KEY TAKEAWAYS:

In this guide, we share a 3-stage framework for how to get started with AI in recruiting and how to progress through the maturity curve to maximize impact:

  • Crawl: At this stage, AI is introduced to improve efficiency in existing workflows by automating repetitive, time-consuming tasks.
  • Walk: AI shifts from broad-based task automation to specialized detection, providing data-driven insights to elevate the recruiting process.
  • Run: AI becomes a partner in decision-making, offering recommendations to complement human ownership of hiring outcomes.

As we kick off 2025, AI has solidified its place as a non-negotiable component of the recruiting process. What was once a buzzword is now a must-have asset in retaining a competitive edge in hiring. But getting real leverage out of AI is more than just adding a tool to your tech stack — it should be an intentional process that’s always evolving toward higher-order impact.

In this guide, we’ll help you navigate the AI maturity curve in recruiting, from the basics to expert-level AI integration. Along the way, we’ll tap into insights from Metaview’s co-founder and CEO, Siadhal Magos, on how recruiting teams can embrace AI at each stage. We’ll explore where most organizations stand today, give practical steps for moving forward, and look at what’s next as the pace of innovation continues to accelerate. And stay tuned for our upcoming deep-dive guides where we’ll explore each phase — crawl, walk, and run — in even more detail to give you practical advice for maximizing impact at every level.

The current state of AI in recruiting 

The recruiting world has been proactive and open-minded in exploring AI. Across all of the experimentation that’s happened in the past year, Siadhal identifies two breakout use cases that are already clearly a net benefit for the industry: note-taking and application review. These use cases have saved recruiters game-changing amounts of time, freeing them to focus on higher-leverage work like building relationships with candidates and hiring managers. But the impact goes beyond just time saving; AI is helping recruiting teams extract value from all of the unstructured data that’s important to their workflow—a resource that was previously untapped.

Recruiters are bombarded with information from all sides. They’re often routing all that unstructured data to wherever it needs to go — hiring managers, interviewers, or ATSes. Siadhal explains, “Recruiters are exposed to lots of unstructured data and they're doing the task of routing information — to whatever system or person needs to receive it. ​​There's massive short-term benefits that people enjoy because an AI is now doing that job for them. But actually what we increasingly saw towards the back end of 2024, and we'll see more in 2025, is what people do with all this information now that it’s being managed by an AI. Harnessing that unstructured data within recruiting workflows is a massive opportunity when it comes to recruiting, especially because it's such a human-centered process.”

Another key area where AI is already having a big impact is application review. Siadhal explains, “Various factors, including AI, have led to a massive uplift in the number of applications organizations receive for open roles because suddenly it's very easy to finesse your cover letter or resume to match up with what it appears that this role is looking for. Plus, you've got these systems out there that can allow you to apply for thousands of jobs at once.”

For companies, this has created a new problem: how to sift through all these applications? To help manage this, purpose-built AI tools have come onto the scene to help with application review at scale, and central systems of record are beginning to integrate similar functionalities too. While 2024 was a watershed year for application review, it’s likely here to stay, and we’ll continue to see how recruiting teams strike the right balance between AI-assisted decision-making and human input.

Siadhal’s perspective on AI’s evolution in recruiting is clear: “We should all be in beginner mindset mode.” While AI tools are widely adopted in certain pockets of recruiting, we’re just beginning to unlock their potential for more specialized and strategic uses.

While everyone is at different stages of their AI in recruiting journey, we’ll break the maturity curve down into three stages — crawl, walk, and run — and help you understand how to best navigate each.

The crawl stage: Automation of rote tasks 

The crawl stage is where most recruiting teams begin with AI — starting small and focused. At this point, AI can improve parts of your existing workflows rather than overhaul your entire recruiting process. Think of it as introducing AI to handle the repetitive, manual duties — undifferentiated tasks — that suck up a lot of time, but aren't necessarily core to the jobs of recruiters or the rest of the hiring team.

The goal here isn’t transformation, but optimization. Ask yourself: How can AI help me work more efficiently so I'm spending more time on the essential parts of my job?

Key characteristics of the crawl stage

  • Integration with existing workflows: At this stage, recruiters are typically using generic tools like AI note-takers and scheduling assistants to handle routine tasks more efficiently.
  • Focus on efficiency: The emphasis is on saving time on tasks that can easily be automated, like taking interview notes or managing scaled candidate communications.
  • Low-risk experimentation: Teams experiment with easy-to-integrate tools and refine their processes without making major changes to their overall recruiting strategy.

Siadhal emphasizes, “The crawl stage is about adding AI to your existing workflow. You’re not actually thinking about, ‘How can I take a fundamentally different approach to hiring?’ You’re just thinking about, ‘How can I get rid of some of the things that we currently have to do that we really wish we didn’t?’”

How to execute the crawl stage

  • Start by experimenting with generic AI tools to get a feel for how they can help automate repetitive tasks. This is often led by early-adopter ICs who act as the agents of change. Of course, having a leader who is supportive of top-down experimentation will also help accelerate the process. 
  • Identify areas where AI can take over manual processes that automation and AI are smart enough to handle, like taking interview notes. It’s particularly helpful to think about where AI can remove tasks that are important, but not core, to someone’s role. For example, it’s not an official part of the job of engineers, salespeople, or PMs to take great interview notes, but the data from those notes is essential to a high-quality hiring process. 
  • Build an opinion on which tools or processes work best, and think about refining your approach as you gain more experience and drill down further into your specific needs.

Signs you’re ready to progress from the crawl stage

  • You’re comfortable using basic AI tools and have automated tasks that once consumed significant time.
  • You’ve built intuition around which tasks benefit most from AI.
  • As your familiarity with the tech grows, you start identifying opportunities for more specialized AI solutions to unlock more benefits.

The walk stage: Detection with specialized solutions

The walk stage marks the shift from automating tasks with generic AI tools to leveraging the data gleaned from specialized AI purpose-built for recruiting. A key component of this stage is detection. Once you’re capturing the data that’s flowing through your recruiting processes, the focus shifts to identifying patterns. Siadhal explains, “Now that you have this data, you can start to detect things that you otherwise would have missed. You can start to instruct the AI to pull out specific insights from a sea of unstructured data. That's where the specialist tools really come into their own.”

Key characteristics of the walk stage

  • Adoption of specialized AI tools: Moving from broad-based AI tools to tools purpose-built for recruiting.
  • Data collection and analysis: AI enables deeper insights by analyzing data across the recruiting process. For example, AI can help derive compensation banding data from what’s mentioned in conversations or refine job descriptions with data from intake meetings and interviews.
  • Integration into core workflows: AI starts to play a central role in day-to-day recruiting tasks, rather than just adding a productivity boost to existing workflows.

“You start to realize there’s a whole heap more you can do with the data,” says Siadhal. In the walk stage, AI tools are no longer just automating tasks — they're helping recruiters make smarter decisions by analyzing data collected throughout the recruiting process.

How to execute the walk stage

  • Implement specialized recruiting AI tools designed to handle specific tasks, like interview note-taking, candidate scoring, or job description optimization.
  • Start using AI-generated insights to improve recruiting outcomes. For instance, AI can suggest more effective interview questions or leverage insights to help you stop rogue interviewers from jeopardizing your hiring process.
  • Use AI to detect patterns you wouldn’t otherwise be able to uncover. For example, you can diagnose issues in your interview process or source candidates from the historical bank of all candidates you’ve previously spoken to. 

Signs you’re ready to progress from the walk stage

  • You’re consistently using specialized AI tools across the recruiting team.
  • You’re regularly detecting and taking action on AI-generated insights that affect your hiring process.
  • You’ve started to see clear ROI from your AI implementations — whether through improved quality of hire, increased efficiency, or more confidence in hiring decisions.

The run stage: AI-assisted decision-making

The run stage is where teams will start to rely on AI for assistance in decision-making. As we enter this phase, we’ll have to answer the weighty question: In what way are we comfortable with AI affecting our decisions about who to hire? While we’re still in the nascent phases of this debate, the ultimate outcome will likely include a mix of AI-assisted recommendations and human input. For example, AI can look at quality-of-hire data, historic pipelines, and data from intake meetings and interviews to make an informed recommendation about whether or not someone will be a strong hire. And the human in the loop will need to apply their judgement on top of that data. 

As Siadhal says, “At the end of the day, the AI is not going to get fired if it makes a bunch of bad hires. The hiring manager and the recruiting team will be. But it would be short-sighted to think that in the near future, this super intelligence at our fingertips won’t be applied to better hiring decisions.”

Key characteristics of the run stage

  • AI-assisted decision-making: AI moves from automating tasks to influencing hiring decisions. By providing recommendations based on deep contextual data, AI will help hiring teams make more informed, data-driven choices while humans retain final authority over decisions.
  • AI as a strategic partner: AI shifts from detection and automation to becoming a core assistant in strategic hiring questions. Recruiters will use AI to assist with everything from assessing candidate fit to predicting hiring outcomes. 
  • Empowered recruiters: In the run stage, recruiters will be empowered to create leverage for themselves with AI in whatever way suits them. Companies will be instrumented in such a way that recruiters can choose how and when they want to adopt AI in different parts of their workflow, and it doesn’t need to be a one-size-fits-all approach.

How to execute the run stage (once we get there)

  • Implementing AI-driven insights into decision-making frameworks, while maintaining human oversight and control.
  • Creating an environment in which recruiters are empowered to innovate with AI tools and adapt them to meet their personal needs and preferences. 
  • Developing custom AI workflows that align with your organization’s unique hiring process.

The run stage is the future of AI in recruiting — where AI becomes a strategic partner in the hiring process and deep customization at the personal and organizational level is commonplace. While we’re not there yet, it’s exciting to think about how far things will likely advance in the next couple of years. 

The role of the future-proofed recruiter

You might still be wondering what evolving across these stages means for the role of the recruiter. Siadhal stresses that the fundamental role a recruiter plays will always be important: “Even if you enable every step of the workflow with AI, you're still going to have a group of human beings who are tasked with giving the company alpha in winning the very best talent. And those people are still going to be recruiters. The tasks they do might be different, but companies will always want someone whose job it is to make sure that they have every chance possible of winning the best candidates.”

Reimagining the recruiter's role

As we move through this year and beyond, recruiters will find their roles shifting in new directions. Here’s where recruiters will increasingly focus their time and attention and AI’s impact deepens:

Strategic coaching of hiring managers

With AI handling routine tasks, recruiters will have more time to focus on guiding hiring managers to run a precise hiring process that gets the best talent in the door. As Siadhal puts it, “The actual job of getting a pipeline full of candidates to speak to becomes the easy bit. Your job will increasingly become coaching the hiring manager.” 

Developing deeper candidate relationships

Recruiters will increasingly focus on creating personalized candidate experiences to drive competitive advantage in the talent market. As Siadhal explains, a great recruiter can bring value to the organization by “obsessing over how we get every human being we come into contact with to have an amazing candidate experience.”.

Making nuanced hiring decisions

Despite AI’s advancements, human judgment will remain central to hiring decisions. Siadhal explains, “The recruiter’s job will become about weighting, evaluating, and verifying the outputs of these AI models.” As AI becomes more integrated into decision-making, recruiters’ roles will shift toward customizing and verifying AI-generated insights that influence hiring decisions.

Moving forward with AI in recruiting

No matter where you stand on the AI maturity curve, the key is to take action. Start small, experiment, and refine your approach as you go. Organizations that thoughtfully adopt AI, while keeping a focus on leveraging human differentiation, will be well-placed to succeed as disruption continues. 

The future of recruiting isn't about AI replacing recruiters — it's about AI enabling recruiters to be more human, strategic, and effective at what they do best: bringing the right people together to build great teams.