Discovering hidden talent: How AI-powered talent marketplaces benefit employers

Kendra Business Technologies’ CEO, Gopal Kulkarni, discusses the transformative power of AI-driven internal talent marketplaces, which utilize machine learning (ML), natural language processing (NLP), and robotic process automation (RPA) to deliver personalized experiences for employers and employees. This innovative approach to talent acquisition revolutionizes how employers engage with potential candidates, offering unparalleled efficiency and effectiveness.

An internal talent marketplace, also known as an Internal Job Board (IJB), is a technology-enabled platform that captures and shares data on available positions, projects, assignments, and other opportunities within an organization. Through the use of AI, these marketplaces match employees’ skills with suitable opportunities based on their capabilities and interests. Additionally, they provide recommendations and feedback to help employees enhance their skills and advance their careers.

Similar to how a travel booking app matches hotels to specific criteria, an internal talent marketplace presents employees with a database of available postings within the organization. Employees input their skills and interests, which can be updated as they develop their abilities through training or new experiences. Algorithms then generate matches and recommendations to relevant candidates based on their profiles.

Departments across an organization can utilize the internal talent marketplace to find the right individuals for various opportunities, including full-time or part-time positions, short-term or long-term projects, temporary assignments, mentoring or coaching relationships, learning or development programs, and volunteering or social impact initiatives.

AI-powered internal talent marketplaces leverage ML, NLP, and RPA to create a seamless and personalized experience for both employers and employees:

1. Machine Learning (ML): ML enables computers to learn from data and make predictions or decisions without explicit programming. ML helps internal talent marketplaces by analyzing large amounts of data on skills, roles, opportunities, and performance. It identifies patterns, trends, and talent gaps, generating data-driven insights and recommendations. ML models also adapt and improve over time based on feedback and outcomes.
2. Natural Language Processing (NLP): NLP enables computers to understand, process, and generate natural language. Within internal talent marketplaces, NLP extracts relevant information from resumes, job descriptions, feedback forms, and other text sources. It classifies and tags skills, roles, opportunities, and interests based on keywords and phrases. NLP also matches candidates with suitable opportunities based on semantic similarity and relevance. It can generate natural language responses and suggestions based on user queries.
3. Robotic Process Automation (RPA): RPA automates repetitive and rule-based tasks. Within internal talent marketplaces, RPA streamlines the workflow of posting, applying, screening, and hiring for opportunities. It reduces human errors and biases in the talent matching process, enhances speed, accuracy, and efficiency of marketplace operations, and integrates with existing systems and platforms such as HRIS (Human Resource Information System), LMS (Learning Management System), and ATS (Applicant Tracking System).