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September 5, 2025 
9 min read
The internet makes reaching top candidates easier, but it also means anyone can apply. The result is hundreds or thousands of applications. Even spending seconds per application means days of review time – time your best candidates are spending applying elsewhere.
That’s where AI recruiting comes in. It ups your talent acquisition efforts by automatically sourcing, sorting, screening, and surfacing top applicants for human evaluation.
Built into recruiting software, AI lets recruiters focus on nurturing the best talent rather than on the administrative backend.
Here, we’ll learn about what AI sourcing actually is, why it works, and how to implement it.
AI sourcing uses algorithms and machine learning to find candidates matching your job requirements. Think of it as an always-on personal assistant that learns what great candidates look like based on historical data and current needs, then analyzes each application for those qualities.
The technology works 24/7, evaluating and organizing candidates as soon as they apply. It often spots connections recruiters miss, like transferable skills, and reduces hiring bias by focusing on skills, experience, and certifications rather than discriminatory factors such as sex or age.
You’ll encounter AI sourcing through features like résumé screening, candidate matching, automated outreach, and talent pool analysis.
Did you know? AI speeds up decision-making but doesn’t make decisions for you. It screens and identifies potential matches (often with reasoning), but recruiters still review contenders, conduct assessments, and handle interviews where human judgment matters most, such as evaluating values fit.
Automated resume scanning or parsing uses AI within applicant tracking systems (ATS) to extract key information from resumes, including:
This organizes unstructured data from various résumé formats into structured, searchable ATS fields. You can then search, filter, and tag candidates by different attributes without manually reviewing each résumé yourself.
What’s more, advanced AI in ATS allows you to search using natural language rather than search methodologies, like Boolean, for faster and more accurate results.
For the most advanced AI scanning tech, learn more about iCIMS’ enterprise-grade ATS.
Just like recruiters, AI candidate matching is the process of identifying candidates that fit with open job positions based on the information in their applications.
But unlike recruiters, AI algorithms do this automatically, typically assigning a compatibility score or other marker to indicate which candidates align best with each role.
While old AI models relied on keyword matching with job descriptions, modern ATS AI algorithms use semantic relationships to uncover talent.
This goes beyond keywords to analyze related skills, experiences, and qualities of past successful hires for a more holistic understanding of each candidate.
Did you know? In most ATSs, you can train your AI to prioritize the criteria most important to you. For example, a 24/7 fast food restaurant hiring overnight cashiers might weigh availability more heavily alongside other attributes like location and compensation expectations.
AI personalizes and automates communication with candidates, depending on the recruitment software you use.
An ATS, for example, focuses on recruitment process automation to move candidates through the hiring pipeline after they’ve applied. It uses algorithms to automatically reach out to candidates at scale on things like:
But, the AI in a candidate relationship management (CRM) platform uses algorithms and generative AI (GenAI) to proactively source passive candidates through targeted outreach campaigns.
This includes assisting in the creation of marketing materials, like social media posts, and intelligent message targeting.
For instance, you can create email drip campaigns for candidates who visit your career site. Based on their actions, the AI adapts messaging frequency and content to fit their interests and skills, nurturing the right talent to apply while recruiters focus on strategy.
One of the benefits of AI parsing is that it automatically assigns applicants to talent pools categorized by role, skills, location, education, and even silver medalists. Instead of manually searching these lists, AI analyzes past applicants within pools to find matches for open roles.
This reduces the need for additional applications since you have ready-made candidate lists, which is especially helpful for urgent or specialized roles like software engineering.
Pro tip: AI can level up your recruitment marketing by reviewing your various talent pools and sending relevant messaging to keep pipelines hot. Look for CRM software that has this ability built in, such as iCIMS Engage.
AI-powered sourcing comes with a slew of benefits, including:
For a successful and strategic AI rollout, you need to research technology vendors, understand your current tech setup, and set recruitment goals.
Start by asking: What AI sourcing features matter most to us? Review the beneficial capabilities of AI-drive candidate sourcing, then research vendors offering these features. You may be surprised to learn you already have AI sourcing in your current ATS or CRM but aren’t using it.
Remember: Not all vendors’ AI is equal. Be sure to look at its cost, user reviews, integration capabilities, and, most importantly, compliance with labor laws.
The right vendor’s AI should be transparent, with explainable algorithms that promote fair hiring to comply with regulations like the EU AI Act. iCIMS AI, for example, holds TrustArc’s TRUSTe Responsible AI certification to demonstrate its accountability, reliability, and hiring bias reduction standards.
Learn more about how iCIMS built its responsible AI program.
Whatever vendor you choose, its AI must integrate with your existing tools, especially your talent platforms, to see the most sourcing efficiency gains. This means working within current systems to analyze large datasets and suggest suitable candidates.
While many AI recruitment tools come with native integrations with ATS and CRM platforms, not all integrate with human capital management (HCM) systems.
Those that do can increase hiring efficiency further by learning what makes successful hires based on HCM data and uncovering skill gaps candidates can fill.
Determine what key performance indicators (KPIs) your recruitment stakeholders want to improve with AI sourcing. This makes tracking return on investment (ROI) easier.
Whether it’s reducing overall cost per hire, improving hiring velocity, or shortening time to fill or time to hire, tie recruitment metrics to KPIs for simpler monitoring and alignment within larger hiring goals. Below are some example AI-sourcing KPIs that you can modify to fit your needs:
The last step is experimentation, training, and rollout.
First, become familiar with how the AI works, including how it interprets information and how to access its functions. If you can, work in a sandbox environment to test mock automations, evaluate candidates, and understand content generation capabilities.
Next, train recruitment stakeholders on how to use it responsibly. Emphasize that AI is a tool, not a final decision-maker. Recruiters remain essential for reviewing AI recommendations and training the system through feedback. That way, the AI learns to evaluate in line with your team.
Last, start with a small-scale pilot program to test the tools in real life. For example, test the AI’s candidate matching feature on one new job requisition while maintaining normal processes elsewhere.
If the AI successfully meets the KPIs you set in step three, expand to additional positions while testing other features individually.
Eventually, your recruiting needs will outpace what your team can handle manually.
High-volume hiring that includes juggling multiple requisitions for various locations or entities means the sheer influx of applications makes it impossible to adequately review résumés and respond timely to candidates, dragging out time to fill.
And top talent won’t wait for your team to catch up, as they accept offers from competitors instead.
To hire smarter and faster, you need AI sourcing integrated throughout your recruitment technology. It should be reliable, responsible, and well-trained, with a team of experts working to make it better every day.
If that sounds up your alley, check out how iCIMS AI supercharges your sourcing efforts.
Alex is well-versed in content and digital marketing. He blends a passion for sharp, persuasive copy with creating intuitive user experiences on the web. A natural storyteller, Alex highlights customer successes and amplifies their best practices.
Alex earned his bachelor’s degree at Fairleigh Dickinson University before pursuing his master’s at Montclair State University. When not at work, Alex enjoys hiking, studying history and homebrewing beer.
