Abstract
For years, the future of work debate has centred on AI automation and which jobs may be replaced by technology. Yet the emerging evidence points to a more nuanced reality. While some tasks are increasingly automated, many of the fastest-growing opportunities will belong to those who can effectively augment AI, combining technical capability with human judgement, creativity and problem-solving.
For universities, understanding this balance is becoming a strategic imperative. Which skills are declining in value? Which capabilities are becoming more important? And how can institutions prepare graduates for continuous adaptation rather than a single job? As these shifts accelerate, the ability to demonstrate a clear connection between learning, skills and career outcomes will become an increasingly important differentiator for universities on employability.
This presentation will explore how AI is reshaping workforce demand and redefining graduate outcomes. Drawing on global skills and labour market trends, it will identify the capabilities most likely to drive success in an AI-enabled economy and share real-world examples of how universities are using labour market intelligence to address skills gaps and connect education more closely with evolving employer needs.
Institutional examples:
- Using labour market intelligence to shape curricula: Universidad Indoamérica used labour market data to analyse 20 programmes against employer demand and emerging skills needs, informing learning outcomes, graduate profiles and programme development.
- Connecting learning with career decisions: Purdue University embedded labour market intelligence into a mandatory first-year engineering course for 270 students, helping them connect their skills and interests with career pathways and employer demand, and make more informed choices about their engineering major and future career.
Learning objectives
- Understand how AI is shifting workforce demand from automation to augmentation, drawing on the QS World Future Skills Index.
- Identify the human capabilities that will differentiate graduates in an AI-enabled economy.
- Explore the implications for graduate outcomes, employability, and curriculum design.
- Provide examples of how data can be applied and can lead to improved curriculum design, career readiness and improved course satisfaction.
Target audience
University leaders, academic and curriculum innovators, employability and careers professionals, international strategy teams, industry engagement leaders, and policymakers seeking to strengthen graduate outcomes and workforce relevance in the age of AI.