Application of AI in HR: Making Business Future Ready, Constructively
The industrial world was already exploring and applauding the possibilities of artificial intelligence (AI) before the pandemic hit the world in 2019 and was seriously discussing strategies to implement suitable AI solutions across verticals to make businesses future-ready. But, the 2019 COVID pandemic pushed the re-set button, accelerating the implementation efforts, specifically in managing human resources to keep the engine ignited and running. In just a few weeks, HR leaders from across the world were facing the gigantic task of transforming operations from real to virtual and making manpower ready for action from home. One possible realistic solution visible on the rather gloomy horizon was the application of AI in the HR process, be it sourcing, screening & interviewing, selecting & offers, on boarding, grooming, managing, or even showing pink slips. Sailing through choppy waters wasn’t easy, especially when the currency was 'urgency' and system preparedness was in question.
Interestingly, the majority of big organizations were already using AI solutions for HR by 2019 in one form or another other and studies suggested the majority of people trusted robots more than managers and preferred consulting robots to managers for advice. Digital transformation was the way, driven by the need for situational adaptation according to evolving ‘new normal’, but it was challenging for medium and small firms as quick tech adoption, that too of a highly advanced nature, required serious fund allocation and most importantly the commitment of the leadership for structural and cultural transformation.
The effectiveness of AI technologies is well accepted, both in terms of operational efficiency and ROI, but reluctance is in the application of AI more directly or visibly in managing HR. Uncertainties, be a financial, geo-political, or global pandemic, are unfortunate realities of the modern world, so it is necessary for HR leaders to not just understand how AI could transform the HR process, but make businesses ready to face future challenges more realistically.
How AI Can Solve HR Challenges and Make Business Future Ready
In Australia alone, according to ABS statistics, over 1.3 million people changed job in 2022 with job mobility rate of 9.5%, the highest rate since 2012. Responding on evolving trend, BizSym, Team HR, said that the high quit-rate trend is likely and it might be sign of the start of a ‘Great Resignation’ in Australia. The major factor behind the era of ‘Great Resignation”, as staffing solution experts pinpoint, is hiring misfit and aspiration-expectation mismatch. The capability of AI-ML solutions to process big data in a fraction of a second, identify realistic patterns, and generate actionable insights make it highly effective in solving most of the challenge HR managers face and make the process more efficient, responsive, automotive, and people friendly with the best ROI.
Investment in HR technology, mainly in advanced data processing technology implementation, is rising in recent years. According to the Fortune Business Insights study, the global HR technology market is projected to grow $39.90 billion in 2029 from $23.98 billion in 2022 with a major focus on AI and allied technology implementation to boost process optimization and cost-effectiveness. Almost all aspects involving smart staffing solutions could be made more efficient using suitable AI technologies, be it hiring, on boarding and training, employee satisfaction, compensation, and retention. It is all about identifying sore areas more realistically and prioritizing challenges so that one could use suitable AI solutions to solve HR challenges in an era of a tectonic shift.
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Hiring Most Suitable Candidate
Modern organizations focus on flexibility and cost-effectiveness when it comes to building a contingent workforce. The biggest HR challenge is the unconscious biases in job descriptions and the inefficiency of traditional keyword-based application tracking systems. AI solutions have the potential to eliminate unconscious biases and churn huge data to find resumes of suitable candidates for further processing, thus eliminating the cumbersome gigantic task of shorting suitable resumes. Following the automated primary candidate verification process, AI systems can be trained to administer various tests and rank candidates by highlighting various parameters. To eliminate the possibilities of boredom and stress involved in the hiring process, AI-enabled communication interfaces, like chatbots, can be of great help in streamlining the process and making it more engaging.
Simplifying On-boarding
The biggest challenge for HR people is simplifying the on boarding process for remote work process. The traditional on boarding process has the advantage of quick on boarding and cultural assimilation at the office. But virtual on boarding makes the task very challenging, at least until the remote work culture matures enough. Thanks to simple AI tools, now it is possible to personalize and automate interactions with recruits and help them complete regular documentation, login credential, and work familiarization according to their personality, time zone, and need. Human interaction-free communication makes it possible to eliminate the response lag effect, thus simplifying the employee integration process and making on boarding hassle-free.
Automating Up-skilling
Hiring suitable candidates and making them battle-ready is time and cost-inefficient, at least compared to re-skilling and up-skilling existing manpower for evolving challenges and newer opportunities. Unlike the traditional classroom model, it is very challenging for both trainer and trainee to impart up-skill training in time bounded manner in an era of the remote workforce. The absence of real-time interaction and one-size-fits-all study material are some other bottlenecks of the virtual training model. The AI-based training model is highly effective in making the process highly interactive as it learns, adopts, and adjusts according to the individual trainee’s learning style and optimizes the delivery model based on engagement, progress, and performance. Natural Language Processing (NLP), a branch of AI designed to understand and process human language, is highly effective in making learning highly personalized and engaging, resulting in better understanding, practical application, and contextual memorization.
Improve Employee Engagement & Wellness
It is well-established fact that the greater the engagement, involvement, and integration of an employee the greater the job satisfaction and productivity. Teams working remotely from different time zones show disconnectedness and a lack of team spirit.
“Job mobility rate is usually high among those with relatively low job satisfaction rate,” said BizSym, HR Team, adding that recent data indicates, it is more pronounced among women (10%) as compared to men (9.1%).
AI-based models are highly effective in analyzing behavioural inputs and identifying patterns in behavioural changes and accordingly highlight the current mental state of the employee. Predictive models are successfully predicting the level of employee engagement, depression, disassociation, anxiety, and burnout. Equipped with behavioural insights, HR professionals can make timely interventions and make changes to make people feel more engaged by creating a more responsive and engaging work environment.
Making Performance Evaluation Simple
The absence of a transparent performance evaluation system is the most highlighted factor among the factors listed in the list of hurdles in the career development path. Lack of trust hurts both employees and employers and a highly distributed workforce, spread across several time and cultural zones, makes it more challenging for HR professionals to develop an unbiased evaluation model. Thanks to the capability of AI-based models to churn huge data from multiple real-time and static sources in a fraction of a second, now it is possible to generate bias-free insights and evaluate performance more transparently. Besides, the predictive models can identify pain areas and accordingly recommend personalized corrective measures, be it new professional skills or behavioural changes.
Collaborative Progress
AI technologies have the potential to transform the whole HR process, as it could process gigantic data from various sources at a speed that no human mind could do. It will help eliminate cumbersome and boring manual tasks and leave the human mind to do something more valuable, which the artificial mind cannot do. Smart collaboration is the way ahead to make HR more humane so that both corporate and manpower could empower each other using suitable AI technologies.