JOB search now
starts with AI
Fix What’s Broken. Build What Works.
AI, LLMs & Hiring Systems
Fix What’s Broken.
Build What Works.
AI is already shaping
candidate decisions.
Whether you planned for it or not.
Large Language Models (LLMs), AI-powered search, and automated decision systems are already influencing how candidates discover roles, interpret employer brands, and decide where to apply.
Most organizations didn’t design for this shift. They inherited it.
GBS helps organizations identify what’s breaking inside AI-influenced hiring systems—and design employer brand and career site experiences that actually work for candidates, performance, and trust.
Candidate behavior is shifting—materially
Candidates are moving away from traditional, linear search behavior.
Instead of relying solely on Google, job boards, and manual comparison, many candidates are now:
Asking LLMs direct questions about employers and roles
Relying on AI-generated summaries to evaluate fit and credibility
Making early decisions before visiting a career site
In these moments, Google is no longer the primary decision engine: LLMs are.
That shift changes how employer brands are understood—often without employers realizing it.
The problem isn’t AI.
It’s unmanaged impact.
From our research and client work, most organizations face an AI readiness gap—not because they lack tools, but because the systems surrounding those tools were never designed to support real human behavior.
Breakdowns typically occur between:
Where things break
We consistently see friction emerge in three places:
Hidden cognitive load
Candidates are already using AI to search, interpret, and apply—but unclear systems force them to guess what “the machine” values. That increases anxiety, effort, and drop-off.
Opaque automation
When candidates don’t understand where AI is used—or where humans are involved—perceived fairness declines, even when decisions are technically sound.
Misalignment between candidate AI and employer AI
Organizations often encourage candidates to “use AI” while obscuring how employer-side automation operates. That mismatch creates confusion, not confidence.
The result isn’t just better efficiency. It’s improved retention- and revenue.
Why this matters for career sites, search, and LLMs
Career sites are no longer just destinations.
They are inputs.
They are read, summarized, and interpreted by:
➤
Search engines
➤
AI-powered job discovery tools
➤
Large Language Models responding to candidate questions
If your career site isn’t designed with AEO / GEO and LLM interpretation in mind:
➤
Your employer brand is being reinterpreted without your control
➤
Critical context may be flattened or lost
➤
Candidates may receive incomplete or misleading signals
GBS designs career sites and content systems that are LLM-aware, not LLM-chasing—grounded in clarity, structure, and intent.
Building Employer Brand Authority
in LLM-Mediated Discovery
How career sites and employer brands move from misinterpretation to trust.
Employer brand authority in LLM environments isn't achieved through one-time optimization. It's built through intentional design and ongoing stewardship.
How GBS approaches AI and LLMs
We don’t start with tools.
We start by fixing what’s broken in the system. Our approach focuses on:
- Making AI use observable rather than invisible
- Reducing unnecessary cognitive load for candidates
- Designing transparency as an employer brand asset
- Aligning candidate guidance with employer-side automation
- Measuring trust and fairness—not assuming them
This isn’t about just promising “ethical AI.” It’s about
building systems that work under real conditions.
How organizations engage GBS
on AI and LLM readiness
LLM visibility and interpretation is not a one-time event.
It’s an evolving system that needs competent partnership.
GBS supports this work for our clients in two primary ways—often together.
Initial build: fixing what’s broken
This phase corrects foundational issues already affecting how LLMs interpret employer brand and career site content.
This work typically includes:
➤
Mapping where and how LLMs currently interpret your employer brand
➤
Identifying misrepresentation, gaps, or flattened messaging
➤
Structuring career site content for AEO / GEO and LLM interpretation
➤
Clarifying employer brand signals LLMs rely on for summarization
➤
Addressing transparency and trust breakdowns in AI-influenced hiring steps
The goal is system stability—so candidates receive an accurate, trustworthy picture before decisions are made.
Ongoing optimization: building what works over time
LLMs evolve. Search behavior shifts. Candidate questions change.
Organizations that want to build and sustain employer brand authority inside LLM-mediated discovery engage GBS on an ongoing basis.
This work may include:
01
Monitoring how LLMs summarize and interpret employer brand content
02
Iteratively improving clarity, structure, and signal strength
03
Updating content based on emerging candidate questions
04
Strengthening brand authority through consistent, interpretable messaging
05
Ensuring changes to automation, policy, or experience don’t degrade trust
This is not content churn.
It’s intentional stewardship of employer brand authority.
Ongoing optimization: building what works over time
LLMs evolve. Search behavior shifts. Candidate questions change.
Organizations that want to build and sustain employer brand authority inside LLM-mediated discovery engage GBS on an ongoing basis.
This work may include:
01
Monitoring how LLMs summarize and interpret employer brand content
02
Iteratively improving clarity, structure, and signal strength
03
Updating content based on emerging candidate questions
04
Strengthening brand authority through consistent, interpretable messaging
05
Ensuring changes to automation, policy, or experience don’t degrade trust
This is not content churn.
It’s intentional stewardship of employer brand authority.
Built on research, not opinion
This work is grounded in:
Ongoing quantitative research into AI, fairness, confidence, and job search behavior
Behavioral and I/O psychology
Enterprise employer brand and hiring system design
The operational realities teams actually face
GBS is not focused on selling you shiny AI tools.
We design systems that hold up for our clients when AI is introduced.
Fix the step. Not the candidate.
AI doesn’t fail because candidates don’t understand it.
It fails when systems aren’t designed to support human behavior.
GBS helps organizations fix the steps that matter—so AI becomes an asset, not a liability.
