AI/ML, Employability and Higher Education - Roundup 31 Mar 2025

The articles examine how AI and machine learning are reshaping the workforce across industries, from software engineering to law to finance. There is a growing focus on AI agents that can autonomously complete complex tasks, potentially displacing skilled workers, which has major implications for how universities prepare students for future careers.

While most articles highlight AI’s potential to boost productivity, there are conflicting views on the pace and extent of job displacement. Some predict rapid automation of many skilled jobs, while others argue human expertise will remain essential in most fields. There are also differing perspectives on whether AI tools will primarily enhance human capabilities or replace human workers entirely in certain roles.

• Okemwa (2025) reports that OpenAI’s CEO predicts AI will gradually replace software engineers, creating an urgent need for students to master AI tools. This highlights how even highly skilled technical jobs may be vulnerable to AI automation, requiring universities to rethink how they train computer science students.
• Schifeling (2025) warns job seekers against over-relying on AI-generated application materials, as it makes candidates blend together. This suggests students need to develop unique skills and experiences that differentiate them from AI, not just technical prowess.
• Chowdhury (2025) outlines three key skills software engineers need in the “vibe coding” era: embracing AI tools, improving prompts, and mastering clear thinking. This indicates how technical education must evolve to emphasize working alongside AI rather than competing with it.
• Susskind (2025) predicts AI could replace traditional lawyers by 2035, fundamentally reshaping the legal profession. This has major implications for law schools in how they prepare students for a radically different future of legal work.
• Burn-Murdoch (2025) analyzes employment data to show AI is already displacing some writers and software developers, while other at-risk jobs remain unaffected so far. This nuanced picture suggests universities need to closely monitor industry trends to understand which skills remain in demand.
• Thompson (2025) reports how major consulting firms are developing AI agents to autonomously complete complex tasks, aiming to “liberate” staff time. This trend toward agentic AI could reshape many knowledge worker roles, requiring broader changes in professional education.
• McKendrick (2025) discusses the challenges of scaling agentic AI, noting only 13% of projects deliver significant results so far. This suggests the need for universities to cultivate skills in effectively implementing and managing AI systems, not just developing them.
• Adams (2025) explores how AI tools could free up teachers’ time from administrative tasks, allowing more focus on students. This demonstrates how AI might enhance rather than replace skilled professions, requiring nuanced integration into professional training.

The articles paint a picture of AI as a transformative force in the job market, with the potential to both enhance human capabilities and displace certain roles. While the exact pace and extent of this transformation remain uncertain, it’s clear that higher education must evolve to prepare students for this new reality. This involves not just teaching technical AI skills, but cultivating the uniquely human capabilities that will remain valuable alongside AI, as well as the adaptability to navigate ongoing changes throughout their careers.

1. Changes in the broader labour market: Educators must prepare students for a rapidly evolving job market where AI is reshaping roles across industries (Okemwa 2025; Susskind 2025). This requires cultivating adaptability, lifelong learning skills, and the ability to work alongside AI systems. Students should understand both the potential and limitations of AI in their chosen fields.

2. Changes in jobs and tasks: Many professions are seeing a shift in task composition, with AI taking over routine cognitive work while human expertise focuses on higher-level analysis, creativity, and interpersonal skills (Chowdhury 2025; Adams 2025). Educators should emphasize these uniquely human capabilities alongside technical skills, helping students understand how to add value beyond what AI can do.

3. Required student preparation: To thrive in the AI era, students need a combination of technical AI literacy, strong domain expertise, and critical thinking skills (Thompson 2025; McKendrick 2025). Universities should integrate AI tools into existing curricula while also teaching students how to critically evaluate AI outputs, understand AI’s societal impacts, and identify opportunities to innovatively apply AI in their fields.

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