highly susceptible to AI automation. Conversely, jobs such as Truck Drivers, Professional Athletes, Cleaners, Launderers, and Bricklayers are least at risk, primarily due to their reliance on manual dexterity rather than advanced university-level training.

The Institute for Public Policy Research [154] analyzed the potential impact AI-induced job automation had on the UK workforce, predicting significant job displacement. AI could disrupt up to 59% of tasks, especially routine cognitive ones. Initially, back-office, entry-level, and part-time jobs, such as secretarial and administrative roles, are most at risk. As AI technology advances, higher-earning occupations involving non-routine cognitive tasks may also be affected. The findings aim to guide policymakers in leveraging AI benefits while mitigating workforce disruptions. Companies should be incentivized to provide upskilling training to enhance productivity and minimize job displacement.

The Institute for the Future of Work [163] surveyed 1012 senior executives from UK firms with over 20 employees. Results showed that 79% of these firms have adopted new technologies for physical and cognitive tasks in the past three years. Small and medium-sized enterprises were automating cognitive tasks at rates similar to larger firms. While the overall impact on job creation and skill enhancement was positive, significant regional disparities persisted due to inadequate investments in education and connectivity. Improved technological readiness is essential for boosting job opportunities and skill levels across the UK workforce.

Within the European Union, Albanesi et al. [144] investigated the relationship between labor market trends and new technology adoption in 16 European countries from 2011 to 2019. They found that employment shares in AI-exposed occupations increased, particularly among younger skilled workers. Wages showed little correlation with AI exposure. The European Parliament [164,165] further indicated that AI adoption between 2011 and 2020 did not lead to widespread job losses as previously feared. This was partly due to the relatively low AI adoption rate, with only 42% of EU enterprises having implemented at least one AI technology [166].

AI’s impact on job displacement varies by gender, with AI-induced job automation primarily affecting white-collar, medium-skilled jobs. Women, who dominate office administration, healthcare, education, and social services, face significant job loss risks due to increased automation [166]. Jobs with well-defined routines and physical/manual tasks, such as agriculture and clerical work, are highly susceptible to automation. In contrast, jobs that are unpredictable (e.g., gardening and childcare) or require social intelligence and empathy are less automatable. Professions in IT, management, science, teaching, humanities, social sciences, media, law, medicine, and nursing will remain in demand [165].

The European Skills Agenda has been launched across the European Union to assist young people in developing a broad range of skills for sustainable living and working with AI-powered technologies [167,168]. These skills, known as Green Skills, encompass transversal competencies, including knowledge, abilities, values, and attitudes essential for eco-friendly practices [169,170]. Green skills, as defined by the OECD and the European Centre for the Development of Vocational Training [171], are crucial for adapting products, services, and processes to climate change, technological advancements, and environmental regulations. These include technical expertise in eco-friendly technologies and transversal competencies for environmentally conscious decision-making. Additionally, AI can significantly enhance green skills, boosting productivity while promoting environmental sustainability [172,173]. The shift to sustainable practices offers significant opportunities for upskilling and reskilling for emerging green jobs such as Sustainability Manager [174,175]. Integrating these holistic green skills into global training systems is thus vital [176].

8.4. Asia-Pacific

In this region, a survey of 19,500 professionals in 14 territories across Asia Pacific conducted by PricewaterhouseCoopers [44] revealed that 41% of employees in the Asia-Pacific region were optimistic about AI’s ability to enhance productivity. However, approximately 16% were concerned that AI might replace their jobs. Meanwhile, around 34% perceive AI as a chance to acquire new skills.

Deloitte [146] surveyed over 11,900 young employees and students and found that these young people were leading the adoption of AI, resulting in increased productivity and new skill development opportunities. In total, 76% of the respondents in China and 29% of the participants in Australia believed that AI had significantly impacted their career decision outcomes. The study underscores the need for businesses and policymakers to adapt to this rapidly evolving technology to fully leverage its benefits.

In Australia, research by McKinsey & Company [177] and ServiceNow [155] indicated that jobs involving repetitive and technical tasks were at high risk of being affected by automation. By 2030, 1.3 million workers, or 9% of the workforce, may need to change professions due to AI-driven automation. Jobs in office support, customer service, sales, and food services are most at risk.

In India, PricewaterhouseCoopers [178] surveyed 600 professionals from various job sectors in 2018. Results showed that there was a high demand for affordable, reliable services, with a preference for AI assistants over real humans in job roles such as Travel Agent, Financial Advisor, and Tax Preparer. However, for health and education, human interaction was preferred. While embracing the power of AI, the workforce feared that AI-run services would result in a loss of human touch. Another downside of AI adoption was that it created anxiety about job loss. According to the Work Trend Index 2023 compiled by Microsoft, 74% of Indian employees were concerned that AI might replace their jobs. However, 83% were open to delegating a significant portion of their workload to AI to reduce the risk of job loss posed by the technology. Comparable results were observed in the survey conducted by EY and FICCI [157]. The study indicated that approximately 37% of the Indian workforce requires reskilling. As a result of AI-induced job automation, the workforce will transition into entirely new roles that do not currently exist, many of which will demand substantially different skill sets.

In Japan, a recent Reuters survey [147] revealed that while nearly a quarter of Japanese companies have adopted AI, over 40% have no plans to utilize the technology. The survey, conducted by Nikkei Research, showed that the major reasons for adopting AI included addressing workforce shortages and reducing labor costs. However, challenges such as employee anxiety over job cuts, high costs, and lack of expertise hinder broader adoption.

In China, a survey study performed by the SAS Institute [148] showed that China leads globally in AI adoption, with 83% of Chinese respondents claiming that they are using the technology. This surpasses the global average of 54% and the 65% adoption rate in the United States. In terms of the impact AI has on employment, Wang et al. [179] used a novel task-based quantification approach to predict the effects of AI automation in the Chinese workforce using characteristics of the American job market. Findings indicated that 54% of jobs in China could be replaced by AI in the coming decades. Unit heads would be relatively secure, while jobs requiring perceptive and manipulative skills are most vulnerable to AI displacement. Contrary to the popular belief that AI will displace humans, Shen [180] demonstrated that AI increased manufacturing jobs in China, enhancing productivity and market size, and benefiting labor-intensive industries and women in digitally advanced regions.

In other Chinese regions, such as Hong Kong, Goldman Sachs [136] predicted that up to 30% of current job roles within the local labor market are exposed to AI automation, with the financial services sector facing the highest levels of impact. A recent study by Amazon Web Services [181] revealed that acquiring AI skills could significantly enhance the career prospects of Hong Kong workers, as well as boosting their productivity. The research indicated that workers with AI expertise could see salary increases of up to 28%. Despite the obvious need for more AI-skilled talent, 73% of employers face challenges in recruiting suitable candidates due to a lack of training resources and financial constraints. In addition, while professionals in Hong Kong were positive about AI, they were at the same time cautious about its adoption as they fear their jobs could be eventually replaced by AI [44].

In Singapore, an analysis by the International Monetary Fund [149] indicated that a significant portion of the workforce is at risk of automation due to the high concentration of highly skilled job roles. Approximately 77% of current job roles are highly susceptible to AI-induced automation. Among these roles, there is an equal distribution between those with high and low AI complementarity. High-complementarity roles, such as managers and professionals, may see productivity gains, while low-complementarity roles, such as clerical and administrative positions, face a higher risk of job displacement. Women and younger workers are particularly vulnerable to the adverse effects of job automation. Although job automation has the potential to exacerbate inequality, Singapore’s world-class infrastructure and skilled workforce position the country to benefit from these technological advancements.

8.5. Africa and the Middle East

In the Middle East, the impact of automation on workers was examined by McKinsey & Company [152]. Among the six countries in the region—Bahrain, Egypt, Kuwait, Oman, Saudi Arabia, and the United Arab Emirates—it was predicted that up to 45% of existing work could be automated by 2030. Notably, workers with low-to-medium levels of education and experience are particularly susceptible to automation shocks. At the same time, AI adoption was projected to drive growth and enhance productivity when the workforce is equipped with the necessary skills. Job automation is projected to bring significant benefits to the region, potentially adding around $150 billion in value. However, the current rate of AI adoption remains low. Challenges to adoption include the lack of a regulatory framework, a shortage of skilled professionals, and data privacy concerns. Despite these hurdles, the outlook for AI adoption is optimistic as Middle Eastern economies are shifting away from oil and gas, investing more in technology and education to develop future AI talent. The region has already witnessed its recent rapid growth in e-commerce, which was driven by its large technologically adept young population [153,182,183].

In Africa, the AI adoption rate remains low. As an example, a mere 9% of African media companies are making extensive use of AI tools, while 48% are employing them to a limited extent. The low rate of AI adoption is primarily due to high implementation costs and a lack of skilled personnel, with many organizations remaining hesitant to adopt AI [150]. Furthermore, 52% of businesses have yet to integrate AI tools into their operations, and 44% have not completed AI-specific training for their employees [151]. Overall, the adoption of AI is progressing slowly, hindered by inadequate infrastructure and resources, with 450 million individuals still without access to mobile broadband networks [156]. Like nations in the West, young people and women are more exposed to the risks of automation because they tend to work in low-skilled job roles [145].

8.6. Part 2 Summary

Overall, AI is transforming work by enhancing productivity and generating new job opportunities. However, it also induces anxiety, job displacement, and inequality, particularly affecting those with limited technology access, women, and younger workers [44]. Both skilled blue-collar and cognitively demanding white-collar jobs are vulnerable. Repetitive tasks, such as those in accounting and law, are highly susceptible to automation, whereas roles requiring creativity and emotional intelligence, like teaching and fine arts, are less likely to be automated [7,121]. Regional impacts vary, with significant disparities in AI adoption and job exposure. In schools, the use of AI technologies excites students and educators [30] but raises concerns about academic integrity and its potential negative effects on critical thinking and problem-solving skills [39].

AI-induced job automation impacts the workforce in the following ways. First, AI boosts productivity [120,139]. Working professionals are generally optimistic about adopting AI at work, as it allows them to focus on meaningful tasks [121]. Younger employees are particularly active AI users [146]. Automation, however, also leads to job displacement and inequality. Policies and programs aimed at reskilling and social safety nets are thus crucial [122]. At the same time, workers should acquire skills that complement AI technologies. Continuous learning and upskilling in areas less likely to be automated, such as critical thinking, creativity, and complex problem-solving, are essential [82,83,122].

Second, there are significant regional disparities in the extent of automation. For example, in the United Kingdom, 10–30% of jobs could be automated, with significant regional disparities [154]. In Japan, high costs and a lack of expertise limited AI adoption [147]. These varying results suggest that workers in highly affected regions should seek training in emerging fields and industries and gain expertise to mitigate the risks brought about by technological disruptions.

Last, AI adoption led to both optimism and fear [44]. In Europe, AI adoption has increased employment in AI-exposed occupations without widespread job loss. In Asia Pacific, 41% of professionals were optimistic about AI, but 16% feared AI-induced job replacement. For example, in Hong Kong, up to 30% of jobs are exposed to AI automation [136]. To get past the fear of being replaced by AI, workers should emphasize adaptability and lifelong learning to mitigate these fears. One solution will be for workers to focus on transitioning into AI-related roles and develop proficiency in using AI. Alternatively, they can focus on developing skills in job sectors (e.g., education) where human-centric skills are irreplaceable [82,83,122].

Within the school context, educators and policymakers can explore how AI technologies can be deployed to facilitate students’ career planning. First, computer systems powered by artificial intelligence technology can be used to help students become more aware of their career interests [184]. Second, AI systems can be used to help students conduct self-regulated learning and explore job opportunities in a particular occupation field [185]. Third, AI systems can also help learners to identify job opportunities and learn about the recent developments of the occupational fields that suit their career aspirations [186]. Last, artificially intelligent technologies such as deep learning have been found to be able to promote the formation of entrepreneurial intentions and motivate students to engage in active career planning [187].

9. Discussion

Schools play a pivotal role in fostering innovation and developing skills valued in the labor market. With rapid technological advancements, AI could soon possess the cognitive capacity to outperform a significant portion of the adult population [124]. To stay relevant, schools must adapt and understand how AI impacts employment and education for young people [46,50,134]. This approach ensures that adolescents can keep pace with technological advancements and enhance their career prospects. As AI advances, upskilling and reskilling will become essential throughout a worker’s career [121,122]. Effective school-based career guidance initiatives are vital for supporting lifelong learning and facilitating work transitions, especially as job automation becomes more prevalent. Given the nascent understanding of AI’s impact on career development, global education systems must establish policies that enhance productivity, growth, and societal well-being through the ethical use of AI [46,134]. This ensures that young people can make informed decisions based on unbiased career information and are equipped with the necessary skills to thrive in a job market increasingly exposed to job displacement and disinformation risks as AI technologies continue to advance [159].

At the system level, results from this review showed that AI enhances productivity but also causes job displacement, anxiety, and inequality. Effective career guidance and training programs are crucial to support career transitions and mitigate fears of job replacement, especially in regions with high automation exposure [154,163]. Globally, a succinct recurrent theme is that people who have difficulties accessing technology and re/upskilling programs are more likely to be exposed to the risks of job replacement due to automation [156]. This is an important inequality concern that policymakers can address by investing in large-scale re/upskilling programs [1,7,120,169,170,171]. A good example will be the policy reforms carried out within the European Union in which a skills framework delineated the qualities, skills, and values contemporary workers should possess [167]. These attributes were not only limited to cognitive skills development and technological competencies but also extended to psychological well-being and self-management, and how these qualities could be applied to promote sustainability and environmental protection [122,170,171]. The design principles adopted in these skills development frameworks can serve as a good reference for education systems worldwide for talent development. When workers are sufficiently re/upskilled, their levels of anxiety about job loss and replacement are likely to decrease as their new skill set will allow them to transition to a new job role more smoothly [79].

Furthermore, to help young people thrive in the future digital workplace and enjoy the benefits of AI adoption, policymakers can develop national-level skills frameworks that emphasize the development of human-centric skills, namely, language proficiency, empathy, adaptability, problem-solving, critical thinking, collaboration, and originality [69,76,82,83,152]. Cultivating critical thinking skills is especially important as adolescents are very likely to come across fake news and distorted information as they search for career information on the internet [129]. These skills can ensure that humans can complement and leverage technological tools rather than being replaced by them.

At the school level, as AI-induced job automation becomes more prominent, school administrators and managers must acknowledge its disruptive effects on students’ career planning [1,5,6,7,11,15,16,40,46,60]. Secondary school educators should recognize their crucial role in supporting students’ transition from school to work, as students are likely to experience anxiety and disappointment regarding their future career prospects due to technological disruption [16,44]. School administrators should proactively allocate sufficient resources to support school-based career guidance initiatives [47]. As influential figures, schoolteachers should stay informed about changes in the job market and communicate new career opportunities to students as they arise [1,52,53]. The massification of higher education has led to an increase in the number and variety of available courses. Educators must be well-versed in the career pathways these courses can lead to [16]. This can help to prevent disappointment and unemployment [51].

As AI’s power to automate work tasks enhances, the focus will shift to human-centric skills that AI struggles to replicate. These skills are, for example, critical thinking, originality, and emotional intelligence [69,161]. Schools will need to adjust their teaching priorities accordingly. Even though schoolteachers may not possess the resources to track the ongoing developments in the world of work, they can leverage their expertise to develop school-based career education programs focusing on human-centric skills and moral and civic values development [82,83,84,120,121,122,154,163]. Strengthening these foundational skills and values, together with educating students on the benefits of lifelong learning and the risks of using AI, are crucial for maintaining young people’s competitiveness in an AI-disrupted job market [44,143,146]. Additionally, mental health counseling should be offered to address anxiety and reduce stress about planning for the future [85,103]. This is essential because AI is evolving rapidly, and academic credentials alone are insufficient to assure cognitive skills proficiency [67].

As automation progresses, the skill requirements for job roles will evolve, with more tasks being performed by machines. Students must be aware of the skills they need to acquire to enhance their employability in their chosen occupational fields. Specifically, in addition to the learning of technological skills, schools should focus on the acquisition of human-centric skills [83] and green skills [168] to enhance students’ career development outcomes. It is also essential for educators to help students understand how AI may impact or enhance each job role, thereby alleviating their anxiety about the future [44,142]. In this context, schoolteachers should assist students in verifying the authenticity of career information to combat disinformation. Career guidance activities can improve students’ understanding of the current status and extent of AI-driven job automation, informing them about declining and emerging job roles [16,123]. Students can choose to focus on developing careers in roles less susceptible to automation and more reliant on human creativity, emotional intelligence, and complex problem-solving [83,85]. They should also consider careers that leverage AI to enhance productivity and creativity, as these roles are likely to expand [123]. Staying updated with technological advancements and being open to retraining and upskilling will help navigate the evolving job market [123]. However, adopting this new mindset for future career choices can be challenging, as many jobs susceptible to AI replacement (e.g., lawyer) are jobs traditionally esteemed, high-status, and well-paid [1,47]. This explains why students’ career preferences have remained consistent, often opting for jobs linked to wealth and social prestige [47].

10. Research Implications

At the theoretical level, first, there is an urgent need to focus on the development of human-centric skills that focus on influencing and relating with people [82,83,84,121,122]. Established concepts in vocational psychology, such as John Holland’s RIASEC model [78], career adaptability [79], and the recently proposed models of career capability [80] and career competencies [81], have not sufficiently emphasized the essential role human-centric skills play in an automated workplace, often overlooking changes in the world of work due to their reductionistic nature. AI advancements challenge the notion that humans are the sole providers of cognitive skills, highlighting the need for skills like leadership, persuasion, and communication to influence people [79,82,83,84,120,121,122,123]. Second, the interpersonal facets of career development should also be emphasized [97]. As AI outperforms humans in cognitive tasks, what is unique to human workers is the human-centric skills (e.g., empathetic listening) they can contribute to the workplace [82]. The concept of career adaptability, for example, is deficient in this respect as it lacks an interpersonal perspective, despite the importance of collaboration in the workplace [86].

At the practice level, the insights generated from the above analysis are summarized in

Table 4. Summary of themes identified.

Theme	Major Concepts
Promotion of lifelong learning	Career guidance should emphasize the importance of flexibility and lifelong learning, focusing on acquiring AI-related skills (e.g., machine learning and statistics) Upskilling makes students more adaptable to changing market conditions and flexible in job transitions.
Cultivate trend awareness	Understanding economic trends and regional differences in AI adoption can enhance career decision-making. Cultivate students’ understanding of which occupational fields are highly affected by AI so that they can make informed decisions.
Psychological well-being and self-management	Develop skills in psychological well-being and self-management, which is crucial because students are very likely to encounter career setbacks due to AI-induced job automation.
Human-centric skills development	Develop unique human-centric qualities such as emotional intelligence, which will help students differentiate themselves from machines and create value for employers as a human worker.
Ethical use of AI	Discuss with students the ethical issues related to the use of AI and what positive and negative implications it can bring (e.g., misformation)
Promoting green technological skills and sustainability	Integrate green skills into the school-based career guidance and counseling curricula Encourage students to think how AI technology can be used to promote eco-friendly practices and sustainable development in different job sectors

. These themes can inform the design of school-based career guidance and counseling initiatives:

Promotion of lifelong learning: School-based career guidance programs should highlight the links between flexibility and continuous learning [122,172]. As the job market evolves, students should be prepared to upskill and reskill throughout their lifespan [134]. As they upskill, this makes them more adaptable to changing market conditions and allows them to be more flexible in job transitions as more options are made available to them [167]. To adapt to changes brought about by automation, students should focus on acquiring AI-related skills (e.g., machine learning and deep learning), statistical skills (e.g., regression), and the ability to express themselves accurately and grammatically [121,122]. A good command of the English language allows students to use effective prompts when working with AI systems [75,76]. Moreover, students should be reminded to consider careers that offer flexible hybrid working modes and the potential for remote work, as these are becoming more prevalent due to technological advancements [163].

Cultivate trend awareness: Make students aware of the broader economic trends, such as the impact of AI on job markets and the potential for job displacement [7,154,164]. This knowledge can help them make informed career choices [1]. Students should become aware of the sectors most and least affected by AI. For example, finance, law, and business management roles are highly exposed to the risks of automation, while jobs requiring human interaction, like healthcare and education, are less likely to be automated [122]. Students should also be aware of regional differences in AI adoption and its impact. For instance, AI adoption rates and job displacement risks vary significantly between North America, Europe, Asia Pacific, Africa, and the Middle East [122,145,148].

Psychological well-being and self-management: Self-management skills such as resilience, stress tolerance, mindfulness, gratitude, and kindness are vital [120,121,122]. These skills help students manage their mental well-being, especially as they navigate themselves through job transitions due to automation. This is because they are likely to encounter personal setbacks and downfalls due to changes in geopolitics and the macroeconomic environment [79,85].

Human-centric skills development: As AI automates tasks, focus will shift to human-centric skills like critical thinking and emotional intelligence [120,121,122,154,161,163]. Schoolteachers can introduce students to job roles that require human interaction, human emotions, and originality, as these roles cannot be easily automated. These roles can be found in fields such as fine arts, healthcare, education, and creative industries. In addition to technical skills, students should also develop their unique human qualities. This includes strengthening skills such as cultural awareness, persuasion, leadership, flexibility, originality, communication, emotional intelligence, critical thinking, and complex problem-solving [7,67,69,82,83,84,120,154]. These emerging “human skills” are increasingly in demand and can enhance job security.

Ethical use of AI: Discuss with students the ethical issues related to the use of AI and what positive and negative implications it can bring. These issues are, for example, biases and misinformation, equity, academic integrity, and how over-reliance on AI could impact the development of cognitive abilities [40,44,46,70,71,72,178]. Encourage students to think critically about how they can contribute positively to these fields and contribute to the positive development of mankind [69]. Teachers should also keep themselves informed about the latest developments in the job market so that they are proficient enough to identify fake or distorted career information [1,5,6,16].

Promoting green technological skills and sustainability: green skills encompass a range of competencies, values, and knowledge aimed at promoting environmental sustainability [166,170]. These skills enable students to engage in eco-friendly practices, develop innovative solutions for environmental challenges, and contribute to a greener economy [168]. Integrating green skills into the school-based career guidance and counseling curricula can prepare students for future job markets. This includes job roles about renewable energy, sustainable agriculture, and waste management [169]. Encourage students to think about how AI technology can be used to promote eco-friendly practices and sustainable development in different job sectors [171].

At the policy level, it is crucial for governments to carefully assess and manage the risks associated with AI-driven job automation. The primary benefits of automation include increased work productivity and the streamlining of workflows by automating routine administrative tasks [120]. This allows workers to focus on higher-value tasks, thereby enhancing productivity and creating more value for businesses [143]. For students, early research indicates that AI technologies can support the development of self-regulated learning practices and foster creativity and critical thinking [32,33,34]. However, as AI technologies continue to evolve, machines are expected to surpass human cognitive abilities in all tasks [188]. Therefore, policymakers must provide upskilling programs and social safety nets to help students overcome the negative impacts resulted from AI-induced job displacement/redundancy [122] and income inequality [156].

As we begin to develop more understanding about AI technologies, recent research evidence suggests that AI can lead to reduced levels of cognitive engagement in both academic and work-related tasks [25,38,39,133,189]. Prolonged engagement with AI can also impede judgment and decision-making due to misinformation [69]. To address these issues, it is crucial for governments to develop frameworks and regulations governing the ethical use of AI technologies. [190,191].

11. Limitations

This review has several limitations. First, only published studies were included, so there may be other relevant materials on the same topic. Second, due to the rapid advancement of AI technologies, this review only provides an overview of the extent of AI disruption at the current state of technology, that is, GPT-4, at the time of writing this paper. Therefore, the analysis in this article serves only as a general guide for school-based career guidance and counseling, as career information about this topic is extremely scarce. Last, the methodologies used in expert reports and academic articles on AI-induced job automation vary significantly. This inconsistency makes comparisons and summarization of quantitative results difficult and potentially wrongful [14,15]. To this end, this review does not aim to predict/measure the speed and scope of AI-induced job automation in disrupting the career planning of secondary students. Instead, it summarizes expert estimates to help readers form a more coherent understanding of the topic.

12. Conclusions

In summary, schools must swiftly adapt to AI advancements, promoting innovation and human-centric skills. Teachers should create school-based career programs to prepare students for AI’s impact on employment and lifelong learning. Lifelong upskilling and reskilling are essential. Policymakers and school managers must invest in extensive re-/upskilling programs to address inequality, especially as automation accelerates [134,158,161]. Global education policies should enhance productivity and societal well-being through ethical AI use. The EU’s skills framework [168,169,170], emphasizing cognitive skills, technological competencies, and sustainability, can serve as a model. Developing human-centric skills like critical thinking and career flexibility is crucial for thriving in the AI-driven job market. National skills frameworks should prioritize language proficiency and human-centric skills to help young people excel in the digital workplace and leverage AI effectively [122]. Incorporating these insights into career guidance and counseling will better prepare students for the future job market.