HR analytics uses sophisticated levels of analysis of employee-related data to inform decisions and affect positive workplace change (Boudreau and Cascio 2017). HR analytics could be used to improve employee well-being and performance by providing managers with data-driven insights into HR processes, human capital, and organizational performance in a more human-centered way. (Timothy Bartram & Fang Lee Cooke, 2022 in the paper Celebrating the 60th anniversary of Asia Pacific Journal of Human Resources: what has been achieved and what more can be done). HR Analytics engine can help in monitoring of employees’ personal emails, social media activity, and interactions with digital devices, and apps. These may be presented as a means of supporting the employee experience or enhancing “workplace wellness” whilst, in fact, also providing 24/7 intelligence about location, activity, mood, health, and social life (Ajunwa et al., 2017). Employee data are also being used to train algorithms to modify or “shape” behavior in and outside of the workplace, such as through gamifying tasks and incentives (Cardador et al., 2017). HR analytics can be used to monitor talent performance (Minbaeva & Vardi, 2019). HR Analytics, therefore allows HR teams to quickly review performance and impact instant recognition and reward employees.
P4: Machine intelligence positively influences employee engagement by providing capabilities for instant recognition and reward
One of the key methods of influencing an employee’s behavior or performance is to provide them feedback on their past performance (Stajkovic and Luthans, 2001). Traditional feedback methods include annual appraisals and these methods are long-drawn and laborious. However, with digital technologies, it is now possible to provide real-time feedback to employees. JD-R model propagates that employees are motivated when they receive feedback on their performance.
AI tools provide immediate feedback to employees through immediate processing of customer feedback through surveys that maybe administered through a kiosk placed at the check-out counter; or quick data-processing of tickets resolved by service agent and provide rating almost daily.
P2: Machine Intelligence positively influences the motivation of employees, by providing real-time feedback on their performance
Employees were found to informally mobilize using internal digital platforms for employee voice, action or participatory means. (Claire Taylor & Tony Dobbins, 2021) Social Media: A (new) contested terrain between sousveillance and surveillance in the digital workplace). Employee voice (EV) is an enduring employment relations concept encompassing a range of actions that allow employee involvement and participation in workplace decision-making (Wilkinson et al., 2020).
P9: Machine intelligence positively influences employee engagement by enabling digital platform to empathize with their peers/other employees.
Employees are now expressing their disapproval of managers monitoring what they are doing. (Mann et al., 2003). So employees are now monitoring their supervisors (Fernback, 2013; Ganascia, 2010). This applies to all prevalent social media channels, including emails, etc., and allows employees to communicate across.
P3: Machine Intelligence positively influences employee engagement by enabling them to express on social media platforms in the workplace
AI is used to enhance employee experience (Bondarouk & Brewster, 2016). To improve productivity at the workplace, we have started automating work and introduced digital workers. (PwC, 2018). AI enables the implementation of a contract between employer and employee that is based on relationships and not transactions. (Ashley Braganza, Weifeng Chen, Ana Canhoto, Serap Sap, 2021 in their paper Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement, and employee trust)
P7: Machine intelligence positively influences employee engagement by enabling increased employee autonomy
The entire process of career planning, therefore, becomes largely automated and quick. Avoids human biases. And helps in drawing our career paths for employees. AI is used to support internal actors of organizations such as employees facilitating internal job applications. Organizations can reach a broader audience when publishing online information as they are enabled with fine-tuning algorithmic parameters for online services such as online job advertisements. (Cristina Trocin et al, 2021 in their paper How Artificial Intelligence affords digital innovation)
P6: Machine intelligence positively influences employee engagement by providing best-fit career plans for employees.
Digital Employee Engagement
The execution of daily business in the context of remote and agile collaboration requires a certain set of digital tools – e-mail, discussion boards, chat rooms. Recent innovations, such as digital collaboration networks, blogs, online learning platforms, wikis, serious gaming infrastructure, and information are fruitful enablers for virtual collaboration and facilitators of distant leadership.
P5: Machine intelligence positively influences employee engagement by sustaining employee interest at work (and the workplace or even while working remote) through the application of digital collaboration tools
AI provides a higher degree of perceived fairness, transparent feedback, and increased communication. This builds confidence in employees at the workplace. (Cristina Trocin et al, 2021 in their paper How Artificial Intelligence affords digital innovation). The more employees trust the better their communication with employers. (Aryee et al.)
P8: Machine intelligence has a positive influence on employee engagement, by building confidence, about their work & employer relationship.
AI is viewed as a means of emancipating the working class and improving work-life balance. Evidently ongoing technological innovation means that the nature and meaning of work will continue to evolve (Connelly et al., 2020). At the higher end of work areas, digital platforms are argued to provide increased control over work, greater work-life balance, and the opportunity for more meaningful work (Wood, Graham, Lehdonvirta, & Hjorth, 2018). A complete understanding of HR can only ever be achieved through exploring employee experiences, and not just those most immediate or obvious to the interests of employers (Guest, 2017; Yang et al., 2019).
Machine Intelligence platforms can take away routine work and help employees to focus on creative work, areas that help them actualize and realize their true-self.
P1: Machine intelligence positively influences employee engagement by enabling employees to find their true-self at work
DOT1 Solutions Private Limited
Silver Soft Tech Park, 23/24 EPIP, 1st Phase KIADB, Whitefield 560066
120 & 121, 1F, Corporate Avenue, Sonawala Cross Road, Goregaon (East), 400 063
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