The new AI impact on jobs: how it’s changing roles and titles.

As a recruiter, I’ve seen firsthand how AI has steadily extended to nearly every corner of the workplace. It’s not just automating repetitive tasks; it’s driving a noticeable rise in generative AI jobs, sparking creativity, streamlining workflows, and delivering data-driven insights across departments. This evolution means job titles, responsibilities, and candidate expectations are shifting, leaving many of us navigating new territory when thinking about AI and job displacement. I’m also observing the emergence of new leadership roles focused on generative AI, alongside a general increase in machine learning and AI positions.

In conversations with clients and other suppliers, it’s clear that more organizations are embracing generative AI not just for efficiency, but as a growing part of their culture. For example, at a recent Kimberly-Clark Supplier Summit, leaders shared that everyone in the company—from the C-suite to factory workers and even cleaning staff—is being trained and expected to use AI in their roles. They’ve made a significant commitment, rolling out monthly training sessions, weekly AI chats, and open office hours. AI-forward thinking, including experience with generative AI tools, is now a key trait they look for in new hires.

This shift, while promising, also brings real questions about AI and job displacement. We’re seeing how traditional roles are transforming, new ones are emerging, and the very definition of “qualified” is evolving. So, what does this mean for us in recruitment? In this article, I’ll break down how to effectively adapt to this AI-driven job market, covering everything from navigating the changing landscape of entry-level roles to refining job descriptions for new skills.

The decline of entry-level roles

One clear trend I can’t ignore: many entry-level roles are seeing a decline as AI takes over tasks previously handled by humans. This is a noticeable example of AI job displacement. I no longer recruit for the large teams of junior Copywriters, Social Media Coordinators, or Graphic Designers I did just a few years ago. Companies are leveraging automation to create dynamic marketing campaigns, generate social posts, design visuals, and even draft thought leadership content. One retail client in Canada, for instance, replaced their entire team of Translators with AI, now relying on just a few people to review and ‘humanize’ the outputs.

This shift is also apparent as creative tasks, like designing videos or writing articles, are handled more frequently by AI. Junior-level professionals are finding it harder to locate those traditional entry points, while roles like “Prompt Engineer” or “AI Content Editor” are emerging as in-demand generative AI jobs.

But here’s where hiring managers like us can make a real difference and thoughtfully consider how AI impacts jobs:

• Create upskilling opportunities: Advocate for internal training programs that help junior hires move into hybrid roles combining human judgment and AI fluency.
• Expand internships: Work with employers to offer “AI-centric” internships, giving early career professionals a chance to collaborate with this technology—and with experienced teams—before stepping into full-time jobs.
• Get creative with titles: Sometimes a simple title like “Client Solutions Trainee with AI Expertise” draws in energetic candidates eager to carve out a niche in the world of generative AI jobs.

Eliminating entry-level roles doesn’t have to mean closing doors; it can mean reimagining how those first career steps work in an era of AI and job displacement.

Skills-based hiring and the demand for AI skills

In this environment, what you can do often matters more than what’s listed on your resume or degree. Employers are looking for candidates who not only bring valuable skills but also demonstrate adaptability—especially when it comes to using AI in their roles and seeking generative AI jobs. This focus is a direct response to the shifting landscape, particularly with the changes in entry-level hiring.

Candidates who embrace AI are clearly standing out. As Nvidia CEO Jensen Huang put it, “You’re not going to lose your job to an AI, but you’re going to lose your job to someone who uses AI.” This statement captures the current spirit of hiring: those who leverage generative AI aren’t just keeping up—they’re setting the pace.

For hiring managers and recruiters, this means:

• Seeking out talent who actively use AI to learn, solve problems, and boost productivity. Integrating AI tools into workflows is becoming increasingly essential.
• Prioritizing skills-focused hiring to open doors for candidates from diverse backgrounds who can show their capabilities, especially those willing to grow alongside the rise of generative AI jobs.
• Focusing assessments on demonstrable abilities (e.g., coding challenges, prompt engineering exercises, case studies analyzing AI output), practical projects, and a candidate’s proven capacity to learn and apply new technologies, rather than solely on traditional credentials.

If you’re a job seeker, leaning into AI and building those skills will help you stand out. And if you’re hiring, prioritizing real-world skills and a willingness to embrace new technologies ensures your team stays agile and competitive in a fast-changing world shaped by the impact of AI.

Adding AI skills to job descriptions

Given the critical shift toward skills-based hiring and the need to find talent adept at navigating AI’s impact, our job descriptions must evolve. When I write a job description involving AI, here’s the framework I lean on to get the best results. These practices are especially crucial now that skills are taking precedence over traditional experience.

1. Be Specific About AI-Related Skills

Did you know that 81% of hiring managers are prioritizing AI proficiency? I always make sure to list exactly which AI skills or tools are relevant using plain language as much as possible. For example:

• For analysts: “Familiarity with AI-powered tools for data analysis and pattern recognition.”
• For customer service: “Experience with AI chatbots and natural language processing tools.”
• For content creators: “Ability to optimize prompts for generative AI tools, such as ChatGPT and Midjourney.”

Clarity helps attract candidates who actually have (or want to develop) the skills that matter most.

2. Clarify Responsibilities Around AI

It’s not just about knowing the tech—it’s about what people will actually do with it. AI-related responsibilities might involve supervising automated workflows, interpreting AI outputs, or implementing new systems. When writing job posts, I use phrasing like, “leverages AI tools to streamline processes while maintaining quality standards.” The goal is to show candidates they’ll need to be both hands-on with technology and proactive in adapting to new workflows.

And here’s my personal tip: always include adaptability as a requirement. This technology changes quickly! We need people excited to learn tomorrow’s tools, not just comfortable with today’s. This focus on a growth mindset is paramount, echoing the approach of companies like Kimberly-Clark, which prioritize continuous learning across all departments.

3. Emphasize Ethics and Collaboration

AI hasn’t just changed how we work—it’s changed how we talk about honesty, teamwork, and the very real issue of job displacement. With 74% of hiring managers spotting AI-generated resumes and submissions, I always stress ethical practices. This trend is especially pertinent as automation becomes deeply intertwined with jobs. It’s a fast-changing landscape: one recent report even found that by 2028, one in four candidates could be fake—using everything from AI-generated portfolios to deepfake interviews. In this shifting environment, spotting who’s truly qualified can feel like searching for a needle in a digital haystack, raising valid concerns about AI and job loss.

That’s why it’s critical to clearly specify in your job postings and communications whether candidates are permitted to use AI tools during the application process. Most companies, however, aren’t yet publishing their AI guidelines. This lack of transparency can make it easier for candidates to take advantage of the gray area, contributing to potential AI and job displacement risks. Setting expectations up front not only promotes fairness but also helps foster a culture of trust and responsibility.

Practical language I use includes:

• “Demonstrates ethical practices in using AI tools, ensuring compliance with privacy and data security standards.”
• “Collaborates with cross-functional teams to integrate AI solutions responsibly.”
• “Adheres to company guidelines regarding acceptable AI use throughout the hiring process.”

This signals to candidates (and teams) that we’re taking AI—and its potential challenges with automation—seriously, while also encouraging open dialogue about responsible technology use.

Where I see all this heading

These changes—especially in the world of generative AI jobs and job automation—can seem significant, but I truly believe this is an exciting time for both hiring managers and candidates. For me, AI isn’t a “nice-to-have” anymore—it’s table stakes. We have a responsibility to balance the technical with the human, making sure our job roles stay relevant while our teams learn and grow.

By being thoughtful with our job descriptions, emphasizing skill development, and embracing this next phase of recruitment, we can all thrive—even as the landscape continues to shift under the influence of the impact of AI.