Two Industrial Engineers Use Tablet Computer, AI Big Data Analysis. Visualization of High-Tech Facility into 3D Rendered Neural Network. Industry 4.0 Machinery Manufacturing

 By Rischelle Alysha T. Legaspi and John Paolo R. Rivera 

With a continued pursuit to enhance business competitiveness, further innovations are necessary to keep up with market demands. Can a tool such as Artificial Intelligence (AI) be utilised to build human resources and enhance productivity?  

The emergence of AI found its use in a myriad of things – from being a search engine, information generator, research, curating multimedia content, among others. Given the versatility of AI’s capabilities, it is more than qualified to be utilized for enhancing worker productivity.  

Using AI to enhance worker productivity 

Dell’Acqua et al., 2023 conducted a worker productivity and quality on AI study and found that a group who used AI was able to complete more tasks with higher efficiency and quality than those who did not. There was a 40% performance improvement for the group using AI. Interestingly, it also allowed for the worst performers to significantly perform better by 43%, as compared to the top performers who witnessed a 17% performance improvement.  

This begs the question: what is it about AI that improves the quality and efficiency in accomplishing such projects? Simply, AI makes a process easier, faster, and more efficient. Because of AI’s capability to streamline mundane tasks, it helps workers by facilitating better outputs and opportunities for both the organisation and its employees (Deranty & Corbin, 2024). 

Such can be programmed to specialise in different roles catered to the needs of your company and employees (Marr, 2024). However, it is essential for professionals to understand the capabilities and limitations of AI. In this way, managers and supervisors will be able to delegate as necessary. As a type of AI, machine learning (ML), which allows computers to learn from data and perform tasks without specific instructions by using algorithms to analyze large amounts of data, identify patterns, and make predictions (Brown, 2021), it is employed to perform routine roles, while the professional will handle analytical tasks. Not only will the integration of AI into daily operations reduce potential errors and losses, but it will also allow the company to upscale production (Shen & Zhang, 2024). Thus, allowing for assignments to be fulfilled more efficiently, both in quality and quantity. The emergence of deep learning (DL), which is a type of ML that uses artificial neural networks to learn from data, inspired by the human brain, can be used to solve a wide variety of problems, including image recognition, natural language processing, and speech recognition anchored on supervised (i.e., discriminative) learning, unsupervised (i.e., generative learning), hybrid learning, and relevant others (Sarker, 2021). Figure 1 illustrates the interrelationship between AI, ML, and DL.  

Figure 1. The relationship of AI, ML, and DL. 

The relationship of AI, ML, and DL.
 Source: Constructed by the authors 

The beauty of adopting AI in the workplace is it provides employees an opening to partake in other more significant roles in their organization (Gibson, 2024). It is essential to perceive AI as not just a mere tool because it is capable of greater things. Rather, AI should be viewed as an assistant (Heaps, 2024). AI is a technological advancement made to streamline one’s workflow and automate repetitive tasks, thus supporting workers in improving their outputs efficiently (Bin Rashid & Karim Kausik, 2024). Working in collaboration with technology will allow it to complement humans’ abilities and expertise. This cooperation will allow humans and machines to gain insights, allowing both to yield better outcomes (Wilson & Daugherty, 2018). For example, given an organization’s data and what’s publicly available, the program can be configured to create conclusions based on specified parameters. Once a response has been automated, this is where a person’s subjective intuition is employed. While the software is helpful in decision-making, nothing beats an employee’s experience. AI may be capable of processing an abundance of data and is objectively precise and accurate. However, AI does not possess the capability to make decisions while taking ethics and empathy into account. The human brain remains the best machine in the world, for these machines do not have the same inherent creativity and ethical and moral knowledge which humans have developed and are able to apply based on specific circumstances. (McKendrick & Thurai, 2022).  

A few examples where AI can be helpful is by instructing it to conduct data analytics (e.g., analyse the main determinants of a company’s revenues and engagement data; synthesise previous reports and create questions based on news and company data). Organizations nowadays have even automated AI as customer service agents, handling even complex ticket concerns. 

AI as a caretaker or protector 

Apart from AI being used to enhance productivity, it can also be an instrument towards improving workers’ well-being. (García-Madurga et al., 2024). Workplace well-being is defined by the Croft et al. (2024) as the presence of a supportive culture that values employee contributions and works toward empowering its workers through provision of resources catering to reducing burnouts and improving their mental and physical health. 

Recently, the healthcare industry has been shifting towards utilising AI to analyse employee’s health data and provide assistance in curating wellness programs based on each individual’s needs (Javaid et al., 2023). Furthermore, it can predict any potential occupational hazards that negatively impact an employee’s mental and physical well-being. However, there is a need for a managerial role in determining whether or not these suggestions and programs are feasible and appropriate. Not only will job quality enhance because of more opportunities, but AI also advocates for elevated wellness programs and safer workspaces. A case of an organization revolutionising healthcare is IBM Watson Health that combined ML and data analytics to make health indicators more accessible while improving efficiency and reducing risks of employees (Küster, 2024). Such sophisticated technology not only helps individuals manage their health but also assists health practitioners reduce weeks’ worth of conducting medical research and synthesising patients’ health profiles; allowing them to higher patient volumes (IBM, 2016). Their health-focused business unit partnered with multiple companies and industries to use their AI technology, including human resources, agriculture, and manufacturing amongst others (Lotze, 2023). Case in point, their partnership with the American Heart Association (AHA) started in 2016 for two primary reasons: to measure workplace safety and to better assess employees’ health via AHA questionnaires and data (Pai, 2016).   

The ethical use of AI  

While AI offers the promise of convenience, it is imperative to avoid the tendency to fully depend the apparatus. Its purpose is to augment worker productivity and the quality of their work without undermining human skills (Isham et al., 2021). While ML was programmed to answer prompts correctly, it may still yield misleading results. Believing these incorrect results is known as hallucinations (Dell’Acqua et al., 2023). While AI is able to answer questions through training, lack of data or training results in misperceptions which create AI hallucinations and present inaccurate or illogical results (Awati & Lutkevich, 2024).  Having the tendency to depend on AI could prevent a person from further honing the skills they need to be able to maximise the potential of these systems (Zhai et al., 2024).  

AI can only be a complementary force if the person using it does not simply accept the answer it serves, but analyses and processes it further.  As sophisticated as AI is, it is not invincible to making mistakes (Neeley, 2023). However, workers using such technology have the capability to reassess whether the output is both accurate and feasible to be applied in professional practice. Furthermore, humans should be capable of critical thinking and understand how and why AI generated such output and conclusion. Essentially, while AI is beneficial in streamlining processes and analysing a vast amount of data, the ultimate decision-maker should be the human. Just like new employees, AI has to be trained before it can be an effective assistant. Thus, the worker who is capable of making creative and logical decisions should call the shots instead of AI. Again, AI is just a supplementary tool.    

The future is AI  

Society is moving towards a world that will require professionals to set up a system wherein humans and AI will need to coexist and work together (Annamalai & Vasundandan, 2024; Köves et al., 2024). The International Monetary Fund (IMF) predicts that AI will affect 40% of jobs, mainly those requiring cognitive abilities such as computer and mathematical jobs, administrative work, financial and legal operations, and more by means of both replacing and complementing (Cazzaniga et al., 2024; Georgieva, 2024; Shrier et al., 2023). This calls for the need to begin shifting towards refining workers’ routines by amalgamating the use of ML. This shift also calls for a modification in human skills – a transition towards developing new work capabilities. 

The integration of the use of new technology with positive reinforcement not only provides opportunities to improve employees’ learning capabilities and upskill, but it also helps remove fear of obsolescence in their respective fields (García-Madurga et al., 2024). Only when an organisation embraces change can they move forward into elevating their workforce into an innovative system where AI and professionals augment one another’s capabilities.  

Way forward  

To further reinforce productivity and expand the economy, AI can be a viable partner for augmenting workforce capability. Overall, AI was made to be used for streamlining menial and rudimentary processes. The machine can handle the mundane and repetitive tasks while humans can focus on the strategic analysis and tasks that are of higher value. The coexistence and collaboration between humans and AI is possible as long as there is a positive and proactive adoption and implementation (Zirar et al., 2023). Rather than resisting AI, organisations should embrace this new technology and keep an open mind to the improvements it can yield for their output quality. It is a technological development that is should be a complement to humans’ work rather than a threat to replace them. This phenomenon is known as Industry 5.0 or the Fifth Industrial Revolution or 5IR, where new technology is utilised solely for efficiency and productivity while maintaining employment and workers’ well-being at the center of the process (Kraaijenbrink, 2022). It also encompasses the notion of harmonious human–machine collaborations, with a specific focus on the well-being of the multiple stakeholders (i.e., society, companies, employees, customers) (Noble et al., 2022). Thus, the advancement of AI, ML, and DL also allows for the orchestration of new roles requiring new skills. 

Implementing the ethical use of AI, and maximising the opportunities that come with it, can drive growth and overcome hurdles in keeping up with demand. However, it is also important to prevent the tendency to depend on the tool. The ultimate goal is to use it to allow workers to partake in more meaningful and higher value work.

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About the Authors 

Rischelle Alysha T. LegaspiRischelle Alysha T. Legaspi is an economist at Oikonomia Advisory & Research, Inc. She is also a candidate of the Master of Science in Industrial Economics degree at the University of Asia and the Pacific (Philippines). Her research interests are macroeconomics, sustainability, and development economics.   

John Paolo RiveraJohn Paolo R. Rivera is senior research fellow at the Philippine Institute for Development Studies where he is involved in the study areas of macroeconomics, tourism development, trade and industry. He also founded Oikonomia Advisory & Research, Inc. He is the recipient of the 2024 Outstanding Young Scientist in the field of Economics by the Philippine Department of Science and Technology – National Academy of Science and Technology. 

References 

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