stdClass Object
(
    [id] => 15951
    [paper_index] => 202505-07-021528
    [title] => THE EMPLOYEE EXPERIENCE IN AI-DRIVEN HR: AN ANALYSIS OF OPERATIONAL OPTIMIZATION AND ITS IMPACT ON WORKFORCE OUTCOMES
    [description] => 
    [author] => Ms. Indhumathi. S, Dr. A. Giriprakash, Dr.K.Priyatharsini 
    [googlescholar] => 
    [doi] => 
    [year] => 2025
    [month] => May
    [volume] => 12
    [issue] => 5
    [file] => fm/jpanel/upload/2025/May/202505-07-021528.pdf
    [abstract] => The workplace experience is improved through operational enhancement and improved employee outcomes through AI-based HRM systems. AI systems integrated into HR operations improve hiring, performance management, and employee engagement, which in turn improves operational effectiveness and allows for data-driven decision-making. AI technologies speed up tedious tasks, allowing HR managers to focus their energies on projects that improve workplace satisfaction. HR departments can provide individualized career development and support services to employees through automation and predictive analytics, resulting in an adaptive human resources system. AI systems continue to face challenges because of concerns about their ethical and transparent nature, as well as the need to strike a balance between automation and human interaction. Businesses should seek AI development that aligns with labor needs.
    [keywords] => Workforce optimization, Employee engagement, Data-driven, Automation, Predictive analytics.
    [doj] => 2025-05-11
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 32
    [journal_id] => 7
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Economics, Business and Management Studies (EBMS)
    [short_code] => IJHS
    [eissn] => 2347-4378
    [pissn] => 
    [home_page_wrapper] => images/products_image/2.EBMS.png
)
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