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Hello, and welcome to another hireEZ Academy course. I’m Shelbie Watts, and today we’re diving into a shift that’s reshaping recruiting faster than most people realize — the rise of agentic AI. In the next few years, AI won’t just automate tasks in hiring. It’s going to change how recruiters think, plan, and make decisions.
Research shows 74% of talent professionals expect AI to have a major impact on hiring — yet fewer than a third feel ready to move beyond basic automation. A big part of that gap comes down to understanding.
Most recruiters today are familiar with task-based AI — tools that complete a command when you give it.
Agentic AI introduces something fundamentally different: systems that can plan, adapt, and collaborate toward broader goals with less micromanagement.
While agentic AI is a relatively new term in recruiting, it’s widely recognized in the AI community as a step beyond basic automation, one that gives systems more autonomy in how they work toward goals.
Today, we’re going to explore what agentic AI really means, how it’s defined across industries, and why learning about it now will put you in a stronger position for the future — even if you're not using it in your daily work yet.
Let’s get started by hearing from our favorite Academy instructor, Dan Harten.
Across industries, agentic AI is defined as AI that demonstrates goal-directed behavior.
Rather than waiting for prompts, agentic systems can work toward objectives independently.
They can adapt strategies, make recommendations, and prioritize actions — all based on learning and feedback.
These systems are typically built on large language models (like GPT or Claude) but go further by adding memory, feedback loops, and planning capabilities, allowing them to act more independently.
In recruiting, that could mean an AI system that doesn't just surface candidates when you search, but notices gaps in your talent pipeline, suggests alternative sourcing strategies, or shifts outreach plans based on changing market conditions.
This shift — from AI as a tool to AI as a collaborator — is important because it changes your role too.
As a recruiter, you move from operating every task manually to guiding strategic outcomes.
Even if you're not using agentic AI today, it's helpful to start noticing which tasks in your workflow could eventually benefit from systems that anticipate needs instead of waiting for instructions.
Back to you, Shelbie!
Sourcing has always required a mix of science and creativity — finding not just candidates who fit, but candidates who can thrive.
Traditional AI improved efficiency by speeding up keyword searches. Agentic AI goes further by understanding the broader hiring goal — and suggesting skill sets, adjacent industries, or candidate profiles you might not have considered.
Imagine hiring for a marketing strategist. Instead of matching job titles word-for-word, an agentic system could recognize that candidates in product marketing, growth strategy, or even customer research roles could bring the capabilities you need.
The shift in mindset here is important: it’s not just about searching better. It’s about thinking more broadly about potential — something agentic systems are designed to support.
And here’s the good news: if you already think this way, you’re ahead of the curve. Agentic AI simply helps you scale that broader thinking across more roles and candidates.
As you source today, start practicing this broader thinking.
Ask yourself: what adjacent skills, industries, or career paths might lead to success in this role — even if they don't match the job title exactly?
Next, let’s see what Dan has to see about Agentic AI and screening.
Screening candidates has often been a balancing act — between speed and depth.
Traditional AI can rank candidates by keywords or basic checklists. Agentic AI can evaluate candidates more contextually — reading career trajectories, transferable skills, growth patterns, and leadership potential.
Instead of only asking, "Who has the right title?", agentic systems ask, "Who has the right trajectory to succeed here?"
These systems are not meant to replace judgment. They act as strategic partners, giving you deeper insight, while still requiring human evaluation, especially for nuanced or leadership roles.
As you review candidates now, even without agentic tools, you can start practicing this deeper lens.
When screening, look for signals of growth, adaptability, and leadership beyond just surface-level keywords.
Developing this habit will prepare you to collaborate more effectively with agentic AI systems as they become available.
Up next is personalization and engagement. Shelbie, we’d love to hear your thoughts.
Today’s candidates expect more than generic outreach. They expect personalized, relevant, timely communication.
Agentic AI makes this possible at scale by adjusting messaging strategies based on candidate behavior — not just sending templated sequences.
However, the effectiveness of these systems still depends on the thoughtfulness of your overall strategy; personalization powered by AI can only go as far as your employer brand and message allow.
If a candidate clicks on a link or replies with a specific interest, the system can adapt the next message automatically, creating a more natural conversation flow.
Even before using agentic systems, it’s valuable to understand this shift.
Think about your current outreach sequences:
Are they designed to adjust based on engagement?
Are you building room for responsiveness instead of just sending automated follow-ups?
Understanding the principles behind dynamic engagement will help you build stronger pipelines today — and position you to use agentic technologies more effectively tomorrow.
Back to you, Dan!
The candidate experience is a critical differentiator in competitive markets.
Agentic AI can create experiences that feel more human, less transactional — by qualifying candidates conversationally, reducing friction in applications, and even scheduling interviews dynamically based on availability and fit.
The end goal isn't just efficiency. It’s creating smoother, more respectful, more personalized experiences for candidates.
That’s why the recruiter’s role is still essential. You set the tone, define the journey, and ensure the technology reflects a human-centered hiring process.
As you think about your current candidate journey, start identifying friction points.
Where could communication be more natural?
Where could unnecessary steps be removed?
Even if you don’t have agentic systems running today, developing this mindset will put you ahead of the curve — ready to design candidate-centric experiences in the AI-powered hiring landscape.
Shelbie’s up next with data reporting and decision support.
Traditional systems collect data and produce dashboards. Agentic AI interprets that data, identifies patterns, and recommends next actions — helping recruiters move from analyzing data manually to making faster, smarter decisions.
For example, an agentic system might notice that candidates with a particular skill set consistently accept offers faster — and suggest prioritizing similar profiles.
Even if you don't have an AI system making those recommendations yet, you can start training your mind to think this way.
Remember, actionable insights depend on strong data hygiene. If your inputs are fragmented or inconsistent, even the best AI will not produce useful recommendations.
When reviewing hiring data, don't just look at what happened — ask, "What trends can I act on?"
"Where are we seeing unexpected patterns?"
This strategic thinking will make you a stronger partner to AI systems as they evolve.
Now, I’ll toss it back to Dan for a few takeaways on building AI literacy for the future.
The biggest takeaway is this: agentic AI isn’t just about automation. It’s about elevating the role of the recruiter.
By taking on repetitive tasks and offering real-time recommendations, agentic AI frees recruiters to focus on what machines can’t replicate — building relationships, understanding nuance, and driving strategic alignment between talent and business goals.
And part of building AI literacy is understanding where its boundaries lie, such as when AI might reinforce bias, or when human empathy is irreplaceable.
Learning about agentic AI now — even before it’s fully embedded in your day-to-day tools — is an investment in your future.
Recruiters who understand how these systems work, where they're valuable, and where human judgment must stay at the center will lead the next era of talent acquisition.
Agentic AI is more than a trend — it’s a structural shift in how work happens. The recruiters who embrace it now, who build their understanding early, will be the ones shaping what hiring looks like tomorrow.
Keep learning, stay curious, and remember: the future of talent acquisition won’t be built by AI alone — it’ll be built by people who know how to lead it.
See you in the next course.
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