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Introduction of Critical evaluation of AI, competitive advantage and HR issues Assignment
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Just like any other management sphere that had highly benefitted from the emergence and constant upgradation of AI, Human Resource management likewise never really hesitated in terms of using the technological capabilities that can easily surpass the human workforce as a whole. With the help of its non-human, scientifically encoded skills like decision-making, data analysis, and so on, the globally acknowledged business organizations have accumulated a massive surge in their profit levels, with an additional perk of saving a huge amount of human capital. On the basis of a conceptual overview, it is intended to be analyzed therefore that how can an AI become perfectly fitted within a domain like HRM which particularly focuses on dealing with problems, interactions, and complications related to human psychology precisely.
L03. Critical evaluation of AI, competitive advantage and HR issues
In order to critically analyze the role of AI in Human Resource Management and its practical usage in the development of innovative business strategies, the four building blocks that are used here are as follows – Recruit and staff, Develop and Growth, Monitor and Evaluate and Reward.
Recruit and Staff
For the sake of introducing multi-dimensionality and cross-cultural acuteness at the time of new recruitment, new employees should be enlisted using the impartiality of an AI that is capable of offering a new perspective and its inclusiveness can also serve the ethical purposes of a company.
Multidisciplinary Teams
As the organizations keep on looking for ways to improve the performance of AI in Human Resource Management, they are perfectly aware of the fact that the qualitative outcomes of a non-human invention are bound to offer more layered, specific, and statistically versatile results in terms of choosing competent employees based on the particular needs of the institution. The advantages of having an AI can enhance the actual possibility of forming a team of workers that can cater to various requirements, if needed, with the help of an AI-enabled recruitment process (Malik et al., 2020).
Restructure Roles and Functions
The analytical approach of an AI in the HRM can be applied as a business strategy to bring forth updated adaptability in terms of categorizing the employees with a basic HR database that enfolds the area of expertise of each employee and then use such skillsets into forming new subsections in the entire workspace. AI digitization can be effective to a certain extent so that it might not only trigger the need for a thorough evaluation of the entire workforce but also might be helpful in order to reveal the strengths and weaknesses of its recruitment procedures.
Liquid Workforce
Having clarity is one of the essential components that HRM always needs and nothing but AI can offer so much professional openness during the time of hiring people based on their mobility and adjustment skills. Besides, looking from the perspective of a management team, it should also be kept in mind that an AI can never properly interpret human ecosystems and thus, the change will occur solely on the basis of the data which might initiate an offensive attitude from the workers and affect team management (Premnath and Arun, 2020).
Develop & Growth
Keeping up with the constant technological advances, business strategies are also receiving modifications based on the feedback about their usage and AI tools are also being designed to automatically opt for new methods to achieve job satisfaction in the arena of HRM.
New Ways of Working & Behaviour Skills
Following the employee maps, AI systems are being mentored to learn human attributes and handle sensitive issues that often happen in these fields so that they can be used more like a mobile coach. The National Aeronautics and Space Administration (NASA) supporting the usage of AI in the sectors of HRM, stated that the use of AI has improved HR procedures and enabled them to complete most of the HR activities irrespective of human intervention (Arslan et al., 2021).
Knowledge Development
Readymade and customized training programs and knowledge guides generated by the AI to provide new pieces of information and share previous knowledge can not only be beneficial for the trainees but also become a way to make the experience employees up-to-date. Moreover, AI can be extremely helpful in terms of conveying the change that the company is willing to implement without having delays in terms of indulging in lengthy discussions and thus, forming a fluidity among the staff members.
Lifelong Learning
A major difference that can be spotted if AI is used thoroughly in HRM, is that an AI will never get tired of receiving new information and accepting external collaborations for the empowerment of its management skills. Eventually, it will accept the newly programmed knowledge and use it with a professional approach that would be highly profitable for the organization in terms of the human cost that was spared with the reduction of the training period as a single learned AI can substitute a large number of human trainers that too with an effective training process.
Monitor and Evaluate
With quantitative and qualitative sample selection study methods, the AI can improvise an entire data collection process in order to simplify the evaluation process and keep a tab on the entire flow of work from each and every staff.
Continuous Feedback
A properly synchronized and goal-oriented data collection will provide the workers to understand their shortcomings and rectify them within a due time period. Such an AI-monitored statistical study will be devoid of any personal engagements and a professional distance can be easily maintained with simplified data collection rules with minimal effort. In order to maintain proper communication, Chatbots were launched by Upadhyay and Khandelwal to enable updated and personal connection competencies with candidates and employees through digital formats like text messages, dialog boxes, or emails (Del Giudice et al., 2021).
Value-based Targets
The information underpins such studies as a practice that might inspire multidisciplinary teams to satisfy the managers and peer reviewers with their structurally formed monthly reports. Now, if the monitoring is done by an AI, the entire system becomes more numerical as well as systematic which uplifts the target value with a possible measurement, and consequently, such healthy competition amidst the workspace will improve the quality of performance on a daily basis.
Strategically Aligned Evaluation
The effect of AI should be emphasized in its fundamental purpose of strategical HR management and its automation can be used to transfer the previously gathered reports and data on a regular basis as a shred of evidence to the HR managers who are assigned to program new AI systems. However, it should always be intended to use the technological power of AI only with a substantial effect that has happened with a minute and proper alignment with the HR theories in order to be careful about its risk factors.
Reward system
The AI and its information can be used in terms of showing gratitude that will eventually be able to bring forth engagement from the end of the employees too which would obviously be beneficial for the organization.
Celebrate Learnings & Success
Backed up by HR theories, AI systems are being trained to not only set certain goals for the employees to achieve, but also to provide certain positive feedback in order to celebrate the accomplishments. The assessment of the employee performances can be used to thank the workers for having been productive extraordinarily in a certain sector, for helping out with extra labor in the time of crisis, and congratulate them for their ethical uprighting which can skip a human brain, but can never be missed out by an AI (Tambe et al., 2019).
Ownership Of Complementary Rewards
In terms of managing a team, the reward after a certain period goes beyond the amount of money that the employee receives, and gradually, it becomes a token of honor and praise to show gratitude stimulating a sense of belonging in the professional work atmosphere. The more technologies like AI are introduced to these arenas, the better such rewarding systems can be done with a complementary touch in their approach.
Flexible Rewarding System
By collecting data about the employees for continuous evaluation, an AI can be trained to include categories regarding the employees’ personal preferences and later use them so that a satisfactory reward can be provided in exchange for an accomplishment. It would be a gesture on the behalf of the organization to showcase that the management is very thoughtful about the well-being and it would form a personal connection between the employer and the staff members (Pan and Froese, 2022).
L04. Discussion of the evolution of suitable business examples and its implications for contemporary management practice
Along with the increasing complexities of HR roles and consulting management systems, with professional interactions in mind, introducing AI to cope with business competitions is eventually turning into an essential requirement rather than an innovative choice. In order to deal with several types of business scenarios, internationally acknowledged companies like McDonald’s are incorporating various AI-enabled platforms and devices which would eventually deduct their massive work pressure as well as save a significant amount of human capital to collect more profit with more interesting and creative investments into technological aspects. In the recent times, only 10% of global organizations are using AI in high context and 36% of institutions are supposed to full potential of AI in the near future (Oswal et al., 2020).
Having been determined to overcome any kind of pre-conceived notions and personal biases with the help of AI in the sector of Recruit and Staff following the HR theories, Marlena Taynor, D&I lead at McDonald’s, decided to go for a unique evaluation process by joining hands with SmartRecruiters for tracking down an applicant’s skills, be it professional or emotional intelligence during a process of hiring new employees. With the help of the AI-driven pymetrics platform, they made the entire final screening stage extremely neutral and entirely professional (Dražeta, 2022).
Now, to sustain the Growth and Development in HRM, McDonald’s has decided to collaborate with Apply Thru so that they can reach out to their potential applications in a much easier way than their rivals and in this way, can maintain their position as one of the largest employers. Moreover, the way McDonald’s joined hands with McHire in spite of agreeing to compromise with their hiring requirements, shows how an AI can manage to provide better facilities to both the employees and employers by conducting an interview through online mode. Applications like Paradox, Talkpush, and others used by McDonald’s create a new atmosphere of communication for the applicants to have an experience of speedy interviews and gets a path to learn more about the employer company straight away (Budhwar et al., 2022).
Nevertheless, it should also be highlighted that McDonald’s is also trying their best to involve AI in the task of keeping a record of employee performances and rewarding them for their achievements after a certain period. AI performance management sessions are being introduced timely for conducting real-time assessments, regular checks, and necessary feedback and suggestions. They are also trying to improve their internal communication by looking for the help of AI in order to maintain clarity among the staff members as well as other competitors. It is also trying to build an easily accessible AI system so that those employees who are still trying to get used to these technological advances cannot be deprived due to their lack of enough knowledge (Chowdhury et al., 2022).
In today's industrial environment, it's important to remember that AI's flexibility in the hiring process, in particular, has grown dramatically over the past two decades. McDonald's Director of Workforce Planning and Talent Acquisition, Alexa Morse, has stated that the company's recruitment time is now around a week thanks to the use of AI in the hiring and interviewing processes, which is 60% less than it would have taken a year earlier and significantly less than the industry average of around 21 days. McHire, Talkpush, and Pymetrics are examples of AI technologies that have the potential to speed up the hiring process, which has been a huge assistance to the HRM team overall (FraiJ and László, 2021).
However, McDonald's and others have admitted that AI techniques cannot replace human observations of body language during face-to-face interviews. The candidate's facial expressions during the in-person interview are still very important and are given equal weight, if not more, to the other factors considered. Psychological characteristics are hard for AI to grasp when it comes to high-paying occupations. It is difficult for machine language to evaluate the human ability to swiftly learn, level of dedication, and determination skills and obviously, AI lacks the ability to analyse such soft skills and emotional features. Artificial intelligence (AI) can be seen as a tool to streamline the process, but replacing the human element in most HR recruitment-related operations is a topic of serious dispute (Hamouche, 2021).
Conclusion
Human resource management (HRM) guided by artificial intelligence (AI) is undeniably a system that is solely connected to the management of humans; as such, we should always prioritise the human touch across the board in all facets of management, from seeking applicants to evaluating performance to expressing appreciation, all while maintaining our professional and ethical empathy. Even with AI, it is still necessary for managers to gain first-hand experience from workers at various stages of the hiring and supervision processes. It is important to remember that the applications of AI are programmed and based on data. Artificial intelligence (AI)-enhanced technologies make recommendations, decisions, judgments, and selections based only by data interpretation and analysis, disregarding all human qualities and variables. However, human minds are also responsible for inputting these details into the machines. Thus, there is still the possibility of biases arising from the appraisal of the data, as performed by humans. Furthermore, when hiring new members and searching for numerous potential prospects, keywords restrict the recruiter's pick pool. Applicants who aren't tech savvy but have extensive knowledge in the subject could fall between the cracks of recruiters' radars. It's possible that despite their vast repository of information, they were ill-equipped to craft a resume that would impress an artificial intelligence. Even if there are numerous obstacles and concerns associated with AI and technology, their impact on the field of Human Resource Management is undeniable, and it is also certain that as time progresses, their reliability will rise.
References:
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