How Catalyzr Is Ending the AI Arms Race in Hiring

Ryan Fitzgerald
Nov 3
4 min read

Artificial intelligence has supercharged the hiring process—and in many ways, broken it. Recruiters are drowning in applications that all look perfect, and job seekers are fighting algorithms with algorithms to stand out.

In this escalating “AI arms race,” Catalyzr is changing the rules.

Catalyzr blends cognitive science and AI to measure what truly matters: human potential. Its platform replaces résumé keyword wars with something far more predictive—a person’s Career Quotient (CQ), a data-driven measure of cognitive fit and potential to succeed in a specific role.

The Problem: When AI Meets HR, Everyone Loses

AI was supposed to make hiring smarter. Instead, it created chaos.

Applications have exploded. On LinkedIn alone, submissions jumped more than 45% year-over-year—roughly 11,000 every minute. With generative AI tools like ChatGPT, candidates can mass-apply to hundreds of jobs at once.
Recruiters are overwhelmed. Burnout rates among HR professionals are rising as inboxes flood with AI-optimized résumés.
Authenticity has vanished. Candidates use résumé-scanning tools like Jobscan or Kickresume to mirror job descriptions word-for-word. The result? A “sea of sameness” where nearly every résumé looks flawless.

To cope, employers have turned to their own algorithms—AI screening tools, chatbots, and game-based assessments. But this arms race has led to unintended consequences.

“We’re seeing a battle of AIs where nobody wins,” said a Catalyzr founder, Jeremy Bargiel. “Companies rely on keyword matches for skills, and candidates game the system. The best talent disappears in the noise.”

That noise is expensive. Each mis-hire can cost three to five times a role’s salary, and across large enterprises, those mismatches add up to billions. Worse, AI screening systems often amplify existing biases—Amazon famously scrapped its AI recruiter after it penalized women for technical roles.

The Shift: Measuring Potential, Not Keywords

Catalyzr’s insight is deceptively simple: stop trying to guess who looks qualified, and start measuring who is qualified.

The company’s platform integrates AI with cognitive assessments that evaluate critical thinking, reasoning, problem-solving, and adaptability—capabilities decades of research show are the strongest predictors of job success.

“Cognitive ability is the single most reliable predictor of job performance,” said Catalyzr’s CEO, Trevor Higgs. “We combine that science with AI modeling to measure how well someone fits your top performers—not just your job descriptions.”

At the heart of the system is the Career Quotient (CQ)—a single metric that quantifies a person’s potential to thrive in a specific role.

Step 1: Model success. Catalyzr uses AI to analyze the traits, decision patterns, and work styles of an organization’s best performers.
Step 2: Quantify potential. Cognitive assessments then measure how closely each candidate—or employee—aligns with that success profile.
Step 3: Apply the CQ. Everyone receives a role-specific CQ score, giving recruiters, managers, and employees a shared language for potential.

The approach is both scientific and scalable. It captures what makes someone successful here, not just experienced elsewhere.

The Impact: De-Risking the $141 Billion Skills Gamble

The timing couldn’t be better. Fortune 1000 companies are projected to spend $141 billion annually on reskilling and upskilling by 2035—an enormous bet on workforce transformation. Yet most firms still can’t predict who will succeed in new roles or training programs.

Catalyzr solves that problem by helping companies de-risk those investments before a single training dollar is spent.

Precision workforce transformation

With CQ data, organizations can identify employees who are cognitively suited to new roles—say, shifting from customer service to data analysis—before investing in training.

Smarter L&D spending

Instead of spreading learning budgets thin, Catalyzr helps direct funds toward employees with the highest potential to succeed, ensuring measurable ROI on skills programs.

Proven results

At Trucking Edge, a pilot program using Catalyzr’s CQ model cut turnover by 47% and achieved zero voluntary departures among high-CQ employees in their first 90 days of employment.

The Human Advantage: Ending the AI “Black Box”

For job seekers, Catalyzr’s model offers something rare in today’s algorithmic hiring landscape—fairness and transparency.

Instead of being filtered out by opaque “black box” systems, candidates are evaluated on measurable abilities that can’t be faked by AI résumé tools.

Fairer evaluation: Cognitive data levels the playing field for candidates who may lack elite credentials but possess exceptional aptitude.
Reduced bias: Because assessments measure objective performance, they mitigate bias introduced by historical hiring data.
Restored trust: Candidates see how they scored and understand why—a stark contrast to silent rejections from automated screening systems.

“The CQ turns hiring from a guessing game into a shared data conversation,” said Trucking Edge’s CEO Craig Ferguson. “It helps both sides see potential clearly.”

Beyond Hiring: A Talent Intelligence Revolution

Catalyzr isn’t just transforming how companies hire—it’s reshaping how they develop and retain talent.

The same CQ data that guides hiring also powers internal mobility, career development, and succession planning.

Accelerate mobility: Employees can view their CQ for every role in the company, helping them map career paths based on objective fit.
Personalized reskilling: AI-driven recommendations guide employees toward targeted learning programs aligned with their potential.
Strategic succession: HR teams replace subjective 9-box performance matrices with quantifiable, predictive data on future leaders.

This integrated approach supports a shift from skills-first to potential-first workforce strategy—one where companies build adaptable, future-ready teams rather than chase talent in a volatile market.

Why It Matters

The big picture: The global workforce is in transition. By 2030, 59% of employees will need new skills to stay relevant. Yet most “talent intelligence platforms” still depend on static data—résumés, skills taxonomies, and keyword matches—that can’t predict who will thrive in a transformed role.

"Skills indicate readiness, Potential is about the probability of success," Says Jim Griffin, founder of Partner Science Labs, "The conversation shouldn't be 'Skills or Potential', it should be 'Skills and Potential'."

Catalyzr’s bet: potential is the new skill.

By fusing AI efficiency with the rigor of cognitive science, Catalyzr gives HR leaders something they’ve never truly had—precision. It transforms hiring from reactive and biased to proactive and evidence-based.

The Bottom Line

Catalyzr isn’t fighting the AI hiring arms race. It’s ending it.

Instead of matching words to words, it matches minds to missions—helping companies see beyond credentials to uncover capability itself.

In a world awash with optimized résumés and automated rejections, Catalyzr’s Career Quotient brings humanity back to hiring—measuring what machines can’t fake and what truly drives success: human potential.

The takeaway: Stop guessing about talent. Start quantifying it.