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Over the last year, hiring teams have started seeing a wave of new job titles pop up across tech, sales, and ...
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Hiring in 2026 has a new problem.
It’s not a lack of applicants. It is too many of them. And differentiating real from fake is getting a lot harder.
Recruiting teams are getting flooded with resumes that look perfect on paper, match job descriptions with eerie precision, and check every box in the ATS.
Then they fall apart the moment the process gets real. That’s if you stop them before they get hired…
Welcome to the AI-on-AI hiring arms race.
In Part 1 of this series, we explored how Agentic HR is reshaping talent acquisition and why AI isn’t just a tool anymore — it’s becoming an active participant in how hiring decisions get made. If you haven’t read it yet, start there for context:
Agentic HR Is Here: How It Impacts Talent Acquisition
The Pipeline Is Getting Noisier, Not Better
As talent acquisition teams adopt AI sourcing and screening tools, candidates are responding with their own.
Auto-apply bots. AI-generated resumes. Cover letters written in seconds. Interview prep scripts. Portfolio content that looks impressive but doesn’t hold up under scrutiny.
The result is what a lot of recruiters are feeling right now.
More volume. Less trust.
And the worst part is that much of it looks “good” at first glance.
“Workslop” Is the New Hiring Challenge
There’s a term floating around that actually fits the moment.
Workslop.
It’s the flood of fast, polished, low-quality output created with AI. Not always malicious. Sometimes it’s just survival.
But from a hiring perspective, it creates the same outcome.
You end up spending more time screening, more time validating, and more time chasing false positives.
So even though AI is supposed to make hiring faster, many teams are experiencing the opposite.
Keyword Matching Is Dead (And It’s Taking Your Hiring Process With It)
This is where things get uncomfortable.
A lot of TA teams are still running their funnel on keyword logic.
The problem is simple.
AI candidates can generate keyword-perfect resumes in minutes. They can tailor language to mirror your job description line by line. They can optimize for ATS filters better than most humans ever could.
So keyword matching doesn’t identify talent anymore.
It identifies who used the best prompt.
The Shift: Semantic Search and Context-Based Matching
The strongest recruiting platforms in 2026 are moving away from keyword filters and toward semantic matching.
Instead of looking for exact terms, these systems interpret meaning.
They understand that:
- “Client Success Manager” and “Account Manager” often share the same core skills
- “Ops lead” and “Program Manager” may be doing similar work
- Job titles aren’t consistent across industries
This helps on two fronts.
It reduces false negatives, meaning you stop filtering out good candidates. And it reduces false positives, meaning the “perfect” resume isn’t automatically trusted.
Verification Is Back, and It’s Going to Get More High-Touch
Here’s the big takeaway.
In 2026, hiring is becoming a trust problem.
And trust requires verification.
That’s why we’re seeing a comeback of high-touch validation methods like:
- structured interviews
- work-sample assessments
- skills-based simulations
- in-person final rounds for critical roles
- stronger identity and integrity checks
Not because companies want to be rigid, but because the cost of hiring the wrong person is rising.
When the resume is no longer reliable, you need new ways to validate capability.
The Real Risk: Overcorrecting and Breaking the Candidate Experience
Some companies are reacting by turning hiring into a security checkpoint.
Over-correcting is common, particularly when you get burned. But that doesn’t mean it is the right thing to do.
If you add friction everywhere, you lose good candidates. You also lose trust in a different way.
The teams doing this well are tightening verification at the right moments. They keep the process fast, clear, and respectful.
They validate skills without treating candidates like criminals.
That balance is the new competitive advantage.
What Talent Teams Should Be Doing Now
In 2026, the teams winning this arms race are doing a few things consistently:
- Reducing dependence on resumes
Resumes still matter, but they cannot be the main proof of ability. - Building verification into the process
Work samples, structured interviews, and skills checks are no longer optional for many roles. - Improving transparency
When candidates know what’s being evaluated and why, trust goes up, and gaming goes down. - Upgrading the funnel logic
Semantic matching and real skills signals are replacing keyword filtering.
What’s Next
The arms race is real. It’s also pushing recruiting into the next major shift.
The future is skills-first hiring, whether companies are ready for it or not. And Gen Z is accelerating that change faster than most employers expected.
Next in this series: Skills-First Hiring + Gen Z’s Mandate
Most companies are going to handle this by adding more filters, more steps, and more complexity. That usually creates slower hiring and worse candidate experience. If you want to modernize your funnel without losing trust or hiring quality, we can help. Reach out and we’ll share what we’re seeing across the market.
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Over the last year, hiring teams have started seeing a wave of new job titles pop up across tech, sales, and operations.
Some are legitimate new roles.
Others are existing jobs with a slightly different name.
And many of them have one thing in common: AI is suddenly part of the job description.
From Go-to-Market Engineers to AI Specialists, companies are experimenting with new roles as they figure out how automation and AI fit into their teams.
But most of these positions aren’t entirely new. They’re evolutions of existing roles.
The Rise of Go-to-Market Engineers
One role that is gaining traction is the Go-to-Market Engineer.
Depending on who you ask, it is either:
- A new role focused on automation and AI-driven growth
- A modern version of Revenue Operations (RevOps)
In practice, it is a bit of both.
As Matt Tokarz recently pointed out after closing a search for an Outbound & Go-to-Market Specialist, the role looked very different from traditional RevOps. The focus was not reporting or CRM hygiene. It was building prompts, leveraging tools like Clay and Smartlead, and enabling SDRs and AEs with backend insights to accelerate pipeline growth.
Instead of traditional RevOps work like reporting and CRM management, the focus was on:
- Building AI prompts
- Creating campaign messaging
- Automating outreach workflows
- Using tools like Clay, Smartlead, and Trigify
The goal was not simply managing sales data. It was accelerating pipeline generation through automation.
AI Isn’t Creating New Functions. It’s Changing Existing Ones
One trend is becoming clear. Companies are not replacing entire departments with AI.
Instead, they are changing how existing roles operate.
Sales teams still need pipeline.
Marketing teams still need content.
Engineering teams still need to build software.
The difference is that employers now expect candidates to use AI tools as part of their workflow.
As Zac Colip noted during the discussion, we are currently in a transitional phase where companies are labeling roles with “AI” as they experiment with how the technology fits into teams.
But that may not last forever.
Why Many “AI Job Titles” May Disappear
Right now, AI still feels new enough that companies highlight it in job titles.
But eventually, AI will likely become a baseline expectation, not a specialty.
Think about it like cloud technology or data analytics.
At first, companies hired “cloud specialists.” Now most engineers are expected to understand cloud infrastructure.
The same shift will likely happen with AI.
Instead of hiring “AI-enabled marketers” or “AI engineers,” companies will simply expect employees to know how to work with AI tools.
The Talent Pool Is Still Small
One challenge with these emerging roles is simple: there aren’t many candidates with real experience yet.
Many of these positions didn’t exist two years ago.
In one recent search, we started looking for a candidate locally in Chicago. Eventually we expanded nationwide because the pool of people with relevant experience was extremely limited.
This is a common issue with emerging roles:
- Companies want experienced candidates
- But the roles themselves are still new
That gap will likely persist for the next few years.
Hybrid Roles Are Becoming More Common
Another noticeable shift is that roles are becoming more hybrid.
Instead of hiring for narrow responsibilities, companies are combining multiple functions into one position.
As Matt Mulcahy highlighted, one example is the rise of Forward Deployed Engineers, a model popularized by Palantir.
These engineers:
- Work directly with clients
- Gather product requirements
- Write user stories
- Build the software themselves
What used to involve several roles, including product managers, engineers, and solution architects, can now sometimes be handled by one person. AI development tools are part of what makes this possible.
AI Adoption Is Happening at Different Speeds
Not every industry is moving at the same pace.
As Ashley DuBois pointed out, some sectors, such as transportation, are applying AI to specific workflows like load booking and operational automation.
At the same time, some companies are adding “AI” to job titles even when the core responsibilities remain largely traditional.
In many cases, it is still essentially an IT manager role with AI familiarity layered in.
This reflects a broader transition period where companies want to signal modernization and candidates want to signal relevance.
Automation Is Changing Operations Roles
In logistics, AI is increasingly handling scheduling, tracking, and coordination tasks.
According to Brittany Lasky, operational roles such as logistics coordinators may experience the greatest impact from automation.
However, freight brokers who manage negotiation and strategic RFPs remain in demand.
AI can optimize processes. It does not replace relationship management or strategic negotiation.
Across industries, a pattern is emerging.
Execution becomes automated. Strategy becomes more valuable.
Finance Roles Are Becoming More Analytical
Automation is also reshaping finance and accounting roles.
As Adam Slater noted, accounts receivable jobs that once focused on high-volume manual processing are evolving into more analytical positions centered on reporting and insights.
The work is not disappearing. The expectations are increasing.
Organizations are now hiring for:
- stronger technical skills
- analytical thinking
- systems understanding
Even roles traditionally considered administrative now require deeper technical capability.
Analyst Roles Are Expanding
AI is not eliminating analyst roles. It is expanding them.
Financial analysts are also expected to understand tooling, sourcing, and data transformation.
In many cases, two or three roles are being combined into one.
This raises a long-term question.
If entry-level roles become more complex or disappear entirely, how will organizations develop senior talent in the future?
Sales Development Is Becoming More Human
The traditional model of high-volume cold calling is changing.
According to Jack Smith and Emily Canna, teams are shifting toward:
- personalized LinkedIn videos
- voice memos
- highly tailored messaging
At the same time, companies are moving away from activity-based KPIs and focusing more on outcomes such as demos set and SQLs generated.
In a market saturated with automated outreach, authentic communication has become a competitive advantage.
Several clients have said it directly. They want a human in the seat.
Go-to-Market Teams Are Rebuilding the Fundamentals
Every six to twelve months, hiring trends in go-to-market teams shift.
As Jennifer Salerno noted, companies move through cycles.
One quarter it is BDRs.
Then RevOps.
Now it is go-to-market engineers.
Many companies experimented heavily with AI to accelerate pipeline generation.
What those experiments exposed were structural gaps, particularly in outbound strategy.
AI can support execution. It does not replace a well-built top-of-funnel engine.
Inbound momentum can hide weaknesses. Outbound forces clarity.
The companies gaining traction right now are not chasing trends. They are rebuilding the fundamentals of their go-to-market strategy.
What This Means for Hiring
For employers, the takeaway is straightforward. Job descriptions and expectations need to evolve alongside technology.
Across functions, we are seeing the same shift play out. AI is not eliminating entire roles. It is changing how those roles operate and increasing the baseline skill set required to perform them well.
Hiring managers should start thinking less about traditional titles and more about capabilities. That often means prioritizing candidates who can:
- Learn and adapt to new tools quickly
- Think in terms of systems, automation, and workflows
- Combine technical and business skills within a single role
In many cases, the perfect candidate with the exact title simply does not exist yet. The strongest hires are often people who have developed adjacent skills and shown the ability to adapt as the tools evolve.
The Bigger Trend
The broader trend is that AI is accelerating a shift that was already underway.
Roles are becoming more hybrid. Expectations are increasing across nearly every function. And repetitive tasks are being automated, leaving more strategic work behind.
Sales teams still need pipeline.
Operations teams still need coordination.
Finance teams still need reporting and analysis.
Engineering teams still need to build software.
What is changing is how the work gets done and what skills are required to do it well.
Right now we are in a transitional phase where companies are still labeling roles with “AI” as they experiment with new workflows and technologies.
Over time, that label may disappear.
AI will simply become part of how work gets done.
And the roles themselves, while evolving, will look more familiar than the titles might suggest.
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