Graduate employability and the Senate inquiry: What the politics misses

Graduate employability and the question of whether universities are adequately preparing graduates for work is not new, but policy pressure on the topic has been escalating over the last few years. Governments have already tried one heavy-handed policy lever in response to it: the 2020 Job-Ready Graduates package, which attempted to use differential fee structures to redirect student demand toward fields deemed more aligned with labour market needs. That policy attracted criticism from the outset and has not produced the graduate employment improvements its architects anticipated.

The Senate’s Education and Employment References Committee has now been referred an inquiry into ‘the rise in the number of Australian university graduates who struggle to find work’. Senator Fatima Payman’s motion frames the problem as the responsibility of universities. Graduates were promised that study would be rewarded, the promise was not kept, and the committee will examine everything from the entry-level job market to “the quality of university education in Australia.” Times Higher Education covered the referral in detail, noting both the data Payman cited (a 26% rate of graduate underemployment six months post-completion in 2024, up five percentage points on the year before) and the political dynamics of an opposition-chaired committee with every incentive to make findings uncomfortable. Submissions close in June; the committee reports in November.

The inquiry arrives alongside several other pressures on the sector: the December 2025 Senate governance inquiry final report, the passage of the ATEC legislation, a Four Corners investigation into university finances and governance, and sustained public debate about whether universities have lost their social licence. Together these represent a sector under simultaneous scrutiny from multiple directions.

I want to engage with the substance of the Senate Inquiry, because graduate employment outcomes are important and some of what is being raised is legitimate. I think that the inquiry’s framing obscures more than it illuminates, and the policy responses it is likely to generate will be inadequate unless the full complexity of the problem is properly understood.

What universities are actually doing

The inquiry’s implicit premise, that universities have been inattentive to graduate employability, sits uneasily with the evidence. Australian universities have invested substantially in work-integrated learning (WIL) over the past two decades, driven partly by graduate outcome performance metrics and partly by institutional commitment to employability as a dimension of educational quality. The research base on WIL is robust. Participation in well-designed WIL experiences consistently improves graduate employment outcomes, with effects documented across disciplines and institution types. Career development learning, embedded across curricula at numerous institutions, also shows positive effects on graduates’ capacity to navigate transitions over the longer term.

There is unevenness of employability development across the sector, and I would not want to overstate the case. Some disciplines and institutions have progressed considerably further than others, and overall the equity dimensions of employability support remain insufficiently addressed. I’d suggest that initiatives under The Accord like Support for Students, needs based funding and the Commonwealth Prac Payment fall well short in improving student access and equity issues relating to WIL and employability development. The CPP, for instance, covers only students in Commonwealth-supported places undertaking professionally accredited placements in certain disciplines. It’s a start, but we have a long way to go (I may address this further in a blog post at another time).

Still, “the sector has not tried” is not an accurate characterisation of where things stand, and accepting that framing forecloses more useful questions about why progress has been uneven and what conditions would accelerate it.

The supply-side/demand-side problem

The structural issue that the inquiry’s terms of reference largely sidestep is that universities control the supply side of graduate outcomes, and have very little control over the demand side. Denise Jackson and I argued exactly this point in our article in The Conversation as early as 2019.

Graduate employment is a labour market outcome, shaped by employer hiring practices, industry investment in early-career development, macroeconomic conditions, and government policy settings around skills, migration, and economic structure. Economic modelling by the Centre for Future Work joins a long line of econometric analyses showing that short-term graduate employment outcomes correlate more strongly with macroeconomic conditions and employer demand than with graduate attributes or qualification type. The 24% decline in graduate job postings in 2024 cited in Payman’s speech, is clearly a demand-side signal, and largely shows a correction back to pre-COVID levels of employer demand for university graduates. Universities did not produce that decline and cannot reverse it through curriculum reform alone.

A Senate inquiry that focuses its analytical lens on universities while not examining employer behaviour, industry investment in graduate development, and government labour market policy risks a serious misattribution of causation.

AI disruption is shared and unresolved

The inquiry’s terms of reference include the impact of artificial intelligence on graduate employment, and here the picture is particularly complex. Senator Payman described a “bizarre battle of simulacra” in which AI-mediated recruitment processes screen graduates before any human has read their application. This is a real and growing phenomenon that warrants attention.

What the political commentary has not yet grappled with is that employers are working through their responses to AI-disrupted work at the same time as universities, not ahead of them. In my very recent research (Bridgstock & Kuek, under review), we surveyed employers who host WIL and/or recruit graduates, examining GenAI adoption and its implications for graduate roles and recruitment. Adoption remains uneven and concentrated in routine, repetitive, and first-pass tasks rather than relational or high-judgement work. Most employers reported no widespread loss of graduate roles in the past twelve months, though a significant proportion anticipate moderate role reconfiguration over the next two to three years.

In my research, employers consistently described navigating AI adoption in real time –  experimenting, setting governance constraints, and adjusting expectations incrementally. An unprompted finding was that several employers reached out after completing the survey to reassure universities that graduates remained important and that WIL opportunities would continue.

Holding universities solely accountable for preparing graduates for conditions employers themselves are still navigating is a misdirection. What employers in my research did consistently ask for was closer collaboration with universities, to enable faster curriculum responsiveness, more authentic industry-connected learning, and a relationship of co-navigation rather than parallel adjustment in working through AI’s educational implications.

What does need to change

None of what I have said is an argument for complacency. Universities do need to change, and to become better at change. The shift toward skills-based hiring has real implications for how we credential, communicate, and design learning. My research findings show that employers want graduates who can exercise AI-related judgement and fluency. This is not just basic tool use, but the capacity to evaluate AI outputs critically and also make decisions about when and how AI should be used.

Changing student cohort needs around things like flexibility, support, and the pacing of learning across life and work, require institutional responses that many universities are still developing. As I have been arguing in my series of posts on future and change capability in higher education, institutions cannot cultivate adaptive graduates without being adaptive themselves. That institutional adaptability is constrained by funding models, governance structures, and policy settings outside universities’ unilateral control. This then returns us to the question of what kind of policy response the current situation actually warrants.

A question about the inquiry itself

I think it is worth being direct about what a Senate inquiry of this kind is structured to produce. Inquiry mechanisms are well suited to identifying problems, generating political accountability, and signalling community concern. They are considerably less suited to producing the collaborative, multi-actor strategy that graduate employment challenges require.

Put in terms of government priorities, higher education remains the chief producer of professional-level human capital. The sector is navigating substantial structural change, including financial strain, AI disruption, shifting student demographics, and funding volatility. It is simultaneously being asked to deliver better outcomes for a more diverse student population than at any point in its history.

An inquiry whose terms of reference locate the graduate employment problem primarily in university practice, while leaving employer behaviour, industry investment, and government labour market policy largely unexamined, is unlikely to produce findings proportionate to the problem’s complexity. This scrutiny also arrives after years of funding decline, following an international enrolment shock, during active workforce restructuring at numerous institutions.  These contextual factors do not place the sector above accountability, but they do raise the question of whether adversarial scrutiny is the right instrument for a moment that calls for something more constructive.

What would actually help

I suggest that rather than a Senate Inquiry, the situation calls for a co-designed national strategy. The strategy would map the full causal structure of graduate employment challenges and distribute accountability across the system accordingly. That means government taking its obligations seriously around labour market policy, economic conditions, and education funding. It means industry being explicit about its investment in early-career development, the evolution of hiring practices, and its shared responsibility for navigating AI’s implications for the graduate pipeline (as employers in our research indicated they were willing to do). And it means universities continuing to develop, honestly evaluate, and improve their employability provision, particularly in the areas where progress has been slowest.

The graduate talent pipeline is a shared infrastructure. It functions when all contributors – institutions, employers, government, and students themselves – work together and are held to account for their roles. There is a difference between accountability applied across a whole system and attribution concentrated on one part of it. Right now, the sector needs a partner in navigating a genuinely difficult moment, not a framing that treats universities as the source of a problem with many authors.

Bridgstock, R., & Kuek, M. (under review). Will a robot steal my internship? Generative AI, WIL, and graduate work in Australia: Implications for education. International Journal of Work-Integrated Learning.

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100 Jobs of The Future: what are the job roles that could be created in the next few years?

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Media reports and scholarly literature alike tend to emphasise the jobs that might / will disappear over the next few years under the influence of automation and artificial intelligence. Some reports suggest that as many as 50% of job roles will disappear. Others suggest that work might eventually become a thing of the past entirely, resulting in either a leisure-based utopia and universal income for humans, or the end of society, economy, and possibly even civilisation as we know it.

Over the past 5-6 years that I’ve been active in this area of research, I’ve worked to temper these claims. Yes, some roles have disappeared already (typesetter, switchboard operator, toll and parking fee collector…) It is very likely that other roles will follow behind them in the next few years (tax accountants, warehouse jobs, many types of customer service roles, telemarketers [yay!]…) Other jobs roles will continue to exist, but the tasks inside those roles will become more about (i) interacting with technology, and (ii) things that only humans can do (or things that it is too expensive for machines to do).

I’ve always wanted to know about the other side of this story: Could there be jobs that become more common? Will there be entirely new jobs created?
This is what the ‘100 jobs of the future’ research project is about.

I (at Griffith University) worked with colleagues from Deakin University (Russel Tytler and Peta White), with funding supplied by Ford Australia, to try to figure out what the ‘uniquely human’ job roles might be in the next 20-30 years, including some entirely new roles. We explicitly wanted to provide a counterpoint to the ‘Robots are Coming For Our Jobs’ narrative, and to inspire young people to think about the possibilities that they might be able to find or create for themselves.

We interviewed a range of experts in technology, science, and various social science-based fields, to figure out what the key broad trends were that might impact on the world of work over coming decades*. By overlaying these trends onto one another, we were able to construct job roles and descriptions, and an indication of the kinds of human capabilities that might be required to do them. We then built a quiz based on career theory to help young people identify future job roles that might suit them, and to get them started in developing their interests and capabilities.

It was a really fun project. The report, quiz, and supporting educational materials are available at 100jobsofthefuture.com

Here are the jobs:
• 100 year counsellor
• Forensic data analyst
• Energy and data systems installer
• Additive manufacturing engineer
• Freelance virtual clutter organiser
• Entomicrobiotech cleaners
• Aesthetician
• Fusionist
• Ethical hacker
• Aged health carer of the future
• Gamification designer
• Farm safety advisor
• Aged persons climate solutions consultant
• Genetics coach
• Flood control engineer
• Agroecological farmer
• Haptic technology designer
• Food knowledge communicator
• AI educator
• Health shaper
• Trendwatcher
• AI intellectual property negotiator
• Human habitat designer
• Virtual and augmented reality experience creator
• Algorithm interpreter
• Innovation manager
• Virtual assistant personality designer
• Analogue experience guide
• Integrated ecology restoration worker
• Virtual surgeon
• Automated transit system troubleshooter
• Integrated energy systems strategist
• Waste reclamation and upcycling specialist
• Automation anomaly analyst
• Integrated home technology brokers
• Water management specialist
• Autonomous vehicle profile designer
• Lifelong education advisor
• Weather control engineer
• Behaviour prediction analyst
• Local community co-ordinator
• Drone experience designer
• Biofilm plumber
• Machine-learning developer
• Early childhood teacher
• Bio-jacker
• Massive 3D printed building designer
• Terraforming microbiologist
• Biometric security solutions engineer
• Mechatronics engineer
• Biomimicry innovator
• Media remixer
• Bioprinting engineer
• Memory optimiser
• Blockchain talent analyst
• Multisensory experience designer
• Chief digital augmentation officer
• Nanomedical engineer
• Chief ethics officer
• Net positive architect
• Child assistant bot programmer
• New materials engineer
• Community farm finance broker
• Nostalgist
• Community support worker
• Nutri-gutome consultant
• Cricket farmer
• Offworld habitat designer
• Cross-cultural capability facilitators
• Personal brand manager & content curator
• Cyborg psychologist
• Personalised marketer
• Data commodities broker
• Predictive regulation analyst
• Data farmer
• Quantum computer programmer
• Data privacy strategist
• Real-virtual transfer shop manager
• Data storage solutions designer
• Regional community growth co-ordinator
• Data waste recycler
• Robot ethicist
• Data-based medical diagnostician
• Robot mechanic
• Decision support worker
• Satellite network maintenance engineer
• De-extinction geneticist
• Shadowtech manager
• Digital apiarist
• Sharing auditors
• Digital implant designer
• Smart dust wrangler
• Digital memorialists and archivists
• Space tourism operator
• DigiTech troubleshooter
• Sportsperson of the future
• Displaced persons re-integrator
• Sustainable energy solutions engineer
• Drone airspace regulator
• Swarm artist

*I acknowledge that some have crticised the use of trends (and megatrends) to predict the future. These people argue that some of the most impactful influences are very difficult to predict – they are truly disruptive and result in what Kuhn would call paradigm shifts. This means that the some of the jobs in the list might be too ‘safe and predictable’, and too like our job roles of the present. I think that it’s still worthwhile to do the research. While not every job role we’re predicting will happen, and others will be too similar to jobs of today, it’s worthwhile to use the jobs we’ve created as a somewhat concrete launch point to think about the kinds of things we might be doing in 20-30 years time. In turn, we can use these jobs to inform our design of broad-based educational experiences so that people have the right kinds of capabilities.Facebooktwitterredditpinterestlinkedinmail

Grand Challenge Lecture: Future Capable — Learning for Life and Work in the 21st Century

Last month I delivered a ‘grand challenge’ public lecture at Queensland University of Technology. The Institute for Future Environments hosts these lectures, which, as you’d expect, are all about the big challenges facing humanity, from feeding the world’s booming population to managing scarce natural resources and reducing our carbon footprint. Over the years they’ve hosted people like Professor Federico Rosei from the University of Quebec, who presented on new technologies for energy sustainability, and Professor Kevin Burrage from Oxford University, talking about personalised medicine.

My lecture was (of course!) about why, given disruptive changes to the world of work, society, and education, we all need to be future capable, what future capability means, and how we can all learn to be future capable.

Here’s the abstract:

This presentation asks what it means to be capable in the context of a world of work and society undergoing massive disruptive change under the influence of digital technologies. It engages with the key shifts that are occurring to the labour market, work and careers, and explores the 21st century capabilities and skills that research suggests will be important to graduates’ productive participation in the years to come, including capabilities for complex problem solving and innovation, enterprise and career self-management, social network capabilities, and digital making skills. It suggests some key ways that universities can foster 21st century capabilities, and some strategies for building agile and dynamic educational institutions that are as ‘future capable’ as the graduates they produce.

And here’s the lecture itself:

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