AI recruiting software applies machine learning and language models to streamline sourcing, screening and interview coordination by extracting and structuring candidate information, highlighting relevant skills and automating routine steps that typically slow teams down. Additionally, AI recruiting software can also provide valuable insights into brand reputation and help companies measure and monitor how candidates see and perceive their brand throughout the hiring journey.
By reducing manual review, improving signal quality and providing valuable insights, AI tools help recruiters focus on decision-making rather than administration. As the technology matures, these platforms are rapidly becoming essential for teams looking to hire with greater speed, accuracy and reach.
Top AI Recruiting Software
- Built In
- Braintrust
- GoodTime.io
- Manatal
- Recooty
- Hirefly
- Workable
Built In provides employers with a clear picture of how their brand appears in the AI search tools candidates increasingly rely on to power their job search. Its all-in-one platform analyzes visibility, ranking signals and message consistency across tools like ChatGPT, Google and Perplexity to provide companies with an Employer Brand Reputation (EBR) score. Built In then pairs those insights with actionable items like structured content and AI-ready job distribution to improve how candidates see and perceive a company's brand during every step of the hiring journey.
Best fit for: Organizations that want a centralized AI-powered platform to monitor and optimize employer brand visibility across every point of the candidate hiring journey.
See how your employer brand is performing in AI tools like ChatGPT and Google.
Braintrust uses AI to categorize skills, match talent to project needs and automate parts of the vetting workflow. Its system draws on performance data and past engagements to refine candidate recommendations. The platform supports teams that want structured, repeatable matching within a talent-network model.
Best fit for: Teams seeking AI-supported matching within a talent network structure.
GoodTime applies AI to interview scheduling, load balancing and pipeline efficiency analysis. It evaluates interviewer availability, workflow delays and team capacity to optimize coordination. The goal is to reduce operational friction in high-volume or complex interview environments.
Best fit for: Organizations with complex interview operations that need data-driven scheduling optimization.
Workable uses AI to source candidates, extract skills and generate succinct resume summaries. Its tools support job description drafting, applicant ranking and automated screening steps. These features help teams surface relevant candidates faster within a traditional ATS structure.
Best fit for: Teams looking for ATS functionality with embedded generative and machine-learning features.
Manatal uses AI for resume parsing, candidate scoring and skill-tagging. The platform highlights relevant experience and provides recommendations based on role requirements. It’s designed to deliver lightweight AI assistance inside a streamlined ATS.
Best fit for: Organizations wanting lightweight AI-enabled filtering within a simple ATS environment.
Recooty includes AI functions for job description suggestions, basic filtering and automated resume parsing. Its models help small teams structure incoming applications and surface key details. The focus is on simplifying early-stage review rather than providing deep analytics.
Best fit for: Small businesses needing straightforward ATS workflows with light AI assistance.
HireVue uses machine-learning and conversational AI to support structured interviews, automated screening and assessment workflows. It standardizes interview prompts and offers tools for asynchronous video evaluations. The platform is built to help teams run consistent, repeatable interview processes at scale.
Best fit for: Teams that rely heavily on standardized interview processes and structured evaluations.
hireEZ applies deep-learning models to multi-channel candidate sourcing, skill inference and talent-market analytics. It expands search queries, ranks profiles and unifies multiple data sources about a candidate into a single view. Recruiters use it to run targeted, data-driven outbound sourcing.
Best fit for: Recruiters focused on outbound sourcing and competitive talent research.
Eightfold AI uses large-scale deep learning models to map skills, career paths and candidate fit. It supports sourcing, internal mobility and long-range workforce planning through a unified talent graph. The platform is built to provide predictive insight across multiple recruiting and HR workflows.
Best fit for: Enterprises seeking comprehensive talent intelligence across multiple recruiting and HR functions.
Hirefly uses AI to summarize applications, identify relevant skills and prioritize candidate submissions, helping teams reduce manual screening time by extracting structured signals from unstructured resumes. The platform focuses on early-stage decision support rather than end-to-end workflow management.
Best fit for: Teams needing streamlined screening with minimal configuration.
Paradox uses conversational AI to automate candidate engagement, pre-screening and interview scheduling. Its assistant handles FAQs, qualification steps and high-volume communication across multiple channels. This reduces repetitive tasks for teams managing frequent, rapid applicant interactions.
Best fit for: Organizations managing large applicant volumes and frequent candidate communication.
Beamery leverages machine learning and a large talent graph to assess skills, predict candidate fit and support long-term relationship management. Through its talent advisor, Ray, and intelligence suite, Beamery helps organizations understand talent supply, segment pipelines and plan future hiring needs. The platform is geared toward enterprises operating large, multi-layered recruiting ecosystems.
Best fit for: Enterprises prioritizing predictive talent insights and large-scale pipeline management.
Frequently Asked Questions
What is AI recruiting software?
AI recruiting software is a category of tools that use machine learning and language models to streamline tasks like sourcing, screening, scheduling, candidate communication and brand reputation monitoring. These systems extract skills, classify applicant data, automate repetitive steps and provide valuable insights for hiring managers.
How is AI used in the recruiting process?
AI is used to parse resumes, identify relevant skills, match candidates to open roles, generate structured summaries, automate routine outreach or scheduling, and measure, monitor and analyze brand reputation. It also supports sourcing by expanding search queries, surfacing adjacent skills and analyzing labor-market signals. In later stages, AI can help standardize interview workflows and provide consistent prompts or evaluations.
Will AI replace human recruiters?
AI is unlikely to replace recruiters because much of the hiring process depends on judgment, context and relationship-building. Instead, AI removes administrative overhead by handling tasks such as screening, data extraction and coordination. Recruiters still make the final decisions, interpret nuanced information and guide the overall hiring strategy.
