Let’s examine the effects of AI on employment dynamics, skill requirements, and the emergence of new job roles.
Learning Objectives
- To Evaluate AI's effects on different job categories
- Identifying Key Skills
- Develop strategies for adapting skills in the AI era
- Exploring Strategies for Career Guidance
Introduction
Embracing AI: Shaping the Future of the European Workforce
As we stand on the brink of a technological revolution, the European Union finds itself at a pivotal moment, where the transformative potential of Artificial Intelligence (AI) promises to reshape the landscape of its workforce. With advancements in AI technology accelerating at an unprecedented pace, the European workforce faces both opportunities and challenges on the horizon. As AI integration becomes increasingly prevalent across industries, from manufacturing to services, the skills required to thrive in the workforce are undergoing a profound evolution. This evolution will not only impact the nature of work itself but also necessitate a reevaluation of education and training paradigms to ensure that European workers remain competitive in an AI-driven global economy.
How does AI affect employment demand
When contemplating the ongoing and future changes in the job market affected by AI, or any form of automation, it proves beneficial to consider three interconnected concepts:
In the context of AI, automation refers to the process whereby machines take over some or all of the tasks typically performed by humans in a job. According to D.Autor’s survey (2022), this can range from simple, repetitive tasks to more complex ones, enabled by advancements in artificial intelligence and robotics. In fact, empirical data from the USA and Europe suggest that jobs at risk of automation often fall in the middle of the occupational hierarchy, such as skilled trades jobs. Jobs that involve tasks following explicit rule sets are more likely to be automated. These tasks may be relatively complex but can be replicated by computer programs. For example:
- Data Entry Clerks: Tasks involving data entry and processing may be automated using software solutions.
- Manufacturing Machine Operators: Routine tasks on assembly lines could be automated with robotics and machinery.
- Cashiers: Automated checkout systems in retail environments may reduce the need for human cashiers.
- Administrative Assistants: Automation software can perform tasks such as scheduling appointments, managing emails, and generating reports, decreasing the need for manual administrative work.
Conversely, high-skill jobs requiring abstract thinking and interpersonal skills, like managerial and professional occupations, are less susceptible to automation. Some other lower-skilled workers will also be safe from automation, such as waiters or cleaners. These roles involve tasks that cannot be easily reduced to explicit rules for replication by machines, but will probably undergo some changes (which could require somekins of AI skills)
Augmentation involves the use of AI and technology to complement the tasks undertaken by human workers, thereby increasing their productivity and efficiency. Rather than replacing humans entirely, machines work alongside humans to enhance their capabilities and performance in various tasks and roles. For example:
- Medical Laboratory Technicians: Automation can assist in data analysis and sample processing, allowing technicians to focus on complex tasks and interpretations.
- Automotive Technicians: AI diagnostic tools can augment technicians' abilities to diagnose vehicle issues accurately.
- Electricians: Augmented reality (AR) tools can assist electricians in visualizing wiring diagrams and troubleshooting electrical systems.
- Automotive Body Repairers: Augmented reality tools can overlay repair instructions and diagrams onto damaged vehicles, aiding technicians in complex repair processes.
According to Autor, D., Salomons, A., and Seegmiller, B. (2021) technological advancements do not occur in isolation; they create new tasks and jobs. This leads to a "task reinstatement effect," where new jobs or tasks emerge alongside automation, leading to the emergence of new skill requirements. Evidence shows that technology indeed creates new forms of employment, with around 60% of US employment in 2018 being in job titles that did not exist in 1940. For example:
- Construction Project Managers: Emerging technologies in construction may create new tasks for project managers, such as overseeing the integration of automation systems or coordinating drone surveys for site inspections.
- Solar Panel Installers: Task reinstatement could occur with the emergence of new renewable energy technologies, creating demand for VET professionals to install and maintain solar panel systems.
- Renewable Energy Technicians: As renewable energy industries grow, VET professionals may see new tasks related to maintaining and servicing wind turbines, solar panels, and other green technologies.
- Cybersecurity Specialists: As technology evolves, new tasks may emerge for cybersecurity professionals to protect against emerging threats, implement new security measures, and analyze cybersecurity trends.
As long as this reinstatement effect outweighs the automation effect, labor demand will increase. However, there is no consensus on the scope of these changes:
- A recent report on analysis by the Institute for Public Policy Research (IPPR) said the UK was facing a “sliding doors” moment around its implementation of generative AI: while the first wave is already under way, an upcoming second wave in which companies will more deeply integrate AI tech into their processes - a stage at which it suggests as many as 59 per cent of tasks done by workers could be vulnerable to being replaced by AI automation if no intervention occurs, with women and young people the most likely to be affected as they are more likely to be in those jobs.
- However, according to Acemoglu, D. and Restrepo, P. (2020), when technological changes, such as those driven by AI, result in weak productivity growth, job creation may also be weak. Some western economies have experienced this issue recently. The tasks automated so far have led to relatively weak productivity growth, limiting the reinstatement effect and thus impacting job creation.
Tackling the upcoming skill gaps
According to the EU Coordinated Plan on Artificial Intelligence and CEDEFOP, AI and digitalization are expected to have a significant impact on the skills demand: there will be a need for adaptation in skills and training due to the changes AI will bring to the job market.
As AI technologies continue to advance and become more integrated into various industries, workers will need to adapt and acquire new skills to remain competitive in the job market. The spread of digitalisation in labor markets is offering marked opportunities for transformation in jobs and business models. Unfortunately, as the demand for digital skills, including AI skills, is increasing, there is a risk of a digital skills divide in the EU labor markets. While there is already a high demand for advanced digital skills -crucial for jobs expected to grow in the next decade-, about 33% EU workers are already at risk of digital skills gaps. This shift in the skills landscape underscores the importance of education and training in preparing the European workforce for the AI-driven economy.
Some ways in which AI will affect the skills workers should learn include:
To further enhance the effectiveness of career orientation for vocational training students, consider the following additions and modifications:
Personalized Pathways: Utilise advanced analytics to create personalized career pathways for students. By leveraging data on individual skills, interests, and career goals, programs can offer tailored guidance that aligns with both student aspirations and market needs. This personalized approach ensures that each student receives targeted support to maximize their potential and success in the workforce.
Adaptive Curriculum: Develop an adaptive curriculum that evolves with technological advancements and market shifts. Engage with industry experts and stakeholders to regularly review and update training materials, ensuring they remain relevant and aligned with current industry standards. An adaptive curriculum enables students to acquire cutting-edge skills and stay ahead of the curve in rapidly evolving industries.
Strategic Partnerships: Establish strategic partnerships with local businesses and industry leaders. Collaborating with employers allows vocational training programs to gain valuable insights into industry needs and tailor their offerings accordingly. These partnerships can lead to the creation of specialized training programs, apprenticeships, and internship opportunities that provide students with hands-on experience and a direct pathway to employment. Additionally, partnerships with industry leaders can provide students with exclusive insights into industry trends, best practices, and career pathways, enhancing their overall career readiness.
Industry Insights: Integrate real-time labor market data into career guidance programs. By incorporating current industry trends and skill demands, students can gain valuable insights into emerging opportunities and make informed decisions about their career paths. Access to up-to-date information will enable students to anticipate future job prospects and tailor their training accordingly.
Overall
The advent of Artificial Intelligence in the labor market implies a profound transformation that necessitates a shift in the guidance provided to students and future workers. The automation of certain jobs, particularly those involving routine tasks, is a reality. However, AI also enhances and creates new roles requiring more complex, abstract thinking and interpersonal skills. Adaptability, continuous learning, ethical reasoning, data literacy, and technical competencies are becoming increasingly important. Balancing job automation and augmentation, adapting to skill mismatches, and considering the ethical and social implications of AI in the workplace are crucial aspects of this transformation. This change is not just about the evolution of jobs but also about how we prepare for and adapt to these changes. It’s a comprehensive endeavor that involves educators, policymakers, and individuals to prepare the workforce for the future AI-driven economy.
