With AI skills in high demand, the tendency to exaggerate AI knowledge is also on the rise, and it often begins with the job application process. Increasingly, applicants are overstating their AI expertise because they know it can be a competitive advantage, and many are also relying on AI tools to craft cover letters and CVs.
In fact, half of today’s job seekers use AI to support their applications, while 77% say they have used it to exaggerate or lie about their skills on a CV. Our recent AI Skills Report found this AI exaggeration to be true in the workplace too: over three quarters (77%) of UK executives and technology workers admit they have pretended to know more about AI than they actually do.
This trend isn’t new in tech. We have long seen that CV inflation among technologists rises in line with demand for certain skills. Given the current demand and fever around AI, we’re likely at a high point.
That’s why interviews for tech jobs, like software development, usually involve some form of skill assessment as part of the process. Given the rising importance of AI for all roles, skills assessments, along with personality and general competency assessments, should be standard practice for most roles. This is how employers can determine quality candidates from candidates who oversell themselves in the age of AI.
As many candidates feel pressure to appear AI-savvy, it’s crucial that leaders have a strategy to look for authenticity in the application process, understand skill potential, and find applicants with a growth mindset.
Demand-driven CV inflation
The majority of tech companies now look for some level of AI competency when hiring. With discussions in the news about how AI could take over jobs in years to come, or substantially reshape industries, job seekers are understandably anxious. Factor in reports that AI skills help to increase salaries, and it’s clear to see why applicants might exaggerate their skills.
Our research shows high anxiety on this front, with 93% of executives and tech workers still feeling there is a risk AI will replace them, despite 44% saying they have actually added more roles due to the growth of the technology.
It’s well known that any new technology—whether at the time of the dot com boom or the dawn of cloud computing—creates high demand and fuels inflated claims. AI is no different. As the demand for AI skills increases, the pressure to appear competent intensifies.
It’s no surprise that candidates would use AI to create application materials, and in a sense this should be viewed positively by employers. If you want your employees to increase their productivity with AI tools, applicants who already use AI likely fit the profile of eager adopters.
Searching for authenticity
As AI tools become central to operations in the modern workplace, hiring managers shouldn’t show prejudice towards applicants who use AI for their applications. Instead, the hiring process should be viewed as an opportunity to evaluate not just what candidates submit, but how they use AI to do it.
Generic, jargon-laden statements are a telltale sign of overreliance on large language models. LLM-produced answers to generic questions like “Why are you interested in this position?” are equally inauthentic and may be carbon copies of other applicants’ answers.
If businesses want AI skills, the key is to find applicants who utilise AI effectively to become more efficient, not as a crutch. In this light, the application process can be the first test of whether a candidate will use AI as an assistant in the process of creating a high-quality work product, or rely on it too heavily without knowing how it works.
Supplementing this qualitative judgement with psychometric testing can provide deeper insight into a candidate’s cognitive abilities and gauge overall cultural fit. Meanwhile, these assessments also help recruiters determine the honesty of the applicant. Alignment of performance and stated experience reinforces trust and helps shape the next step of the application process.
In a landscape increasingly being shaped by AI, these tactics are key ways for hiring managers to adapt.
Hiring for potential versus validating existing skills
While skills assessments are typically a key factor in most application processes, it’s equally important to assess applicants with a growth mindset, especially given the widespread skills shortages that persist in the tech industry. For some young people, entry-level roles can feel out of reach, as demand for experience outweighs traditional academic qualifications.
To build a sustainable talent pipeline, businesses need to assess what they value in a candidate—not just what they’ve done, but their capacity for learning on the job.
In some ways, the use of AI in job applications speaks to this capability. Younger workers have grown up around technology and their ability to learn how to use AI fast suggests they are well-positioned to work with technology and develop their skills quickly. While recruiters may find its use frustrating in applications, it should not be dismissed as part of their overall aptitude for the job. Psychometric testing can add a quantitative mechanism for sussing out a growth mindset.
Technology is changing so quickly that the willingness to continually upskill is more important than demonstrating 100% proficiency with any given set of skills.
The continuous learning arc
Hiring candidates with a growth mindset is only half off the equation. To truly become high-impact team mates, there should always be room for employees to access training and upskilling opportunities once they are in the workplace because with the pace that technological advances, we will never be ‘done’ with learning.
But having the right foundational skill set for a specific role is key and it can then be further developed and enhanced over time. Ultimately, the most-future proof teams will be built not only on current skills, but on the ability to evolve.
As the next generation of tech-savvy talent enters the job market, the use, or overuse, of AI in job applications is unlikely to disappear any time soon. In the short term, skills assessments and aptitude tests will help recruiters identify the best candidates for long-term growth, and whether they have the correct technical skills to succeed. These tools should be used as a supplement to CVs and cover letters to get a comprehensive view of the individual’s competency.
Longer term, HR departments have a real opportunity to reshape how we view AI once workers are in employment. Continuously educating employees on how to use AI in a safe and transparent way is crucial to driving innovation and working towards shared organisational goals.
Chris McClellen is the Chief Product and Technology Officer (CPTO) of Pluralsight, Inc., the leading technology workforce development company that helps companies and people around the world transform with technology. In this role, Chris is responsible for driving innovation across the Pluralsight learning platform, better enabling consumers and businesses to transform with technology skills.
