Artificial intelligence is reshaping roles, redefining skill sets, and accelerating the rate at which entire industries evolve. The question is no longer if your workforce can adapt, but how quickly.
Learning agility—the ability to learn, unlearn, and relearn as conditions change—has become the skill that separates those who can evolve with technology from those left behind. In an AI-driven economy, where tools and knowledge expire faster than job titles, it’s the single most reliable indicator of long-term success—particularly in leadership roles.
Skills-based hiring gives organizations a practical way to measure and compare this capability, surfacing candidates who can grow into what comes next instead of matching what already exists.
Review the basics with Learning Agility 101.
Filling the AI Skills Gap
Eighty-seven percent of organizations already face skills gaps or expect to within the next five years according to McKinsey. Deloitte adds that 45% of technology executives believe GenAI expertise is their most urgent gap.
As hiring teams race to find unicorn candidates with specific AI experience, the real advantage lies in applicants who demonstrate learning agility.
Thirty-seven percent of workers’ current skill sets will be transformed or rendered obsolete by 2030, so domain-specific experience is becoming less and less important. Learning agility allows employees to stay relevant as new tools and processes emerge.
Technical knowledge can be taught, but the ability to continuously absorb, apply, and adapt new knowledge across different roles and applications is what sustains performance long after the next technology shift.
Explore other AI-related obstacles in talent acquisition.
How to Identify Learning Agility with Skills-Based Hiring
To close that gap, organizations need a hiring model that looks beyond resumes to reveal true potential. Instead of weighing titles or years of experience, skills-based hiring evaluates what candidates are capable of and how quickly they can grow. By combining validated assessments with structured evaluation, hiring teams can identify learning agility as a measurable, comparable skill rather than an abstract trait.
Download “The Science of Skills-Based Hiring” white paper.
1) Identify learning-agile behaviors via job analysis
Job analysis is the key to identifying the learning-agile behaviors that make employees effective in AI-driven environments.
The process breaks a role into its core components, pinpointing what people actually do on the job and how critical each activity is to performance. It ensures that when you measure for learning agility, you’re assessing behaviors that are actually relevant to the role.
For example, a job analysis might reveal that success in a given role depends on how often employees:
- Decide confidently with imperfect data, interpreting AI-generated insights to make timely decisions.
- Unlearn outdated workflows, replacing manual processes with automation or new tools.
- Connect the bigger picture, translating technical findings into business impact.
- Adapt methods while staying outcome-focused, shifting priorities without losing momentum.
- Seek feedback quickly, using critique to refine performance.
- Experiment with the unfamiliar, testing emerging technologies and applying lessons learned.
These behaviors signal that a candidate can adapt as work evolves—exactly what AI-era organizations need most.
Learn more about the role of job analysis in Harver’s skills-based hiring process.
2) Measure learning agility through predictive assessments
Harver’s learning agility assessment evaluates how effectively applicants learn from experience, respond to change, and turn insight into action.
Candidates complete a structured set of questions that assess how frequently they demonstrate the workplace behaviors unearthed during job analysis and how strongly they prefer different approaches. The results highlight each person’s capacity to think flexibly, generate creative solutions, and make sound judgments under pressure.
The assessment provides a single learning agility score supported by detailed insights into the behavioral and personality dimensions that shape it. This allows hiring teams to compare candidates consistently and connect results directly to job requirements.
Harver’s studies show a strong relationship between learning agility scores and on-the-job success across management roles, individual contributors, and early-career professionals. Candidates who score higher consistently outperform peers, making learning agility one of the most reliable predictors of performance in modern hiring.
Browse Harver’s other predictive assessments.
3) Evaluate learning agility with structured interviews
Once assessments identify promising candidates, structured interviews provide the final layer of validation. In a skills-based hiring process, these interviews confirm how learning agility shows up in action, linking assessment results to concrete, job-relevant behaviors.
Because job analysis defines which behaviors matter most, interview questions can focus precisely on those capabilities.
Harver’s assessment data equips hiring teams to personalize these interviews, probing how candidates apply the skills reflected in their results. For example:
- “Your results indicate strong adaptability. Can you share a time you adjusted your approach when a new tool or process was introduced?”
- “Your profile highlights high feedback receptivity. How have you used feedback to improve a project or outcome?”
- “Your results show quick learning in cognitive assessments. How do you typically approach mastering unfamiliar systems or technologies?”
By anchoring interviews in data, organizations make evaluations more consistent and objective. Learning agility can be compared fairly across candidates and linked directly to performance expectations.
Watch our webinar for more skills-based hiring strategies.
Hiring for Agility, Building for the Future
AI is shortening the shelf life of technical expertise. The advantage now lies in identifying people who can prepare for what’s next.
Learning agility is a transferable skill that amplifies others: problem-solving, communication, and collaboration all accelerate when people can adapt quickly. For employers, that translates to shorter time-to-productivity and a workforce that keeps pace with change instead of chasing it.
The shift to skills-based hiring starts with understanding where you are today.
