AI Agents in HR: How They're Creating Superworkers in 2025

TL;DR

AI as a copilot? That's old news. Today it doesn't wait for instructions. It acts. Decides. Learns. Welcome to the era of the Superworker: people who combine human judgment with AI agents to redesign work from the inside out.

We're not talking about automating minimal tasks. We're talking about AI agents and processes that think themselves, correct themselves, scale themselves... but without human oversight, they can also get us into serious trouble.

The key isn't knowing how to use AI. It's knowing what you're using AI agents for. And then having the guts to rewrite what you used to do.

Work isn't in crisis

The concept of work is.

This isn't some 2030 fairy tale. It's happening now. While some people are still wondering if AI agents will take their jobs, others are already designing with AI agents how work will get done.

Spoiler alert: it's not about asking AI agents to make a spreadsheet faster. It's about rethinking the entire flow: from how someone enters a company to how they learn, grow, rotate, get measured, and move around. All of it with AI agents running in the background.

But knowing how to "prompt" isn't enough for that. You need clarity. Do you want efficiency? Do you want autonomy? Do you want fewer operational tasks, or do you want real impact? Because, as always, the problem isn't the tool. It's not having a clear strategy.

We're entering the age of the Superworker. A new generation of talent that doesn't wait for instructions but also doesn't delegate judgment.

What is a Superworker?

A Superworker is someone who works in an amplified way: with AI agents operating in the background, tools that suggest actions without you asking for them, and most importantly, with human judgment to decide what to accept, what to adjust, and what to discard. According to Josh Bersin, teams that adopt Superworker models improve their productivity by 100 to 300%. How? They stop operating with static role descriptions and start working as living systems.

But to really understand how a Superworker operates, you need to know what types of AI agents they're working with. Because not all AI is the same, and each type of artificial intelligence requires a different approach.

What are the different types of AI?

While there's no academic classification, this is the practical typology for understanding the impact on talent and People Ops.

1. Generative AI
   Creates original content (text, image, code, audio). Doesn't understand deep context or have its own objectives. Just responds to what you ask it.
   Examples: ChatGPT, Midjourney, DALL·E, GitHub Copilot.

   
   

2. Analytical or Predictive AI
   Detects patterns, anticipates scenarios. Doesn't act.
   Examples: People Analytics tools like Visier or Human Capital Management

   
   

3. Assistive AI
   Executes tasks on predefined workflows.
   Examples: simple bots, Zapier with AI.

   
   

4. Cognitive AI
   Interprets natural language, reasons, and decides in limited environments.
   Examples: automated interviews, legal review with NLP.

   
   

5. Adaptive AI
   Learns from the environment. Adjusts behavior in real time.
   Examples: dynamic learning platforms.

   
   

6. Agentic AI
   The most advanced stage. Defines objectives, acts, and learns. It's what allows you to create AI agents that operate as digital collaborators.
   
   

Agentic AI is the qualitative leap. But there's a key difference that many people confuse...

What is an AI agent

(and why it's not the same as Agentic AI)

Agentic AI is the capability. The agent is its concrete form of existence. Still confused? Yeah, me too! Let me clarify this:

An agent perceives the environment, reasons, acts, and learns. It can detect signs of discontent, propose changes, execute communications, and measure impact. But it has no ethics. No context. No empathy.

That's why it always needs human supervision. To avoid scaling errors and to avoid automating bias. To avoid making decisions with human impact... without human intervention.

Now that you understand the difference, the question is practical: how do you incorporate this into your organization's real processes?

How to redesign with AI agents

While generative AI functions as a copilot, AI agents (based on Agentic AI) no longer wait for constant instructions. They act, propose, adapt, and execute autonomously.

That doesn't mean they do everything right. That's why they need a human figure to supervise, correct, and make final decisions. And guess who that human figure is? (wink, wink).

AI agents are transforming the complete talent cycle:

• Recruiting: AI agents that filter, interview, schedule.

• Onboarding: personalized, iterative assistants.

• Performance management: automatic monitoring and suggestions.

• Upskilling: detected gaps, suggested content, measured progress.

• Internal mobility: projects and roles suggested by AI agents based on potential.

Supervising isn't slowing things down. It's preventing an algorithm from making bad decisions on your behalf. The key: don't replace people. Free them from what they no longer need to do. And for that supervision to be effective, you need concrete tools. One of the most important is knowing how to communicate with AI in a structured way.

What are CAPE Prompts and why do they matter?

A prompt isn't an order. It's a structured conversation with AI. CAPE is a structure that helps create prompts with intention and context:

C: Context (what's happening?) A: Audience (who is the output for?) P: Purpose (what are you trying to achieve?) E: Expectations (what form should the response take?)

These prompts don't just work for copilots. They also better train your agents to operate with judgment.

For this to work, People Ops needs to stop operating as a "people machine" (static roles, fixed processes) and move to a systemic model, with dynamic talent flows and decisions based on real data. If not, the agents move forward... and the HR area becomes a brake instead of an enabler.

That simple. That raw. That urgent.

But the strategy doesn't stop at prompts. If you really want to transform your area, you need a step-by-step implementation plan.

Where to start?

1. Map talent processes: what's repetitive? What can be automated?

2. Train in agentic AI: systemic thinking, not just prompts.

3. Run a pilot in a specific area: onboarding, upskilling, internal mobility.

4. Redesign roles: agent supervisors, flow architects.

5. Measure differently: not just productivity. Also adaptability and time to value.

   
   

Frequently asked questions (FAQ)

What is a Superworker?

A Superworker is someone who combines human judgment with AI agents to work in an amplified way, improving their productivity by 100% to 300%.

How do AI agents differ from regular AI tools?

Regular AI tools only respond to instructions. AI agents act autonomously: they perceive the environment, make decisions, and learn without waiting for step-by-step orders.

What are AI agents in HR?

AI agents are autonomous systems that can perceive, reason, act, and learn to handle HR processes like recruiting, onboarding, and performance management with minimal human intervention.

Do AI agents replace HR professionals?

No. But they will replace operational tasks if HR doesn't update itself. HR professionals will focus on strategy, organizational design, and human experience.

How do you implement AI agents in HR?

Start by mapping repetitive talent processes, train your team on agentic AI, run a pilot in one area like onboarding, redesign roles around agent supervision, and measure adaptability alongside productivity.

What are the risks of using AI agents in HR?

Misuse, bias, and automating decisions without proper human oversight. That's why governance and human supervision are as important as the technology itself.

How long does it take to implement AI agents in HR?

A basic AI agent pilot can be running in 2-4 weeks. Complete implementation across all HR processes usually takes 3-6 months, depending on organizational complexity.

What AI agent tools should HR teams use?

For recruiting: HireVue or Pymetrics. For onboarding: Luma or personalized chatbots. For employee development: Coursera for Business with AI or Degreed. Many already integrate AI agent capabilities.

Can small companies use AI agents in HR?

Yes. Small businesses can start with simple AI agent tools like Zapier + ChatGPT to automate candidate screening or Calendly with AI to coordinate interviews.

What if we don't have budget for AI agent software?

Many HR platforms you already use are adding AI agent functions. And with good prompts and clear processes, you can start implementing AI agents without major investments.

Quick glossary

• Agentic AI: the technological capability to make decisions, act, and learn autonomously.

• AI Agent: the concrete implementation of that capability in a process or system.

• Superworker: the person who integrates AI + human judgment to add more value.

  
  

Moving toward the future

If you still think AI is "future stuff," you're late to the party. But if you already understand it's not a threat, but a new way of working, you're still on time. To redesign. To take a position. To stop watching from the sidelines.

HR isn't going to disappear. But maybe those who don't dare to rewrite themselves will.

Download free:

• Our tool for auditing bias in AI applied to talent

• The CAPE Prompts guide for training agents with strategic judgment

And join our WhatsApp community of AI x People Teams. Because it's not enough to use AI. You have to know what you're using it for and have the courage to lead what's coming. Because if you don't lead... someone's going to take your place. And they won't have judgment.