US GOOD BUSINESS LAB FOUNDATION

AS PART OF THIS PROJECT, THE ORGANIZATION HAS DIRECTLY IMPROVED THE WELL- BEING OF 189,852 WORKERS AND INDIRECTLY REACHED OVER 815,273 WORKERS ACROSS INDIA THROUGH TOOLS THAT AMPLIFY WORKER VOICE AND STRENGTHEN ORGANIZATIONAL ACCOUNTABILITY. THESE TOOLSINACHE AND STITCHWERE DEVELOPED TO ADDRESS SYSTEMIC COMMUNICATION GAPS BETWEEN LOW-INCOME WORKERS AND THEIR EMPLOYERS, PARTICULARLY IN THE MANUFACTURING SECTOR. INACHE FUNCTIONS AS AN ANONYMOUS TWO-WAY COMMUNICATION SYSTEM, ENABLING WORKERS TO SAFELY REPORT CONCERNS, LODGE COMPLAINTS, AND OFFER FEEDBACK, THUS FOSTERING A CULTURE OF TRANSPARENCY AND RESPONSIVENESS. STITCH COMPLEMENTS THIS BY ENABLING RIGOROUS, REAL-TIME ASSESSMENTS THROUGH SURVEYS AND TESTING, FACILITATING DATA-DRIVEN IMPROVEMENTS IN WORKPLACE CONDITIONS. IN THE CURRENT REPORTING PERIOD ALONE (JANUARY TO DECEMBER 2024), THE PROJECT DIRECTLY IMPACTED 122,071 WORKERS AND INDIRECTLY REACHED 175,415 WORKERS. ADDITIONALLY, AS PART OF THIS GRANT, WE ARE RUNNING RESEARCH STUDIES FOCUSED ON DECENTRALIZING PRODUCTION AND PROMOTING FINANCIAL INCLUSION AMONG WORKERS. WHILE THESE STUDIES ARE STILL UNDERWAY, WE REMAIN COMMITTED TO REACHING OVER 2,000 WORKERS THROUGH PILOT INTERVENTIONS ACROSS THE RESEARCH STREAMS. FULL-SCALE IMPLEMENTATION, ONGOING DATA ANALYSIS, AND STAKEHOLDER ENGAGEMENT ARE PLANNED THROUGH 2025 TO INFORM SCALABLE, EVIDENCE-BASED SOLUTIONS FOR WORKER EMPOWERMENT AND INCLUSIVE ECONOMIC GROWTH.

ENHANCING EMPLOYMENT ACCESS FOR DISADVANTAGED WORKERS THROUGH AI-BASED JOB SEARCH SUPPORT PROJECT OBJECTIVES: TO REDUCE LABOR MARKET BARRIERS FOR LOW-INCOME AND DISPLACED WORKERS BY ADDRESSING DISCRIMINATION, SEARCH FRICTIONS, AND LACK OF JOB MARKET INFORMATION. TO EXPAND ACCESS TO STABLE EMPLOYMENT AMONG HISTORICALLY UNDERSERVED POPULATIONS, INCLUDING WORKERS OF COLOR, THROUGH AI-ENABLED TOOLS THAT MATCH INDIVIDUAL SKILLS TO SUITABLE VACANCIES. TO IMPROVE REEMPLOYMENT OUTCOMES BY INCREASING EXPOSURE TO SECTORS WHERE WORKERS SOFT AND TECHNICAL SKILLS ARE TRANSFERABLE. TO PROMOTE EQUITABLE LABOUR MARKET PARTICIPATION BY TESTING INCLUSIVE, SCALABLE JOB SEARCH SUPPORT TOOLS THAT CAN REDUCE INEQUALITY IN RECOVERY FROM ECONOMIC DOWNTURNS. ACCOMPLISHMENTS: DEVELOPED AND IMPLEMENTED AN AI-ASSISTED ALGORITHM DESIGNED TO MATCH JOB SEEKERS WITH SUITABLE JOB VACANCIES BASED ON A COMPREHENSIVE ANALYSIS OF THEIR PERSONALITIES AND SKILLS. SUCCESSFULLY DESIGNED AND DEPLOYED A WEB-BASED PLATFORM OFFERING PERSONALIZED JOB SEARCH ASSISTANCE TO OVER 1,213 DISPLACED AND LOW-INCOME WORKERS. REACHED A PARTICIPANT POOL THAT IS 66% WOMEN AND 54% NON-WHITE, POPULATIONS TRADITIONALLY UNDERREPRESENTED IN LABOR MARKET RECOVERY EFFORTS. PRELIMINARY RESULTS SHOW THAT PARTICIPANTS RECEIVING AI-INFORMED SEARCH GUIDANCE WERE MORE LIKELY TO BE EMPLOYED AND SPENT FEWER HOURS SEARCHING FOR JOBS, SUGGESTING IMPROVED ALIGNMENT BETWEEN CANDIDATES AND JOB OPPORTUNITIES. PARTICIPANTS RECEIVING BOTH AI AND PREFERENCE-BASED RECOMMENDATIONS SHOWED A 7.9 PERCENTAGE POINT INCREASE IN EMPLOYMENT RATES AND 3.99 HOURS/WEEK REDUCTION IN JOB SEARCH TIME COMPARED TO THE CONTROL GROUP. LONG-TERM GOALS: TO EDUCATE POLICYMAKERS BY PROVIDING EMPIRICAL EVIDENCE ON THE EFFECTIVENESS OF AI-ENHANCED JOB SEARCH TOOLS. TO INFORM PUBLIC WORKFORCE DEVELOPMENT POLICY BY DEMONSTRATING HOW TECHNOLOGY CAN SUPPORT FAIRER LABOUR MARKET ACCESS DURING ECONOMIC RECOVERY. TO SCALE THE PLATFORM FOR BROADER GEOGRAPHIC AND DEMOGRAPHIC REACH, CONTRIBUTING TO SUSTAINED REDUCTIONS IN UNEMPLOYMENT AMONG UNDERSERVED COMMUNITIES.