The economics job market is in a period of change. The march of AI in work and research presents myriad opportunities but requires new skills in candidates, which recruiters need to be able to identify. The recognition that some tasks, for example coding/modelling or research, can be supported by, or even in part largely carried out by AI tools, means roles need to be adjusted, reduced, or merged into other positions.

Moreover, the use of AI by applicants to “flood” recruiters with a large number of, in many cases, lower quality AI-generated applications, presents a challenge both for recruiters and for those high-quality candidates who want to stand out from the crowd. Times are turbulent, and national prioritization, budget restraints and global uncertainties contribute to a more cautious approach for recruiters of academics in economics. At the same time, a labour surplus creates challenges for recruiters – as well as candidates.

Indeed, in 2026 the market is fractured, with economists and economics graduates being recruited through a range of channels. Traditional recruitment events like the AEA meeting in the US, and job boards like INOMICS continue to be the most important channels for successful economics and finance specific recruitment. But they are increasingly complemented by other approaches: from direct outreach through existing networks, to recruitment via large international platforms, which are tempting recruiters with low prices, modern user interfaces and impressive (sounding) AI tools. However, these alternative channels present their own challenges for recruiters. 

Candidate Applications in 2026 – Zero Marginal Costs

Gone are the days where a strong candidate could shine through with some impressive points on their CV and a well crafted cover letter. Instead candidates need to demonstrate both the skills increasingly demanded by employers (and by extension the wider economy and/or funding bodies), as well as the ability to prepare and send applications that can both pass an AI filter, and impress a human recruiter.

Ideally, a recruitment process will identify those candidates who will perform well once employed. Depending on the position, this might mean being able to engage students in a teaching role, contribute to meaningful research, navigate funding applications and win grants, or a combination of all these and more.

In reality, or more precisely, in 2026, an excellent candidate might no longer be an excellent applicant. When any applicant can use AI to perfectly mirror a job description, good grades and standard reference letters lose their sorting power. For faculty recruiters, this means traditional metrics are failing.

In economics terms: AI has effectively broken traditional signalling mechanisms like a well-crafted CV and cover letter, because the marginal cost of sending a highly-tailored application has dropped to near zero.

As such, with recruiters realizing that keyword-optimized AI applications are masking mediocre candidates, they are forced to rely on alternative signalling. This can include more importance for verifiable, institutional data, or devising short challenges that are difficult for an AI to respond to without clever prompting by the user.

The Buyer’s Market: A Challenge for Recruiters

In the competition to recruit talented economists and data-scientists, faculty recruiters in 2026 are confronted by challenges on either side of the recruitment process. On the one hand, many countries are experiencing economic slowdowns, which trickle down to reduced budgets for universities and research institutes. This often translates to fewer hires, and tighter hiring budgets for those positions still available. Indeed, it has been well noted how the number of posts on economics specific sites (JOE, INOMICS, econjobmarket) has fallen over recent years. While some specific areas like financial economics and health economics seem to be stabilising due to higher demand for those specializations, the overall trend of fewer publicly advertised job openings continues. So when there is a position to fill, you want to get it right.

On the other side, recruiters face a challenge in the sheer number of applications. In short, the academic job market has become lopsided, with too many job seekers for too few positions. This might sound like a luxurious problem to have as a recruiter, but couple it with the ability afforded by new AI tools for any (also weaker) candidate to put together a cohesive application, as already detailed earlier, and the reality is that recruiters can be quickly overwhelmed by a mass of applications, and struggle to differentiate between the best candidates and the rest.

Especially when you are up against higher-paying and, in terms of recruitment capacity better equipped, private sector employers, this can be tough.

Apart from emphasising the benefits (also non-monetary) of your open positions, achieving the right mix of quality and quantity of applications is the major challenge facing academic recruiters today. Options can include more targeted candidate searches, or being more selective of the channels used for recruitment. Some recruiters decide not to advertise a job at all apart from on their own recruitment pages…

Possible Solutions

• Stealth Hiring: keeping your job openings on your own website sounds like an easy fix, however it limits the reach. While appealing only to active job seekers on your website might seem like a good way to restrict applications only to motivated candidates, in reality you are ruling out the majority of really good, strong candidates who will never see your job post.
• Direct Candidate Searches: Researching possible candidates and reaching out to them directly, in other words, headhunting, is a classic method of recruitment, especially in the business world. However, the costs are high – either a third-party headhunter’s fee, or the time needed for you and your team to research and reach out to possible candidates, can cost thousands. While this may be justified for senior positions, it is unlikely to be a solution for more junior, or even the majority of regular roles.
• Publicize widely, and use tools to filter applications: Publishing your job on major networks like LinkedIn, or on cross-discipline job boards, typically results in a large number of applications. However, a combination of high visibility and low hurdles to find and apply can also mean that the majority of applications are low quality, or not qualified. A workaround for this is to use recruitment tools such as an applicant tracking system, to pre-filter applications. Increasingly these use AI in an attempt to identify stronger candidates. However, these come with fundamental moral and privacy questions, as well as significant costs. And as recent lawsuits against Workday and Eightfold AI have shown, the “black-box” of AI decisions can risk accusations of bias from candidates who feel they have been unfairly disqualified due to an AI profiling them based on age, gender or ethnicity. While large corporations, with dedicated legal departments, might be able to mitigate this risk, for public universities the risk that a black-box AI-supported application process might discriminate against non-native speakers or specific demographics can quickly become a compliance nightmare.
• Publicize in pre-targeted / expert channels: A middle way is to seek out channels where the audience is already pre-filtered, for example by subject area, so that the candidates are in line with your candidate profile. This includes subject-specific blogs, domain specific recruiting platforms like INOMICS, or selective social media groups. The advantage is that the vast majority of people who will see your job ads will already be suitable. Typically there is also some form of quality control, either through community management, moderators, or curated listings. The challenge of this approach is finding a channel, or a manageable number of channels, that match your target profile. Broadly speaking you should identify the subject area, level of seniority, and geographical location of expected applicants. Advertising your job on a website or channel that matches these criteria, even if the users aren’t explicitly always looking for a job, can bring excellent results.