Are We Hiring the Right Skills for the AI Search Era? Absolutely not.

The job has changed, but your job description hasn’t.

Open LinkedIn and you’ll see hundreds of SEO roles, all still asking for meta descriptions, keywords, links, and audits. Well, maybe not the meta descriptions, but you get the point.

If you read them carefully, though, a simple question evolves: Are these the right skills to carry a business through the next three+ years of search evolution? Or are we hiring for what we know, while the real work shifts under our feet?

For twenty years, the SEO playbook has stayed remarkably consistent. A new site needed audits, metadata, internal links, sitemaps, keyword clusters, etc. Good SEOs executed those tasks, ran dashboards, tracked rankings, and delivered traffic. But search is being rewritten in real time by AI intermediaries that skip your title tag if they can pull a more useful chunk from your page, or skip your page altogether when they find a more trusted answer somewhere else.

So the real question isn’t whether your next SEO hire is qualified for today’s tasks. It’s whether they (and your team) are ready for what the work will look like next.

With that in mind, there are two things this article brings forward:

1. You need to be hiring today, for the work this employee will be doing in 2 to 3 years. Don’t hire today’s skills and wonder why they can’t keep up. Hire today, for tomorrow.

2. A resource guide exists at the end designed to help hiring managers have internal conversations with HR, hiring panels and executives. This can help you explain and align the hiring process to help get you highly qualified candidate leads. It’s not exhaustive, but it’s a start and can help many.

The Evidence: What We’re Hiring For Right Now

Here’s a general snapshot from real job postings live today:

· SEO Analyst: Develop dashboards, track keywords, conduct audits, build competitive reports, manage redirects and XML sitemaps, and write Jira tickets.

· SEO Manager: Optimize on-page elements, research keywords, monitor competitors, lead link-building campaigns, and coordinate content updates.

· SEO Director: Scale global SEO strategy, lead audits, oversee structured data, collaborate with product and engineering, and maintain best practices.

The skills themselves are fine. The problem is that they’re still tied to signals that made sense when a page of blue links was the entire discovery surface.

That’s no longer true and it won’t be true again.

I looked at over 100 (114 in total) current job descriptions for posted jobs. 14% (16) of them mentioned “ai skills” in the broadest sense, 7% (8) of them actually got to the level of listing ai-marketing-related skills (GEO, AI Search, AEO, AIO, GenAI Search, etc.). Keep in mind, those are jobs searched for with common SEO job titles, and we already talked a lot about the new titles we’ll need prior to this…and they’re not adopted yet. (New Jobs Series: Part 1, Part 2, Part 3, Part 4)

What the Work Will Actually Look Like

Generative search systems are already here. If you care about discoverability, ranking well on Google isn’t enough. You need to appear in CoPilot, Gemini, Perplexity, ChatGPT, and any other AI layer that skips the click and answers on your behalf.

This changes what SEO work actually involves.

• Instead of tracking keyword positions alone, your team needs to understand how pages chunk, where they land in vector databases, and how LLMs retrieve them.

• Instead of writing meta descriptions for clicks, they shape content blocks that carry trust signals AI systems will cite directly.

• Instead of monitoring rankings, they run prompt-based tests to see if your brand appears in zero-click results.

• Instead of building traditional links, they manage structured data and machine-validated authority that improves synthesis outcomes.

Some of this language has started creeping into senior-level postings. You’ll see terms like “AI-powered search” or “Answer Engine Optimization” appear occasionally—but it’s still rare.

According to the World Economic Forum’s Future of Jobs Report 2023, “AI and big data” skills rank in the top five core competencies expected to grow in importance by 2027 (source). And in a second WEF publication, The Good Work Framework, they highlight the need for upskilling initiatives that directly align with emerging digital workflows, search among them (source).

LinkedIn’s AI at Work Report (Nov 2023) found that AI-related conversations on their platform jumped 70% in under a year, and that the skills required for most jobs are expected to shift by 65–70% by 2030 (source). Despite that, most SEO job descriptions still treat AI as a buzzword, not a requirement.

According to Business Insider, “AI skills are now expected even when they don’t appear in the job description” (source). Which means teams that don’t explicitly ask for them may be unintentionally screening out the very talent they need.

McKinsey adds weight to this shift, reporting that 70% of the skills workers will use by 2030 are different from those emphasized in most job roles today and that AI is the biggest driver of that change (source).

The Practical Hiring Problem

Understanding that search is evolving is one thing. Hiring like it is? That’s where most teams stall.

Start with a few hard questions.

• Are you planning to train for this?

  • If your new SEO Analyst has never run an embedding relevance check or tested how your pages chunk for retrieval, who’s teaching them? Is there a training plan? A budget? Or do you expect them to figure it out in the margins while doing legacy work?

• Does your job description say what you actually want?

  • If it still lists only “title tags, content, link building, keyword research,” then that’s what your recruiter will source—and what your candidates will optimize for.

One or two clear additions can change the whole pipeline:

• “Familiarity with AI search systems and prompt testing preferred.”

• “Experience with content chunking and vector indexing a plus.”

Does your HR team understand what those mean? Most recruiters don’t live in SEO, let alone generative search. They scan for the words you give them. A five-minute teach-in can help them understand why “retrieval,” “chunking,” and “semantic indexing” matter now.

What about interview panels? If your hire will impact product, engineering, or content, your panelists need to know what future-ready work looks like too. Don’t let them improvise. Provide a simple panel script that includes role-specific prompts and what a good answer looks like.

Panel Guidance: Be the Architect

If your product lead joins the interview, hand them a question:

“How would you test whether a new feature page appears in Gemini or Perplexity?”

If your content lead is on the panel, suggest:

“How would you structure long-form content to surface more reliably in AI-driven answers?”

If your engineer is involved, use:

“What technical elements most impact chunk retrievability and structured trust?”

Even a one-page cheat sheet can turn a casual panel into a real alignment filter.

Debrief, Bias, and Ownership

The interview isn’t the finish line. Debrief your panel properly. Ask for the why behind each yes or no. A rejection based on comfort bias (wanting someone who understands the old version of the work) is a red flag, not a decision.

Hiring isn’t a group vote. The panel provides perspective. You make the call.

Remember: they’ll inherit the outputs of this hire’s work. If they don’t understand what retrieval testing or AI-driven optimization means for their team’s success, they won’t support the hire. Your job is to connect those dots.

You also need to screen for growth mindset. SEO is changing fast. Write it plainly: “Must be curious about AI-driven search and willing to learn new systems as they evolve.” Then test it: “Where do you go for updates?” “What’s something you’ve tested recently?” It filters out checkbox candidates instantly.

One of the most overlooked traits? Project management. AI SEO work is no longer a solo act. It’s cross-functional. Chunk optimization, vector testing, prompt experimentation, structured data updates: these require coordination. That makes project coordination one of the most scalable skills for modern SEOs. Encourage your team to build it.

Green Field, Not Locked Titles

You don’t need to rename your entire team. But you absolutely need to realign what those roles are expected to do.

Whether it’s an Analyst, Manager, or Director, the job title doesn’t matter as much as whether the role is scoped to match the new reality.

If you hire someone based on the 2018 playbook and expect them to learn 2026 workflows on their own, you’re not building a future-ready team, you’re building a performance gap.

In my own work, I’ve explored this transition in the four-part series reimagining SEO job roles for the GenAI era linked above. If you missed it, I’ll suggest it’s worth a read.

What Should You Actually Do?

1. Audit Your Job Descriptions
   Pull up a real job post. Mark every task tied to the old playbook. Then ask: what’s missing? Chunk testing, prompt experiments, semantic indexing, trust signal structuring?

2. Add New Cues
   You don’t need to scare off traditional applicants. One or two forward-looking lines are enough to signal what’s coming. The right people will notice.

3. Upskill the Team You Already Have
   No one picks up retrieval optimization by accident. Run an internal session. Bring in a subject matter expert. Allocate real time for training. Build readiness, not burnout.

Where This Goes

Search is already rewriting itself. Zero-click answers. Agent-driven queries. Vectorized content blocks and AI-validated trust signals. If your brand wants to show up when AI does the discovery, you can’t optimize for that after the fact.

Meanwhile, other parts of society are adapting. Microsoft and OpenAI have partnered with the American Federation of Teachers to help train educators on how to use and understand AI tools in the classroom (source). The logic is simple: train teachers, influence students, shape the workforce.

That shift is already underway. Your future hires may have a baseline understanding of AI content construction, retrieval models, or prompt testing, only to find job descriptions written for a decade-old search model. That’s a bottleneck. They’ll be ready for the work but your company won’t be ready for them.

The education system is evolving. The workforce is coming. The real question is whether our hiring systems will be ready to meet them, or will it quietly filter them out, leaving you wondering where all the good candidates went.

Hiring is one of the last frontiers that hasn’t caught up. And it’s time it did. I think you’ll agree: most of the time, right now, we are absolutely not hiring the right skill sets for the work.

Resource Guide: Future-Proofing Your Next SEO Hire

This isn’t just a mindset shift. It’s a tactical shift. Here’s how to make your next hire reflect where search (and content strategy) is actually headed.

Future-Proof Hiring Checklist

Use this quick checklist to realign your hiring process for the AI search era:

• Audit your current job descriptions for legacy SEO language (e.g., “optimize metadata,” “build backlinks,” “track rankings”).

• Add one or two forward-looking signals like vector indexing, content chunking, retrieval optimization, or AI trust signals, even if it’s just in the “preferred” section.

• Meet with HR upfront to explain why the role is evolving and how it will impact downstream teams.

• If you’re doing panel interviews, prep your panel with targeted interview questions, model answers, and a short primer on how GenAI search works.

• Screen for self-directed learning by asking which sources, platforms, or training paths the candidate is already using to keep up with AI developments.

Good vs. Better: Job Description Language for a Changing Role

These four swaps help you frame your needs for today and tomorrow, without overwhelming HR or confusing your candidate pool.

Legacy Phrase: Optimize metadata and track keyword rankings
Future-Aligned Upgrade: Structure content for chunk-level retrievability in LLMs and test visibility in AI search platforms

Legacy Phrase: Build backlinks and conduct site audits
Future-Aligned Upgrade: Implement trust signals and structured markup that boost AI citation and retrieval

Legacy Phrase: Write and publish blog content on _______ topics
Future-Aligned Upgrade: Develop machine-parsable content blocks aligned to semantic density and AI answer formats

Legacy Phrase: Stay up to date on Google algorithm changes
Future-Aligned Upgrade: Demonstrate working knowledge of AI search behavior, including Gemini, Perplexity, CoPilot and ChatGPT

Hiring for SEO today means hiring for AI search tomorrow. These checklist items and language updates aren’t bells and whistles. They’re signals to the market that you understand where discovery is headed. Whether you’re filling a junior analyst role or a senior strategist seat, your job description is no longer just a posting. It’s your first chance to show you’re building for what’s next.