Roles are changing with AI; job titles aren’t, and it’s costing employers heavily

How AI is impacting jobs: The reality on the ground

There are several misconceptions about the impact of AI in the workplace. Some think AI is only creating new roles, some believe AI will replace most jobs, and others think AI will only impact tech. 

The truth is that, for the most part, AI is reshaping today’s existing roles across various sectors, even if job titles aren’t actually changing. As Robert Hourie, company director at Elwood Robers, explains:

“Across roles like recruiters, account managers, analysts, and customer support, the title stays the same but the ‘unit of work’ changes. People are no longer producing everything from scratch. They’re orchestrating: prompting, selecting inputs, validating outputs, and making judgment calls about when automation is appropriate.”

And other experts echo Hourie’s observations. 

Bob Gourley, chief technology officer at OODA and author of The Cyber Threat, says AI has “subtly but dramatically changed the main responsibilities inside many positions” – a shift that’s easy to see in marketing. 

“A marketing analyst may have the same title but now depends much on artificial intelligence tools for segmentation, campaign testing, or perhaps content development. On paper, the job appears to be the same, but the daily life is entirely different,” Gourley explains. 

Similarly, Shahid Shahmiri, founder of Marketing Lad, tells TestGorilla how the same “SEO managers” now “spend a significant amount of time reviewing the output of machines for various types of issues, including minor hallucinations, slight variations in tone, identifying over-inflated metrics[...]the work has shifted from production to decision quality and restraint.”

Christian Sibus, managing director at Semper Prospera, points to the impact of this “invisible role change” on junior tech roles. “A Junior Dev is no longer just writing boilerplate code; they are now essentially an Editor and Quality Controller of AI-generated code. The job has moved from ‘production’ to ‘curation.’”

Meanwhile, Anastasiya Levantsevich, head of People and Culture at Pynest, believes it’s not just juniors whose jobs are changing. “AI is most significantly changing the work of 'mid-level' engineers[...]who, in most cases, handle the bulk of the tasks. Their role has become closer to that of a 'solution operator.’” 

When job titles stay put, hiring starts to suffer

When job titles stay the same, it creates an illusion that the job itself hasn’t changed. So employers stick to the same old ways of hiring. 

“The clearest issue I notice is that firms frequently employ according on what a position used to be rather than what it's evolving to be,” says Gourley. And he’s onto something. 

Using outdated job descriptions is risky business

For years, job requirements have leaned heavily on degrees and experience in a particular role. “Rigid checklists and ‘years of experience’ still dominate evaluation criteria and that’s becoming less and less relevant,” Gourley points out. 

When job titles don’t change, there’s a good chance job descriptions aren’t changing either. Take a look at Indeed’s Accountant job description (updated in 2025). It talks about accounting experience and a bachelor’s degree, but makes no mention of AI fluency. 

With roles changing as fast as they are, these stagnant job descriptions won’t hold up. Candidates will read them and assume they’re a good fit, and you’ll waste time reviewing and rejecting people who never stood a chance. 

What’s even scarier is that you might actually hire the wrong person, especially if you’re relying on job descriptions to assess and select applicants (as hiring teams often do). 

Keyword matching makes things worse  

The problem compounds when inaccurate job requirements feed directly into hiring tools. Keyword matchers, for instance, pull phrases straight from job descriptions and reward resumes, applications, or even LinkedIn profiles that contain those exact phrases. 

Gourley cites an example: “Companies still post requirements for ‘5 years of experience,’” when what they need is someone proficient in AI tools “that launched 12 months ago.” This method just doesn’t work because your resume screener or ATS is prioritizing stale skill sets. 

“Teams draw in applicants with the wrong strengths by means of job descriptions built on obsolete workflows, or even worse, they lose those who could flourish in the position with contemporary tools,” he warns. 

And even good hires can feel catfished

Sibus has noted “a dangerous gap between what people actually do all day and what's written in their job descriptions.” In fact, a recent Monster survey revealed that 4 in 5 employees felt they were victims of “career catfishing,” where their roles differed from what was advertised.

Hutchins has seen the fallout firsthand: “You also get resentment. People hired to ‘write all day’ feel blindsided when half their job becomes managing AI workflows and quality control. They didn’t sign up for that.”

On the off chance you snag a top candidate despite not updating the job title, description, or hiring process, you could still lose them. According to Gallup, employees who aren’t clear about their jobs are less engaged and more likely to leave. 

The best way to recruit when jobs change (but titles don’t) 

It’s tempting to think that changing the job title is the easy fix to all these problems. But in reality, doing so can create a different set of issues. 

Job titles act as anchors for candidates, helping them make sense of the market and decide where they belong. With everything else changing so quickly, people need something familiar to hold onto, and that’s part of the reason they haven’t changed overnight. 

The good news is, you don’t need to change job titles just yet. Here are two things you can do instead. 

Hire for skills that will stand the test of time

Instead of leading with credentials, years of experience, or technical checklists, shape your job requirements around transferable skills and qualities that can help employees evolve as jobs do. 

According to the World Economic Forum (WEF), soft qualities such as analytical thinking, adaptability, curiosity, and lifelong learning will be pivotal over time. 

Vaibhav Bajpai, group engineering manager at Microsoft's Core AI, also emphasizes the importance of this kind of growth mindset and agility. “In [the] current environment [one has to be] open to learn new things and move fast. People should feel comfortable adapting workflows as tools evolve every few months, not years.”

The WEF also discusses the growing importance of AI skills. The problem is that many employers don’t really know what that means. A recent survey found that among the 74% of employers who used the term “AI” in their job ads, only 2% were specific about the AI skills they were looking for. 

As a result, Hourie believes “teams over-index on tool usage (‘uses AI daily’)” and Hutchins recommends we stop looking for tool proficiency in isolation. “Knowing how to use ChatGPT or Jasper or whatever isn’t the skill,” he says. 

A cheat sheet of AI skills to hire for

To make things easier, we put together a practical list of qualities that accurately capture AI fluency. You can use these as a starting point when writing updated job descriptions. 

• Applied AI use and workflows: Can use AI tools proficiently, with little to no rework, and know what AI can and can’t help with. 

• Learning and digital agility: Can adapt to new tools fast, test workflows, and improve how they use AI. Sibus calls this “Critical thinking and ‘Prompt Resilience’ – the ability to iterate with a model until the result is actually usable.”

• Systems thinking and problem-solving: Can break large, messy problems down into smaller tasks and figure out how AI can assist and impact the downstream chain of work.

• Responsible and ethical AI use: Are informed about the legal, moral, and privacy risks of using AI. Hutchins provides an example of why this matters. “When you’re using AI[...]you’re making daily decisions about transparency, accuracy, and trust. That’s not a box you check in onboarding. It’s a skill you either have or don’t.”

• Human-led collaboration and communication: Treats AI like a teammate, knows when to step in with human judgment, and fully understands the assumptions, outputs, and decisions AI makes. 

Use tools of the future to measure skills of the future

The smartest employers no longer leave their hiring luck to semantics and phrasing. Instead of keyword matching, they’re using more foolproof techniques, all rooted in skills-based hiring. This means ditching credentials, experience, and other vague signals in favor of real-life skills validation. 

Here are some of the methods they’re using. 

Live exercises

Some employers now put candidates in situations that mirror the real use of AI. For instance, Shahmiri conducts live exercises and believes that “Candidates [who] are able to correctly identify factual inaccuracies and misaligned intent or risk [in AI] at least 70% of the time tend to be strong candidates.”

According to Bajpai, Microsoft is doing something similar during the interview process. “Many companies, including Microsoft, are shifting interviews toward open-ended problems...that can only be solved within the time limit if candidates have strong, hands-on experience with AI tools.” 

While these are effective ways to assess candidates' AI skills across sectors, they’re hard to scale for higher volumes of applications. Luckily, other tools solve this problem. 

Multi-measure testing 

Talent assessments are the single most reliable way to measure real-world skills. With platforms like TestGorilla, you can assess everything from AI skills to softer qualities such as adaptability, analytical thinking, a learning mindset, decision-making, and other so-called “skills of the future” in one place. 

Our latest survey found that 91% of employers who use multi-measure testing are making quality hires. It’s a quick, objective way to predict candidate success and can be run at scale. 

AI resume scoring 

At TestGorilla, we’ve always encouraged skills assessments over resume screening. But we get that most employers still feel attached to the resume. Fortunately, there’s now a better way to screen resumes, which, once again, doesn’t involve keyword matching or flawed job descriptions – AI resume scoring. 

This AI hiring tool provides scores to resumes against detailed job criteria that hiring teams set for themselves. Hourie, for instance, suggests using more outcome-based criteria like “reduces cycle time without increasing error rate.” It’s a great way to screen candidates for the skills you actually need (even if role titles or descriptions are stuck in the past).

The future of hiring is skills-focused

Jobs have changed considerably since the rise of AI. While job titles are still playing catch-up, your hiring practices shouldn’t stay frozen in time. Otherwise, you’ll hire employees skilled for yesterday’s work, which Sibus says “leads to massive quality drops and, frankly, a lot of frustrated talent.” 

The best way forward? Update your job requirements with transferable, AI-specific, and other relevant qualities. Then use advanced tools like skills assessments and AI resume scoring to measure them. These are the most solid ways to end up with employees who are AI-fluent, agile, and future-proof.

Explore TestGorilla’s AI hiring assessments to get started today.

Contributors

• Anastasiya Levantsevich, Pynest, Head of People and Culture

• Bob Gourley, OODA, Chief Technology Officer

• Bob Hutchins, Human Voice Media, CEO

• Christian Sibus, Semper Prospera, Managing Director

• Robert Hourie, Elwood Robers, Company Director

• Shahid Shahmiri, Marketing Lad, Founder

• Vaibhav Bajpai, Core AI at Microsoft, Group Engineering Manager (Sr. Director)