AI/ML, Employability and Higher Education - Roundup 09 Jun 2025

The articles highlight the rapid integration of AI across industries, emphasizing its potential to both enhance and disrupt traditional job roles while raising concerns about ethical data usage and job displacement. Universities are called upon to adapt their curricula and teaching methods to prepare students for an AI-driven workforce, focusing on developing critical thinking skills, domain expertise, and the ability to work alongside AI technologies.

While some articles (Clark 2025; Raval 2025) report on the growth of AI-related job opportunities, others (Nolan 2025; Levy 2025) warn of potential job losses due to AI automation. There are also contrasting views on the ethical development of AI, with some companies claiming it’s impossible to create AI without using copyrighted data (Landymore 2025), while others are actively working on “ethical” AI models trained only on licensed or public domain data (Shapiro 2025).

• Clark (2025) reports a 21% increase in UK tech job openings, with a 200% surge in demand for AI skills, highlighting the growing importance of AI expertise in the job market. This trend underscores the need for universities to incorporate AI education into their curricula to meet industry demands.
• Raval (2025) discusses how AI is reshaping jobs across industries, emphasizing that while some roles may be displaced, new opportunities are emerging that require a blend of AI literacy and human skills. This shift highlights the importance of universities adapting their programs to prepare students for an AI-augmented workforce.
• Shapiro (2025) explores Hollywood’s quiet adoption of AI in film production, raising questions about job security and the ethical use of AI-generated content. This article is relevant as it showcases the need for universities to address ethical considerations in AI usage across creative industries.
• Levy (2025) presents an interview with Google DeepMind’s CEO, who predicts that AI will lead to an era of “radical abundance” but may also eliminate many current jobs. This perspective is crucial for universities to consider as they prepare students for a future where AI could significantly alter the job landscape.
• Taylor (2025) discusses how attacks on science and research in the US could benefit China in the AI race, emphasizing the importance of maintaining strong research capabilities. This highlights the need for universities to foster robust AI research programs and international collaboration.
• Vaughan-Nichols (2025) introduces a new “FinOps for AI” certification aimed at managing surging AI costs in businesses. This development is relevant to universities as it indicates a growing need for professionals skilled in AI cost management and optimization.
• Rajkumar (2025) reports on AI pioneer Yoshua Bengio’s efforts to make AI safer through non-agentic systems, contrasting with the industry trend towards autonomous AI agents. This research direction is important for universities to consider in their AI ethics and safety curricula.
• Kailas (2025) argues that AI’s primary threat is not to individual jobs but to entire companies that fail to adapt, emphasizing the need for organizational agility. This perspective is crucial for universities to incorporate into their business and management programs, preparing students to lead AI-driven organizational transformations.

The articles collectively paint a picture of AI as a transformative force in the job market, simultaneously creating new opportunities and posing challenges to existing roles and entire organizations. While the immediate impact varies across industries, there is a consistent emphasis on the need for adaptability, ethical considerations, and a blend of technical and human skills. Universities play a crucial role in preparing the future workforce, necessitating a reevaluation of curricula, research priorities, and teaching methodologies to equip students with the skills needed to thrive in an AI-augmented world.

1. Changes in the broader labour market: Educators must prepare students for a job market increasingly dominated by AI-related skills (Clark 2025; Raval 2025). This includes not only technical AI expertise but also the ability to work alongside AI systems and leverage them effectively across various industries. Universities should consider integrating AI literacy across all disciplines, not just in computer science or engineering programs.

2. Changes in jobs and tasks: AI is reshaping job roles, often augmenting rather than completely replacing human workers (Raval 2025; Levy 2025). Educators should focus on developing students’ adaptability and critical thinking skills, enabling them to navigate a work environment where task allocation between humans and AI is fluid. This may involve teaching students how to effectively prompt and direct AI tools, as well as how to critically evaluate and refine AI-generated outputs.

3. Types of study needed: Students must develop a combination of technical AI knowledge, domain expertise, and soft skills to thrive in the evolving labour market (Kailas 2025; Vaughan-Nichols 2025). Universities should offer interdisciplinary programs that combine AI studies with specific industry knowledge, while also emphasizing ethical considerations and the societal impact of AI (Shapiro 2025; Rajkumar 2025). Additionally, fostering research skills and innovation mindset is crucial, as highlighted by the ongoing AI race between nations (Taylor 2025).

Sources