Introduction

Digital transformation has emerged as a critical element for the survival and advancement of contemporary businesses, presenting challenges in the integration and exploration of new technologies (Rêgo et al., 2021). Industry 4.0 technologies have revolutionized global manufacturing trends, with businesses adopting Industry 4.0 models to meet customized demands and compete globally (Jamwal et al., 2021).

This digital transformation has created more intricate working conditions, necessitating upskilling of employees to meet the demands of increasingly specialized and complex jobs (Moore et al., 2020). Companies must cultivate a culture of learning in their work environment (Hochhauser, 2018) to develop innovative products, services, and processes, restructuring knowledge for technological innovations. It is relevant to consider the impact and employee perception of daily technology use (Bag et al., 2021; Hameed et al., 2021; Yuan & Cao, 2022).

The significance of digital technology policies in economic growth is particularly crucial in the era of the 4th industrial revolution (Zhao & Yang, 2023). The impact of digital technology and its adoption for organizational innovation is a central area of study (Li et al., 2023), as markets evolve with changing customer needs accelerated by technology dynamics, compelling companies to adapt (Nyagadza, 2022).

Given the exponential growth of technologies, diverse approaches must be considered. The digital transformation process involves individuals related to organizational culture and leadership in companies (Velyako & Musa, 2023). The development of technological capabilities relies on individual actions at all management levels, emphasizing technical competencies and interactions between managers and employees (Feeny & Willcocks, 1998; McLaughlin, 2017).

The use of AI provides new opportunities for organizations to innovate their value proposition. AI, particularly in combination with increasing production linkages, assists companies in responding specifically to customer needs and personalizing their range of services (von Garrel & Jahn, 2022). This research underscores the value of robotic process automation (RPA) in the globalized digital world, considering new applications and perspectives for business strategy. RPA, an innovative technology, automates repetitive, rule-based tasks previously performed by humans, providing savings to implementing organizations (Ivančić et al., 2019; Syed & Wynn, 2020).

As AI, including other AI-based applications, integrates into human resource management (HRM) approaches, it opens possibilities for innovation. However, it has the potential to impact the labour market by replacing certain jobs, including those involving cognitive elements (Dwivedi et al., 2019). The ongoing advancement of digital technologies, coupled with changes in production structures, affects global worker well-being (Aryal et al., 2019; Parteka et al., 2024).

Current technology, utilizing big data and machine learning, enhances machines’ ability to perform cognitive, physical, and linguistic tasks, creating new jobs (Gibbs, 2022). In this technological context, while the internal workings of these systems remain generally unexplained (Gligor et al., 2021), workers must upgrade and retrain themselves to coexist with AI systems (Jaiswal et al., 2022). Among technologies, AI stands out, radically changing how work is done and who does it. The biggest impact will be to complement and augment human capabilities, not replace them (Wilson & Daugherty, 2018). AI is faster, accurate, and rational, but lacks intuition, emotion, and cultural sensitivity—qualities that make humans more effective (De Cremer & Kasparov, 2021).

One prominent challenge in adopting AI within organizations is the lack of information about the purpose of its incorporation (Babic et al., 2020). Therefore, bridging the existing gap in the current literature through practical research linking employee digital training on digitization and robotic process automation (RPA) and its impact on daily job performance becomes essential. Additionally, exploring the influence of digital skills in society and their implications in the business area will be investigated.

This research begins with the “Literature Review and Theoretical Framework” section that raises the theoretical framework where digitalization and its relevance in the organization are raised. At this point, different approaches linked to the influence of training in the development and implementation of new technologies are considered. In the “Methodology" section, the methodology is developed. In the “Analysis and Results” section, the results are presented and developed. The “Discussion and Conclusions” section develops the discussion and conclusions of the research considers limitations and future lines of research.

Literature Review and Theoretical Framework

With digital technologies shaping competition in many industries, predicting the future of potentially disruptive technologies becomes an essential task for business leaders concerned about the survival and success of their organizations (Krotov, 2019). Digitization is used to describe some social and technical phenomena, as well as the process of adoption and use of digital technologies across a broad spectrum whether individual, organizational, or societal (Legner et al., 2017).

Theoretical Framework

The study has been developed from different sources with a research work, examining the areas to be addressed by the research in terms of process automation and the impact produced not only in the organization but also in the workers.

As indicated in the literature consulted, the methodology used in empirical research can be qualitative, quantitative, or a mixture of both to obtain data that will provide us with the necessary information to carry out the desired analysis.

The paper proposes a qualitative methodology, defining it as “a systematic method for collecting information from a sample of entities in order to construct quantitative descriptors of attributes of the general population of which the entities are members” (Groves et al., 2011). Non-numerical data are collected, which can provide us with more varied information that can provide us with a complete explanation (Jansen, 2013). Both Glaser and Strauss (1967) and Becker (2008) as well as Robinson (1951) will be mentioned as precursors in the use of this methodology. In this type of qualitative research, both the data collection and the research question are developed in interaction with the data analysis (Maxwell, 2012).

The digitalization of organizations, as outlined in various studies (Horlacher et al., 2016; Shet & Pereira, 2021), has the potential to bring about substantial changes by transforming business models and creating value. Managers are required to possess specific skill sets to navigate the constant organizational changes driven by automation (Shet & Pereira, 2021). Digital transformation, defined as the changes brought about by digital technologies affecting a company’s business, involves shifts in products/services and organizational structure (Horlacher et al., 2016). However, preparing for digital transformation is a complex task, necessitating the development of aligned digital capabilities within the organization, including its people and culture, towards a set of organizational objectives (Kiron et al., 2016).

Continuous learning is highlighted as a crucial requirement, with managers responsible for upgrading their employees’ skills for technology-driven jobs (Popkova & Zmiyak, 2019; Shet & Pereira, 2021). Successful digital transformations demand the cultivation of new organizational capabilities for survival and success (Li et al., 2018). Notably, an incremental approach is recommended, focusing on augmenting human capabilities rather than replacing them (Davenport & Ronanki, 2018).

Furthermore, digital transformation should be perceived as a change in organizational mentality, emphasizing innovation and the creative capacity of its people (Vilaplana & Stein, 2020). Managers play a crucial role in maintaining collaboration within teams and motivating them effectively (Shet & Pereira, 2021).

In terms of new insights, the impact of process automation on human resources and organizational processes is emphasized. The shift towards more specialized IT profiles may displace low-skilled positions, and AI applications are expected to fill permanent jobs, with short-term tasks being outsourced (Braganza et al., 2021). This evolution may lead to resistance from workers in easily replaceable roles, necessitating effective communication from managers to mitigate rejection (Arslan et al., 2022; Li et al., 2019). The economic impact of these changes on organizations is highlighted, reinforcing the importance of strategic planning for digital transformation. All references are based on reputable sources and contribute to a comprehensive understanding of the challenges and opportunities associated with digitalization in the organizational context.

Figure 1 shows how the three areas studied in this research work are around the threat of losing the job by automating the processes involved. It can also be seen the different questions that have been used to pose the hypotheses of the research.

Fig. 1
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Evaluation methodology. Own elaboration

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Digital Transformation

Companies that have invested in digital innovation in recent years now find themselves in need of an alignment of their internal competencies to optimize return on investment, recognising that they need to adapt rapidly to new market conditions (Abele et al., 2015) and adapt to a data-driven approach to decision-making (Tiwari & Raju, 2022) using data and data analytics to inform business decisions (Pisoni et al., 2023).

The adoption of new technologies has always been a great challenge for organizations, and the greater the impact, the greater the challenge. The scale and pace of digital transformation makes investments in digitization inevitable for companies of all sizes and sectors (Hossnofsky & Junge, 2019). In highly competitive environments, organizations cannot maintain their advantage without innovation (Ranjbar et al., 2020). The process of digital transformation affects people who are connected to organizational culture and leadership in companies. One of the purposes of this research is to examine the role of digital organizational culture with respect to digital transformation and the development of the firm’s competitive advantage (Velyako & Musa, 2023). Digital transformation is being influenced by various technologies (Nosalska & Mazurek, 2019; Siderska & Jadaan, 2018). Therefore, the continuous advancement of both AI and robotic process automation provides companies with competitive advantages and market dominance (Kot & Leszczyński, 2019). The goals and objectives of the organization are influenced by digital transformations in operations, which affect the organization’s products, processes, structure, and business concept (Matt et al., 2015). This advancement influences daily work routines and consequently working conditions (Metall, 2015). Trends (2016) indicate that digital technologies are currently everywhere, modifying business models and radically transforming the workplace and how work is performed.

Currently, there has been an increase in technologies that have impacted and driven digital transformation (Hofbauer & Sangl, 2019). In turn, within the organization, AI is understood as a multidisciplinary science capable of being applied to the development of new business strategies, relevant for the survival and continuity of the business (Blanco-González-Tejero et al., 2023). The advancement of digitization has equally affected individuals as well as SMEs (Gavrila Gavrila & de Lucas Ancillo, 2021) or large companies. Even though companies have been pushed towards digital change, they are also the enablers of business transformation, creating new sources of opportunities as well as a threat to those who do not adapt (Kane et al., 2015). The use of new technologies gains relevance in the day-to-day operations of the company, as well as Big Data and communications due to their great potential in the business world (Prinz et al., 2016). Consequently, tools are constantly changing, as well as the knowledge and skills required to use them. There are arguments that the introduction of AI in the workplace can also lead to the creation of new jobs, especially in sectors focused on the development and application of AI technology (Puzzo et al., 2020). With a digital mindset, employees throughout the organization will be equipped to seize all the opportunities that come their way (Neeley & Leonardi, 2022). Technology is an ever-changing environment in which companies are subject to continuous change (Corso et al., 2018). In this environment, it is necessary to have a change management where one of the most important points is the development and training of the people in the organization with the necessary skills (Kohnke, 2017); consequently, the following hypothesis has been proposed:

  • H1: Employee training is a driving force that impacts on work automation

RPA in the Work Environment

The concept of robotic process automation (RPA) is a concept that has been implemented in organizations for some time now, focusing on efficiently and automatically resolving large administrative and back-office processes (Madakam et al., 2019; Wang et al., 2022). Its main application lies in tasks, mainly administrative and systematic, on established information systems, where the cognitive activity required is limited (Penttinen et al., 2018). RPA does not require the teardown of existing systems, making it easy to integrate into existing business processes (Shet & Pereira, 2021).

Automation has increased due to the growing use of information technologies, disrupting the labour market. Even though jobs consist of multiple tasks, some of them can be replaced by robots, but it is necessary to think about how humans can complement this automation (Autor, 2015). Automation is replacing those individuals who perform routine and repetitive tasks of low complexity with robots programmed to carry them out (Doménech et al., 2018). Therefore, it is important to establish a systematic approach to RPA implementation, which includes process identification and prioritization; cost and benefit evaluation, role, and responsibility definition; change management; and performance measurement and analysis. According to Siderska (2020) and Eloundou et al (2023), RPA is a driver of digital transformation and can provide several benefits to an organization, including (a) efficiency and productivity (Hou et al., 2023; Wang et al., 2022), (b) accuracy, (c) cost reduction, (d) improved customer experience (Hou et al., 2022), and (e) increased scalability enabling managers to use RPA as a driver for manufacturers to improve productivity, meet consumer expectations, and continuously drive low-cost product innovation (Shet & Pereira, 2021). In this line, Porter and Kramer (2011) suggest that the adoption of this technology can improve efficiency and productivity, which, in turn, can allow companies to invest in higher value-added areas and ultimately create higher-quality and better-paid jobs.

Therefore, it is crucial to provide an overview of the critical factors that contribute to the success of implementing RPA as part of an organization’s digital transformation. In this regard, authors such as Leopold et al., (2018) have pointed out key characteristics such as repetitive, manual, rule-based, and high-volume tasks as good indicators for the implementation of RPA technologies. This is because the use of RPA allows employees to focus on more complex tasks that require creativity and can bring more value to an organization (Siderska, 2020). The impact of new technologies such as AI on workers’ skills is likely to depend on the specific tasks and skills to be automated (Chuang, 2022). However, each organization should evaluate its own processes with the aim of using technology to improve human work, enabling workers to focus on higher-value tasks. Therefore, it is essential to analyse the advantages that RPA implementation brings to the company therefore the following hypothesis has been proposed:

In terms of automation:

  • H2a: Process automation can be perceived as a threat by being more efficient than the worker.

  • H2b: Workers’ creativity increases in digitized workplaces when they are properly trained and coexist with automation systems.

Digital Education

Organizations seem to realize every day the advantages of a symbiotic relationship between workers and AI in the workplace. The organization should foster a culture of continuous learning and development by upskilling employees. This relationship requires workers to develop the technical, human, and conceptual skills necessary for the adoption of AI in the workplace, and organizations must invest in continuous training for their workers, taking time to update and retrain their skills in today’s workplace (Zirar et al., 2023). This will result in and provide motivation for employees and help the organization to attract and retain talent within the organization. Furthermore, a culture of continuous learning and development will help organizations meet changing business needs and remain competitive in a highly changing environment (Cukier, 2020) (Fig. 2).

Fig. 2
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Phases of adopting AI in the workplace

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Digital transformation affects the sustainable growth of companies from a perspective of dynamic capabilities (Yao et al., 2022). The future trend will lead to the disappearance of numerous job positions, of which those that do not disappear will undergo significant changes as automation takes place (Review, 2020). This may suggest that there is a “trust” problem among workers and it can be argued that this problem may progressively improve as workers improve their skills (Gillath et al., 2021). Employees must feel comfortable and find it useful, relevant, satisfying, and easy to use. The employees’ perception of the technology and its features is one of the factors to be considered in the learning process of this technology. Therefore, training is a fundamental aspect to achieve effective implementation of digitalization in both public and private companies. In this sense, several authors have considered the influence of skills training on performance and organizational culture (González-Tejero & Molina, 2022). Organizations need to develop clear and compelling value propositions so that employees appreciate the benefits of acquiring new skills and learning to use AI systems (Sofia et al., 2023).

The Human Resources department has become a vital service in the paradigm shift of employee training. According to Bersin, (2016), digital disruption and social networks have transformed how organizations handle the hiring, management, and support processes for their personnel. Thus, this department acts as an intermediary between employees and digitalization, as it is important to incorporate digital elements into the way work is done to perform tasks effectively, considering that many employees live in a digital world (Bersin, 2016).

In this context, automation is expected to soon transform jobs, workplaces, and workforces (Mashelkar, 2018), where digitization and automation will lead to the replacement of some existing jobs with new ones requiring entirely new skills. The importance of analytical skills will decrease as AI assumes more analytical tasks, tasks that require rule-based and logical thinking. There are arguments that suggest that the introduction of AI in the workplace may also generate new jobs, especially in sectors centred on the development and application of AI technology (Puzzo et al., 2020). Workers are faced with a greater complexity of their daily work tasks and are required to be resilient and adaptable to new (and challenging) work environments (Longo et al., 2017). The adoption of AI will affect both knowledge workers and blue-collar workers, as AI has the potential to improve worker productivity (Leinen et al., 2020).

In this case, a distinction is made between white-collar and blue-collar workers (Gibson & Papa, 2000; Waschull et al., 2022). Blue-collar workers are not as exposed to automation of their jobs because of the physical and manual nature of their work, which is complex to replicate through automation. However, white-collar workers are more susceptible to job loss due to the integration of RPA into work environments. These workers perform cognitive and analytical tasks that RPA has begun to address effectively.

In the next years, both company executives and employees will face a series of challenges as they encounter disruptive digital technologies. People will need to upskill appropriate capabilities for newly defined jobs and work closely with AI technologies to do well in their employment (Jaiswal et al., 2022). In recent years, numerous systems, including web applications and apps, have been designed to facilitate human resource management activities and identify skills gaps in the workforce in order to introduce AI solutions effectively (Sofia et al., 2023). The importance of analytical skills will decrease as AI assumes more analytical tasks, tasks that require rule-based and logical thinking. They will need to learn different important skills, with digitalization and dealing with increasingly omnipresent digital technologies standing out, as well as developing empathy towards their colleagues’ technological preferences (Agrawal, 2018). Thus, the learning of new technological competencies is crucial for digital transformation, but it also needs to consider that employees are motivated to use them (Neeley & Leonardi, 2022). Building on contributions like those made by Seibt and Vestergaard (2018), it should be acknowledged that there will be close collaboration between robots and workers in many areas of the organization. In this sense, it is essential for companies to consider how humans can enhance machine efficiency and how machines can improve human actions, as well as redesigning business processes to facilitate collaboration between them (Wilson & Daugherty, 2018). However, from the worker’s perspective, one of the main fears is the perceived threat of being replaced by a computer (Stettes et al., 2017). As a result of technical advances, unskilled workers will have to adapt and engage in tasks involving social and creative cognitive skills (Rainnie & Dean, 2020). Therefore, training and knowledge associated with the advantages and disadvantages that technologies bring to the organization should be considered. Consequently, understanding the role of training in new technologies and its influence on employee awareness is key. It is necessary for organizations to be able to adapt to the changing environment in an agile manner. This agility will become a competence (Stein & López, 2014). Every agile organization must share the same idea, being purpose and vision, which gives meaning to change and promotes it, as this will be the nexus on which the innovation necessary to cope with market demand will be based; therefore, the following hypothesis has been proposed:

  • H3: The symbiosis between employee and process automation provides better customer service.

Methodology

Methodology and Structure

As indicated in the literature consulted, the methodology used in empirical research can be qualitative, quantitative, or a mixture of both to obtain data that will provide us with the necessary information to carry out the desired analysis. The paper proposes a qualitative methodology since it collects non-numerical data, which can provide us with more varied information. The survey, in studies with a quantitative or qualitative scope, is the most frequently used of all other techniques, including in the virtual online and offline environment, always supported by a properly structured and automated questionnaire to ensure the efficient and transparent handling of a large volume of data in almost real time. Among the traditional and virtual environments, there are obvious advantages, disadvantages, and limitations in the application of techniques and tools in data collection, but due to advances in artificial intelligence and technological advances, old stereotypes have been broken in the virtual environment, ensuring the quantity and quality of data and significantly decreasing the errors that could occur (Cisneros et al., 2022).

The survey has been based on a single attempt and has a single empirical cycle (research question, data collection, analysis, and report) and seeks to study the diversity of a topic within a given population by means of qualitative survey Fig. 3.

Fig. 3
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Research model. Own elaboration

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  1. (1)

    Elaboration and Collection of Survey Data: The survey is elaborated and designed to collect the information necessary to carry out the study.

  2. (2)

    Construct Allocation: Verification that the variables studied reflect or measure the theoretical construct for which they were designed.

  3. (3)

    Initial Analysis: Understanding of the different categories in the audience and their responses using a cross-tabulation format.

  4. (4)

    Threat Perception Analysis: The analysis will be carried out considering the perception of threat with respect to a series of variables.

Data Collection and Sample Characteristics

The questionnaire used was designed based on an electronic form that was distributed among a target group of more than 300 people, which, from the perspective of the objectives of this research, was considered very representative, since in the environment of the University of Alcalá, it includes not only education but also aspects related to administration. At the end of the questionnaire period, 103 samples were collected after eliminating incomplete and invalid samples.

The data collected have been processed and analysed using SPSS statistical software, highly regarded for quantitative research (Yockey, 2018) in the field of social sciences, mainly due to the large amount of information available. SPSS can be highlighted for its usefulness, adequate handling, and easy comprehension, having inside it a great variety of statistical topics oriented mostly to social sciences, covering all the needs of statistical calculation of researchers and professionals in the field to which it is applied (Pacheco et al., 2020). Therefore, the study has been of the descriptive type, using a quantitative approach and cross-sectional design. A questionnaire was sent to working people from different industries and sectors.

Following the proposed theoretical framework and the literature review, the research model was developed to reflect the relationship between training and the impact on automation, the perception of automation on work efficiency, how automation allows workers to act more creatively, and finally how task automation can improve the organization's service.

Analysis and Results

Data and Construct Allocation

The model has been carried out considering the structure of a part of the evaluation questionnaire (Table 1) taking into account the variables EDU, EXP, and AGE, which focus on training, on the attitude towards automation and finally on the implementation and use of automation. From this point on, the three constructs were considered.

Table 1 Evaluation questionnaire. Own elaboration
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The first one “Self-learning” seeks to know the training that the interviewees have with respect to new technologies and the consideration that the interviewees have of the automation of processes. The second one “attitude” seeks to know the opinion of the interviewees with respect to their attitude towards process automation. Finally, the third one “Implementation and use” seek to know the perception of the interviewees about the actual implementation and use of these new technologies.

Initial Analysis

The initial analysis included the variables of form, experience, and age. The variable EDU is taken to check how the interviewee feels about whether he/she can consider him/herself threatened depending on his/her training. The EXPERIENCE variable is taken to check the relationship between the respondent’s years of experience and the sense of threat he/she may feel. The AGE variable will allow us to check the relationship between how threatened the respondent feels depending on the age of the interviewee.

The tables show how respondents answered the questions, considering themselves threatened or not by automation.

In this table (Table 2), the variables Q1_EDU (educational level of the participants) and the variable Q_THREAT (respondents who feel that their job may or may not be threatened by automation). The table indicates that out of 103 people participating in the survey, 60 do not consider their job to be threatened by RPA, while 43 feel that it is threatened.

Table 2 Perception of Threat vs Education
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The table shows a varied distribution of educational levels among the respondents, and most of them do not have the perception that their job is threatened by automation. However, it can be observed that respondents with lower educational levels have a higher sense of threat from the automation of their work.

In Table 3, the variables Q2_EXP (years of work experience of the respondents) compared to the variable Q_THREAT (respondents who feel that their job may or may not be threatened by automation).

Table 3 Perception of Threat vs. Working Experience
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The Table 3 shows a varied distribution in the work experience of the respondents, and as mentioned earlier, most of them do not consider their job to be in danger. However, it can be observed that respondents with higher levels of experience have a greater sense that their jobs may be threatened by automation.

Finally, Table 4 shows the variable Q3_AGE (describing the age of the participants) and the variable Q_THREAT (respondents who feel that their job may or may not be threatened by automation). The table shows that respondents aged between 45 and 59 are the most represented in the sample, and there is a significant number of respondents who do not consider their job threatened by automation. These results suggest that the perception of automation threat may be influenced by the age of the respondents.

Table 4 Perception of Threat vs Age
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Perceived Threat Analysis

An ANOVA analysis is performed because two groups of different sizes are to be compare. In this case, ANOVA will allow us to determine the validity of our hypothesis by comparing the means of the different groups and assessing whether the observed differences are statistically significant.

The ANOVA analysis (Table 5) reveals significant differences in the perception of the respondents regarding the attitude towards RPA-assisted work and the implementation and use of RPA in the workplace. There are responses in which there is a high probability that the differences observed between groups are statistically significant, which implies that they differ significantly in relation to the variable analysed (p < 0.05).

Table 5 ANOVA
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In summary, the results indicate that there is a certain polarization in the perception of the respondents regarding the adoption and use of RPA in the workplace, suggesting that it is important for organizations to understand and address the concerns and opinions of their employees in this regard.

Welch’s t-test is an adaptation of Student’s t-test and is more reliable when the two samples have unequal variances and different sample sizes as in our case. By means of this test, it will check the consistency Table 6.

Table 6 Robust test of equality of means
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Finally, in order to determine the magnitude and the trend of the groups, the descriptive statistics provided the results from the table (Table 7) which indicate that the surveyed individuals have a positive perception regarding the implementation and use of robotics in the workplace. Most of the surveyed individuals perceive that the implementation of such tools can aid in daily work as robots can work more effectively and efficiently. However, there is a neutral perception regarding the efficiency of robotics in customer service and the threat of task automation within an organization.

Table 7 Descriptive statistics
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Statistical tests (Table 6) indicate that there are significant differences in respondents’ answers to some questions related to robotic process automation. In particular, the results indicate that there is no perceived direct impact on automation due to the respondents’ education.

Results

The study that has been conducted provides a series of conclusions that come to demonstrate that the hypotheses that have been considered are valid. The fear of losing their job to a robot and being replaced by a robot is perceived more by people with an intermediate level of education than by people with higher education. In this case, hypothesis H1 is affirmed (H1: Employee training is a driving force that impacts on work automation).

In this case, there is no correlation, so it is true that regardless of education, automation occurs in people with both higher education and primary education.

The adoption of this technology can improve efficiency and productivity, and it will allow us to validate our hypothesis H2a which indicates that the use of robots makes the worker more efficient and leads to fewer errors. The hypothesis “H2a: Automation is perceived to be more effective than the worker” can be considered valid.

Question Q8 (“Robot-assisted workers will be more productive”) and question Q9 (“Robot-assisted workers will make fewer mistakes”) have a significant difference in respondents’ answers, suggesting that most respondents who do not perceive automation as a threat agree that robots increase productivity and reduce errors at work.

The automation will allow the employee’s performance of more complex tasks and requiring more creativity, being able to validate our hypothesis (H2b: Workers’ creativity increases in digitized workplaces when they are properly trained and coexist with automation systems) which states that people who do not consider it a threat free them for other, more creative tasks.

Question Q13 (“Robots replace employees in routine activities, leaving creative and competent activities and exception management to them”) also shows a significant difference in respondents’ answers, suggesting that most respondents who do not consider automation a threat agree that robots can help employees focus on more creative and less routine tasks.

Automation can procure a number of benefits to the organization including enhanced customer experience, and it is considered how humans can improve the efficiency of machines and how machines can improve human actions so our hypothesis (H3: The symbiosis between employee and process automation provides better customer service).

Questions Q16 (“I want to know more about how robots could help me”) and Q19 (“Do you think that by using RPA you can be more efficient in serving customers with the same (human) resources”) have a significant difference compared to questions Q18 (“Investing in automation tools can make everyday life easier”) and Q20 (“Robots can work faster than employees”), suggesting that there is an interest in learning more about automation and consider that it could be beneficial for their work.

The result of this research highlights several factors crucial to the successful implementation of robotic process automation (RPA) in the organization, supported by the survey data. These factors focus on addressing employee perceptions and concerns, as well as recognizing the potential benefits of automation. The following can be highlighted:

  1. (1)

    Customized Educational Approach: Training programmes will be designed to suit employees with intermediate educational levels, as the survey indicates that this group perceives more fear of losing their jobs due to automation.

  2. (2)

    Efficiency and Error Reduction: Focuses on improving efficiency and reducing errors when implementing RPA.

  3. (3)

    Encouraging Creativity and Complex Tasks: Explain that automation will enable employees to perform more complex and creative tasks. It is essential to convey that RPA not only does not replace but also enhances work capabilities by complementing each other.

  4. (4)

    Improved Customer Experience: Automation will be integrated with a focus on improving the customer experience.

Discussion and Conclusions

The result of the research provides some statements that are carried out with process automation. In this case, it can be affirmed that workers are in favour of automation because they are aware that it helps their daily work and that it allows them to be much more efficient than without automation. It can also be seen that the threat they perceive is the same for people with higher education and those with basic education.

The authors conceive automation as something positive for the organization, even though there are several variables that depend not only on technology but also on people: (1) Automation will be limited to a prior study of the process in which a large process must be divided into sub-processes to be carried out. (2) Even though the result may seem positive, it is necessary to consider the limitations on the economic side to not only face automation but also the necessary training for its employees. (3) Automation must be well communicated to employees to avoid rejection by them.

Automation has transformed the way it works by providing new opportunities within the organization and improving the effectiveness and efficiency of certain processes. The use of process automation in companies generates a differentiated perception among employees, with some being in favour of its use in the workplace and others not. The results indicate that the interviewees have moderate levels of training and technological knowledge, suggesting a need for further education in this field and more information about the technology used by the organization they work for, to improve acceptance and implementation of automation.

Conclusions

The research model formulated outlines a framework for clarifying the complex interaction between training initiatives and their consequent impact on automation within organizational contexts. It highlights the importance of identity in understanding how employees respond to the introduction of AI and what outcome it produces. The model explores in detail the dynamics that encompass the perceived influence of automation on work efficiency, focusing on the ways in which automation facilitates creativity among employees. In addition, it considers how task automation, as a key component, contributes to improved organizational service delivery. AI in the workplace will continue to transform the nature of work and the skills required to perform it are increasingly important for both, staff and organizations to address the gap between their current skills and those that will be needed to successfully address these changes. Identifying and understanding this skills gap is the first step in developing effective strategies to improve and reskill the workforce. Once this skills gap is identified, organizations can develop strategies to upgrade and retrain their workforce to fill this gap and ensure that they have the necessary skills to use AI effectively.

By adopting this approach, the research model provides us with an analytical basis for understanding the relationships between training, automation, worker perceptions, creativity, and organizational service improvement.

Specifically, it should be considered that while the results suggest a positive attitude towards automation, concerns still exist. While employees’ fear of job loss due to AI is often due to exaggeration of AI capabilities (Willcocks, 2020), this perceived fear alters workplaces and changes employees’ behaviour, such as knowledge sharing versus hiding (Pereira & Mohiya, 2021).The implementation of automation requires an investment in training and knowledge of new technologies, as well as clear and effective communication about its implementation, to avoid issues with employees (Zirar et al., 2023). The study performed by Manis and Madhavaram (2023) identified in this research three key factors that contribute to the threat of AI identity in the workplace: job changes, loss of status position, and the perception of artificial intelligence as a potential threat. This should be considered by decision-makers within the organization. It is therefore crucial for organizations to understand and address the concerns and opinions of employees in this regard.

Attention should also be given to the associated costs and the concerns that this will generate among employees who view automation as a threat. Finally, it is expected that the implementation of automation can improve productivity and efficiency within the organization, provided that a smooth transition is carried out and accepted by the employees involved in this change.

Theoretical Implications

This research focuses on the positive side of process automation, as well as on the adverse effects on the participants. The research attempts to find the link between the hypotheses raised by answering each one of them. Only a small part has been covered, and much remains to be explored about how process automation affects many other areas of the company.

The study that has been conducted provides a series of conclusions that come to demonstrate that the hypotheses that have been considered are valid. Automation has increased due to the growing use of information technologies, bursting into the labour market. Even when jobs are composed of several tasks, some of these can be replaced by robots, but it is required to think about how the person can complement this automation (Autor, 2015), in line to what Stettes et al. (2017) indicates regarding the fear of losing their job to a robot. The fear of being replaced by a robot is perceived more by people with an intermediate level of education than by people with higher education. Porter and Kramer (2011) indicate that the adoption of this technology can improve efficiency and productivity, which indicates that the use of robots makes the worker more efficient and leads to fewer errors. In turn, Siderska (2020) indicates that automation will allow the employee’s performance of more complex tasks and requiring more creativity which states that people who do not consider it a threat free them for other, more creative tasks. According to a study by Schlegel and Kraus (2023), companies are looking for RPA professionals and expect them to not only have the ability to use certain tools but also specific skills such as business process management or human resources (Madakam et al., 2019). According to Madakam et al. (2019), the cognitive skills of workers as well as their specific skills are equally important.

Eloundou et al. (2023) and Siderska (2021) consider that automation can provide several benefits to the organization among others improved customer experience and Wilson and Daugherty (2018) consider how humans can improve the efficiency of machines and how machines can improve human actions so a large majority of respondents believe it improves customer service.

Digitalization has ensured that automation has taken hold in companies seeking to differentiate themselves from the rest of the competitors. So much so that employee training and adaptation to change is necessary to bring this change to fruition. The result of this change will result in organizations having trained employees capable of meeting new technological challenges, as well as the ability for faster implementation of any new automation-based technology. This will result in greater efficiency and effectiveness of the organization’s employees.

On a theoretical level, it is necessary to continue studying RPA and discover the possible challenges that it will provide to the organization both externally and internally, considering the impact that it can have not only on the technical side but also on human resources.

Practical Implications

The practical result of this study is to see how automation affects the work environment from three areas such as training, attitude towards process automation, and finally on the implementation of this in the workplace.

This automation process takes the organization to a new stage in which (1) it knows the fears that its employees may have regarding automation; (2) it seeks to know the degree of training/aptitude of the employees in automation issues and from here it can make decisions about whether further training is necessary; and (3) it seeks the implementation taking into account the employees to carry out this process.

Although the proposed hypotheses have been validated, in this study, process automation involves very extensive processes. The samples have been taken from persons in active employment, so the results could be biased given the low level of automation that currently exists in many organizations.

It is important to consider the following: (1) The environmental impact of automation as it is known that robots can improve energy efficiency and reduce waste in production processes, but the production and maintenance of robots can have a negative environmental impact. (2) As technology continues to advance it is important that researchers continue to investigate the impact that automation has on all areas of society and a call is made for research in this area with the aim of fostering the area of thoughtful research and facilitating a culture of innovation and digital business collaboration. (3) This will enable companies and organizations to implement effective strategies and policies for the adoption of robotic technologies and ensure a transition for the workers affected by it.

Finally, the study indicates that (1) the authors also warn that even though it can provide many benefits, it is also necessary to see the other side, which are the problems when carrying out automation. A previous study of the process to be automated must be carried out, not every process can be automated. (2) Even when the study seems positive, in real conditions, it might not be so positive due to the different economic and social factors that this entails. The lack of confidence of the management in the project can lead to failure. (3) The help of two people will be necessary, one who knows the process and the programmer who will carry out the automation of this one to avoid possible failures, either of concept or of automation.

In resume, the successful implementation of RPA relies on a combination of customized educational strategies, focus on efficiency and creativity, and the integration of automation to improve the customer experience. These factors not only address employee concerns, but also maximize the potential benefits of RPA in terms of productivity and service quality.

Research Limitations

Although the proposed hypotheses have been shown to be valid, this is only a small part of the research that can be conducted. Process automation addresses many areas of the organization, and this study discusses training, attitude, and workplace implementation and use. The study has only used a small portion of variables that may not reflect the entire reality of the process automation universe or perhaps in terms of the adequacy of the number of variables could have been increased at the cost of making a more accurate questionnaire, but also more complex for the participant.

This research focuses on the positive aspects of process automation and how it can influence the attitude of the people involved in the implementation and use within the workplace, as well as their knowledge of it. It is possible that many companies, even though they are aware of the concept of automation, do not consider its implementation due to lack of resources, either economic or because they do not have employees trained in this area, but even so, organizations will need to invest in upskilling workers to create a more adaptable and skilled workforce that can cope with the new challenges and opportunities of the future.

Lines to Follow

Considering the analyses carried out and the results obtained, it should be considered that research on the processes and tasks susceptible to automation are key in the strategies. The RPA is a growing trend in the business environment and that day by day is transforming the company and its vision of Human Resources. The use of new technologies is part of our daily lives, either as part of an organization or as a society. Although there are many studies, it is believed that there is still much to be explored, so several lines of research are necessary to continue advancing in this field. Thus, it becomes relevant to consider how technologies can impact the health and well-being of robot-assisted workers and how to mitigate potential negative effects.

Other future research line is to analyse the impact that process automation will have on society and the economy within the company. In turn, this will make it possible to consider the gender gap and the inclusion of technologies as facilitating and integrating tools in the face of labour inequalities. It is well known that automation can improve efficiency and productivity, but on the other hand, it will lead to job losses. Research will need to be conducted on how companies will be able to balance automation with the need to retain workers and ensure a just transition for affected workers. Another possible study will be how workers can be upgraded and trained to adapt to these technological changes.

In addition, analysis and evaluation of the benefits and costs of implementing and using RPA in different industries and organizations and its relationship to productivity, efficiency, and profitability should be considered.