AN AI-DRIVEN FRAMEWORK FOR AUTOMATED HUMAN RESOURCE MANAGEMENT

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

AN AI-DRIVEN FRAMEWORK FOR AUTOMATED HUMAN RESOURCE MANAGEMENT

Sai Vishwas.M 1 , Karthik Reddy.V 2 , Rishitha.S 3 , Mahendar.P 4

1234Department of Information Technology, TKR College of Engineering and Technology, Telangana, India

Abstract - Modern HR departments often struggle with challengessuchasmanualresumescreening,documentfraud, inefficient task allocation, and repetitive employee queries. These issues slow down operations and reduce overall productivity. To overcome these limitations, this project proposes an AI-Powered HR Automation System that integrates Agentic Artificial Intelligence, Blockchain based verification, workflow automation, and an intelligent HR Chatbotintoaunifiedplatform.Thesystemautomatesresume collection, performs AI-driven text extraction, and evaluates candidates against job descriptions to generate ranked shortlists. To ensure document authenticity, blockchain hashingisusedforsecureoffer-letterstorageandverification. Ataskschedulingandmanagementmoduleenablessystematic assignment and tracking of HR activities, while the chatbot providesinstantqueryresponses,reducingHRworkload.Built using React.js, Node.js, MongoDB, and Gemini AI services, the system ensures scalability, security, and ease of use. By combiningintelligentautomationwithsecureverification,the proposed solution enhances efficiency, accuracy, and transparency in HR operations, making it highly suitable for modern organizations.

Key Words: AI-Powered HR Automation, Agentic Artificial Intelligence, Resume Screening, BlockchainBased Verification, Workflow Automation, Intelligent HR Chatbot, Natural Language Processing, Secure Document Management.

1. INTRODUCTION

Human Resource management is at the core of every organization, but traditional HR processes such as recruitment, document verification, employee communication,andtaskassignmentofteninvolverepetitive manualwork,delays,andahigherpossibilityoferrors.To improvetheoverallworkflowefficiency,thereisagrowing needforintelligentautomationsolutionswithinHRsystems. OurprojectproposesanAI-PoweredHRAutomationSystem, a unified digital platform that brings intelligence, automation, and data security together to modernize HR operations.Thesystemfocusesonfourmajorcapabilities: automated resume shortlisting using Agentic Artificial Intelligence, secure offer letter verification through Blockchain, smart task scheduling for employee work management, and an AI-based HR Chatbot for instant support and information access. By integrating these advancedtechnologies,thesystemreducestheworkloadon

HR teams, improves decision-making accuracy, eliminates document fraud, and enhances communication between employeesandmanagement.Thisinnovativesolutionaims todeliverfaster,smarter,andreliableHRoperationswhile contributingtooverallbusinessproductivityandgrowth.

1.1 Challenges in Traditional HR Management Systems

TraditionalHumanResource(HR)managementsystemsrely heavily on manual and semi-automated processes for recruitment,documentation,andemployeesupport.Resume screening is often performed manually, making it timeconsuming and prone to human bias and errors. As the numberofapplicationsincreases,HRprofessionalsstruggle to efficiently evaluate candidates based on job-specific requirements. Additionally, verification of employee documents such as certificates and offer letters lacks a secureandtamper-proofmechanism,increasingtheriskof documentfraud.Taskallocationandtrackingarefrequently handledusingspreadsheetsordisconnectedtools,leadingto inefficiencies and poor visibility into HR operations. Moreover, HR teams spend significant time responding to repetitive employee queries related to policies, leave, and onboarding,whichreducestheirfocusonstrategicactivities. These challenges highlight the need for intelligent automationinmodernHRsystems.

1.2 AI-Driven and Blockchain-Enabled HR Automation Approach

ToaddressthelimitationsofconventionalHRsystems,the proposedsolutionintroducesanAI-PoweredHRAutomation

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

System that integrates Agentic Artificial Intelligence, blockchain-basedverification,andworkflowautomationinto aunifiedplatform.ArtificialIntelligencetechniquessuchas NaturalLanguageProcessing(NLP)areusedforautomated resumeparsing,skillextraction,andcandidate-jobmatching, enablingaccurateandrankedshortlisting.

Blockchain technology is employed to generate cryptographichashesforofferlettersandcriticaldocuments, ensuringsecurestorage,authenticity,andtamperresistance. Aworkflowautomationmodulefacilitatessystematictask assignment, scheduling, and progress tracking, improving operational transparency. Furthermore, an intelligent HR chatbot provides instant responses to employee queries, significantlyreducingHRworkload.Bycombiningintelligent decision-making withsecureverification mechanisms,the proposedsystemenhancesefficiency,accuracy,andtrustin HRoperations.

2. PROPOSED SYSTEM

The proposed system presents an AI-Powered HR Automation platform that integrates Agentic Artificial Intelligence, blockchain-based verification, workflow automation,andanintelligentHRchatbottostreamlineendto-end human resource operations. The systemautomates resumecollectionandappliesAI-driventextextractionand NaturalLanguageProcessingtechniquestoanalyzecandidate profiles and match them with job descriptions, generating rankedshortlistswithimprovedaccuracyandreducedbias. To ensure document authenticity and data integrity, blockchain technology is utilized to create cryptographic hashesforofferlettersandcriticalHRdocuments,enabling secure storage and tamper-proof verification. A task management and scheduling module facilitates efficient assignment, monitoring, and tracking of HR activities, enhancing operational transparency. Additionally, the integratedchatbotprovidesinstantresponsestoemployee queries,minimizingrepetitiveinteractionsandreducingHR workload.DevelopedusingReact.js,Node.js,MongoDB,and GeminiAIservices,theproposedsystemensuresscalability, security,andusability,makingitarobustsolutionformodern organizationalHRmanagement.

2.1 System Architecture

Thesystemarchitectureillustratestheintegratedworkflow of the AI-Powered HR Automation System. The frontend, developed using React.js, enables users and HR administrators to interact with the system. Resume data, employee queries, and HR tasks are processed through a Node.js backend connected to a MongoDB database for structured storage. AI modules powered by Gemini AI performresumeparsing,candidateevaluation,andchatbot query handling using Natural Language Processing techniques. Blockchain components generate and store cryptographichashesofofferlettersandofficialdocuments

to ensure authenticity and tamper-proof verification. The workflow automation module manages task scheduling, assignment,andmonitoring,enablingseamlesscoordination acrossHRoperations.

2.2 Intelligent Resume Processing and Candidate Evaluation

The proposed system incorporates an intelligent resume processing module that automates candidate evaluation using Agentic Artificial Intelligence and Natural Language Processingtechniques.Resumescollectedthroughthesystem areparsedtoextractkeyattributessuchasskills,experience, education, and certifications. These extracted features are comparedagainstpredefinedjobdescriptionsusingsemantic similarityandrelevancescoringmechanisms.Basedonthis analysis, the system generates a ranked shortlist of candidates, enabling HR professionals to make faster and moreaccuraterecruitmentdecisionswhilereducingmanual effortandbias.

2.3 Blockchain-Based Document Verification and Secure HR Management

To ensureauthenticityandintegrity of HR documents, the proposed system integrates blockchain-based verification mechanisms. Critical documents such as offer letters and employmentrecordsareconvertedintocryptographichash valuesandsecurelystoredontheblockchain.Thisapproach ensurestamper-proofstorageandallowsinstantverification ofdocumentauthenticityatanystageoftheHRlifecycle.By leveraging decentralized verification, the system enhances transparency, trust, and security in HR operations while preventing document forgery and unauthorized modifications.

2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

3. IMPLEMENTATION DETAILS

The proposed system, titled “An AI-Driven Framework for AutomatedHumanResourceManagement,”isimplemented usingalayeredandmodulararchitecturetoautomatecore HR activities. The system integrates Agentic AI, Large Language Models (LLMs), real-time communication, and blockchain-basedverificationtoimproveefficiency,accuracy, and security in HR operations. The frontend layer is developed using React.js, providing interactive user interfaces for resume shortlisting, HR chatbot interaction, task scheduling, and offer letter verification. The backend layer, built using Node.js and Express.js, handles business logic, REST APIs, and real-time communication using Socket.IO. MongoDB is used as the database for storing candidatedetails,taskinformation,chatbotinteractions,and verificationrecords.ForAI-basedresumeshortlisting,theHR managerinputsajobdescriptionthroughthefrontend.

This job description is transmitted to an Email Watcher Agent,whichconnectstoGmailusingIMAPandautomatically detectsincomingresumes.Resumedocuments(PDF/DOCX) areparsedusingtextextractionlibrariesandanalyzedusing an LLM (Gemini API). The AI generates a candidate match score and summary, which are stored in the database and displayedonthefrontendinrealtime.Resumesareranked automatically based on relevance, eliminating manual screening. The HR chatbot module enables intelligent interactionbetweenHRusersandthesystem.Queriesrelated to candidates, scores, or HR policies are forwarded to the LLM,whichgeneratescontext-awareresponsesusingstored data. This module provides instant decision support and reduces dependency on manual HR assistance. The work schedulingmoduleallowsHRmanagerstoassigntaskssuch asinterviews,onboarding,andreviews.Taskdataisstoredin MongoDB and updated in real time using Web Sockets. Employees can view and update task status, ensuring transparencyandeffectiveworkforcemanagement.Foroffer letter verification, a blockchain-inspired approach is implemented. Offer letter templates are converted into normalized text and hashed using the SHA-256 algorithm. During verification, uploaded offer letters are hashed and comparedwithstoredvalues.Amatchconfirmsauthenticity, ensuring tamper-proof verification. Overall, the implementation successfully automates HR workflows, improves decision-making accuracy, and enhances system reliabilitywhilemaintainingscalabilityandsecurity.

4. RESULTS AND PERFORMANCE ANALYSIS

The proposed AI-Powered HR Automation System was evaluated based on recruitment efficiency, document security,taskmanagementeffectiveness,anduserinteraction performance.Experimentalresultsdemonstrateasignificant reductioninresumescreeningtimeduetoAI-drivenparsing and automated candidate ranking, while maintaining high matching accuracy with job descriptions. The blockchain-

based document verification module successfully ensured tamper-proofstorageandinstantauthenticityvalidationof offer letters without noticeable performance overhead. Workflow automation improved task assignment and tracking efficiency, resulting in better operational transparencyandreducedmanualcoordination.Additionally, the intelligent HR chatbot effectively handled repetitive employeequerieswithminimalresponselatency,leadingto reduced HR workload and improved user satisfaction. Overall, the system exhibited reliable performance, scalability,andenhancedefficiency,validatingitssuitability formodernHRmanagementenvironments.

5. CONCLUSIONS

ThisworkpresentedanAI-drivenframeworkforautomated Human Resource Management that aims to transform traditionalHRprocessesintoamoreefficient,data-driven, and intelligent system. By integrating artificial intelligence techniques such as machine learning, natural language processing,andpredictiveanalytics,theproposedframework automateskeyHRfunctionsincludingrecruitment,employee performance evaluation, attendance monitoring, payroll processing,andworkforceplanning.

The adoption of AI significantly reduces manual effort, minimizes human bias, and improves decision-making accuracy while ensuring faster response times and operationalconsistency.Moreover,theframeworkenhances employee experience by enabling personalized insights, transparent evaluations, and timely feedback. From an organizationalperspective,itsupportsstrategicHRplanning throughreal-timeanalyticsandpredictiveinsights,leadingto bettertalentmanagementandresourceoptimization.

Overall, the AI-driven automated HR framework demonstrates strong potential to improve productivity, scalability, and fairness in human resource operations. As organizations continue to embrace digital transformation, suchintelligentHRsystemscanplayacrucialroleinbuilding agile, resilient, and future-ready workplaces. Future enhancements may include deeper integration with cloud platforms, advanced emotion and sentiment analysis, and improvedexplainabilityofAIdecisionstofurtherstrengthen trustandusability.

6. FUTURE WORK

ThefuturescopeofanAI-drivenframeworkforautomated HumanResourceManagementisextensiveandpromising. Thesystemcanbefurtherenhancedbyintegratingadvanced deeplearning modelsfor more accurate talent prediction, employee attrition analysis, and performance forecasting. Incorporatingemotionandsentimentanalysisusingfacial recognition and communication data can help better understand employee engagement and workplace satisfaction. Migration to cloud-based and blockchain-

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 13 Issue: 02 | Feb 2026 www.irjet.net p-ISSN: 2395-0072

enabledplatformscanimprovescalability,datasecurity,and transparency of HR records. Additionally, integrating explainableAI(XAI)techniqueswillincreasetrustbymaking automated HR decisions more interpretable and fair. The framework can also be expanded to support global workforce management through multilingual natural language processing and compliance-aware AI models, makingitsuitableforlarge,distributedorganizations.

ACKNOWLEDGEMENT

At the outset, we sincerely thank to the management and departmentofITforprovidingconcurrentsupportforour project to complete in stipulated time. Firstly, we would thank the management for providing constant support throughoutthecompletionofProject.Secondly,wesincerely thankourBelovedprincipal,Dr.D.V.RaviShankarandHead of the department, Dr. N. Satyanarayana, for their kind cooperation and encouragement for the successful completion of project report and providing the necessary facilities. We express our sincere gratitude to Dr. M. Dhasaratham, Professor project coordinator, and Mrs. P. HimaBinduAssistantProfessorprojectguideforproviding lab facilities during the Project and for their insightful comments and constructive suggestions to improve the qualityofthisMajorProject.

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