Article: Using AI to Boost Employee Engagement

#Employee Engagement

Using AI to Boost Employee Engagement

With tools to manage talent, monitor effectiveness, measure productivity, performance, facilitate capability building, predict trends, and red-flag potential problems, AI can turn employee management on its head.
Using AI to Boost Employee Engagement

“Karma of humans is AI – Raghu Venkatesh”

Perhaps the most amazing ability of humans is the ability to adapt and adopt. In today’s world, where disrupters are not just welcomed but are embraced with enthusiasm, the use of artificial intelligence (AI) in businesses is a perfect example of this. The ability to adapt has transformed the 21st-century business environment from the earlier meandering behemoth to a new avatar – vibrant, dynamic, flexible, and most-importantly, technology-driven.

Pivotal to this huge transformation has been the employee. Owing to their impact on business metrics, engaged employees are and will always remain the key to a successful enterprise. So, if AI is all-pervasive, can employee engagement be left behind? With the proliferation of data analytics, rapidly developing IoT universe and use of bots, the use of AI in employee engagement and management is expected to be the next breakthrough disruption. With tools to manage talent, monitor effectiveness, measure productivity, performance, facilitate capability building, predict trends, and red-flag potential problems, AI can turn employee management on its head. From the analysis of historical data to identifying patterns, from connections and linkages to forecasting, AI opens the route to actionable insights and solutions for superlative employee engagement. 

Ways in which AI can boost employee engagement:

Data mining and Predictive analysis: Measuring engagement level, collating relevant results therefrom and providing options will be the game changer that AI will drive. Advanced data analytics and machine learning tools can simplify running engagement programs. With facilitated predictive analysis using historical/current data across variables, it will open up efficient, tailored solutions.  For example, if there is a group of people who are dissatisfied and want to leave the organization, analytics could help inform HR before they decide to leave and hence retain some of them.

Natural Language Processing and Machine learning: A lot of discontent among employees often relates to non-financial components e.g. lack of clarity on career paths, the absence of challenging assignments, inadequate attention to training needs, insufficiency, unattended feedbacks etc. The scales/volumes and subjectivity in feedback render the task of analysing them herculean. Developments in NLP/ML have made sentiment analysis of written/spoken language easier. Pulse surveys have become game changers for measuring impacts  and tracking practices in real time.

Chatbots: Communication is a vital part of employee engagement. AI tools such as chatbots, when used judiciously, offer opportunities for making the communication collaborative, succinct, interactive and fun. Integrated AI/bots  in the communication systems help improve performance reviews and management, pattern identification/discernment, behaviour analysis and prediction etc.

Areas of employee engagement where AI can make discernible impacts:

Employee engagement is an ongoing process, which starts with on-boarding the newcomer. From integrating new recruits into the company culture to the exit interviews, against the backdrop of a fluid and open workplace, AI can substantially impact the lifecycle experience of the company for an employee. These include:

Remote learning and training: Skilling is an area where AI can make a marked difference. From innovative, interactive learning to real-life simulated scenarios for skill assessment, AI can be used to provide high-quality training and allow field staff to be guided remotely. Analytics could also be used to identify areas/personnel where training/reskilling may be necessary or deliver customized training and development programs for employees.    

Equality and fairness: Al tools can remove human prejudices, building an equitable, diverse and unbiased workplace.  With the ability to eliminate human bias, AI creates a platform for swift, efficient grievance mitigation system where conflicts are addressed expeditiously.

Managing Rewards and Benefits: Administration of Benefits and Rewards can be tedious particularly in complex, hierarchical levels (the fuel reimbursement benefit is a good example of this). One of the biggest gainers from the use of AI would be this component of employee engagement. Though technology has eased implementation and management of personalised packages, AI makes the whole process more efficient and optimises the benefits. With a user-friendly interface, ease of operation, freedom and flexibility, AI aids seamless integration of unconventional, new-age employee benefits with traditional incentive packages and thereby creates a novel employee experience. 

Enable better decision making: By removing the laborious rigour and enabling predictive analytics, AI assists better decision making, backed by deep data.  Unhampered by geographical locations and time zones, applying AI can enable a more nuanced decision, based solely on comprehensive content analysis.

AI is perhaps one of the most exciting disruptors in a continuously evolving, technology-driven business arena. Harnessing its potential for employee engagement will require a huge paradigm shift in workplace operations.  Organisations will look closely at the trade-off - Benefits of AI versus Fear of Redundancy. 

While it’s important to balance the human-factor with technology-enabled solutions, AI is a sure-fire way of ground-breaking innovation in employee engagement that no organisation would want to be left behind.

Topics: Employee Engagement

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