The Role of Generative AI in Managing Industry Projects: Transforming Industry 4.0 Into Industry 5.0 Driven Economy
Article Category: Research Article
Publicado en línea: 29 dic 2023
Páginas: 27 - 41
DOI: https://doi.org/10.2478/law-2023-0006
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© 2023 Moyassar Y. Mohammed et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
While the extensive use of robots in the manufacturing industry improved production efficiency and seemed to maximize profits, robots have limited capability in vision and unpredicted orientation, unlike humans, who are very capable of making a proper judgment. For example, the Tesla Model 3 production plan to be fully assembled using only automated robots had fallen apart and ended up substituting humans. This plan was the epitome of an Industry 4.0 profitability-driven approach that ultimately needed reconsideration and complementation that requires human selective involvement in the manufacturing process, leading to emerging Industry 5.0, which focuses on human-centric design. Neglecting human collaboration in managing industry projects and leaning on robots and generative artificial intelligence only poses serious problems, from assembly line failure and robots underperform to legal challenges and accountability. By embracing a hybrid model of Industry 4.0 and Industry 5.0 and relying on generative artificial intelligence in a governance environment, the projects would eliminate failure and legal problems. Generative artificial intelligence plays a significant role in assisting humans to perform effectively. For example, Amazon embraced direct human-robot interaction in their warehouses. Robots efficiently assist with transporting packages within the warehouse, while humans focus on essential matters.
This is a position paper on the role of Generative AI in managing industry projects (not ongoing routine activities), transforming the current Industry 4.0-driven economy into an Industry 5.0-driven economy.; Including the engineer’s classification of likely legal challenges associated with this process.
The authors first define the technical terminology; second, provide a background on the Industrial Revolution; third, study the different positions’ arguments and counter-arguments from pertinent scholarly sources and project management practice; and then provide an assertive opinion followed by a conclusion.
Sabrina Ortiz,
Scriven / 4.0 Solutions. (n.d.).
Tammy L. Madsen, Dara Szyliowicz, “Industry Transformation”, in:
Project Management Institute. (2017). A guide to the project management body of knowledge: PMBOK guide.
Xun Xu/The University of Auckland. (2023).
European Commission. (n.d.).
Figure. 1. illustrates the chronological transformation and complexity interaction between the Industrial Revolution and Artificial Intelligence (AI.)
Figure 1.
Industrial Revolution with key milestones and significance of AI towards human beings’ intelligence
Dimitris Mourtzis (ed.), Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology, 1st ed.; Elsevier: Amsterdam, 2022; Saeid Nahavandi, “Industry 5.0—A Human-CentricSolution.”
The coexistence of the two Industrial Revolutions (4.0 and 5.0) has undoubtedly raised some questions. The issues are anchored in both the scientific and business communities. These questions do not purport to be all-inclusive, but some of them include:
Can GenAI assume a role in managing some capacity industry projects? What is the Industry 4.0 Driven Economy? What is the Industry 5.0 Driven Economy? What are the legal Challenges of utilizing GenAI, and how to overcome them?
Many scholars believe that a merger between GenAI and Industry 5.0 is a positive movement toward a more sustainable future and human values captured by new business models and regulations that will reshape how business is conducted, and operation is performed in a resiliency and sustainability approach, including the project management practice. On the other hand, other individuals believe that GenAI is causing legal challenges and data privacy and security issues, and Industry 5.0, as currently defined, is senseless and brings no value. It is a marketing gimmick from people and organizations that should know better
Paul Miller,
Due to its ability to improve decision-making, optimize resource allocation, and expedite workflows, GenAI has grown to be a promising part of project management. Project managers can concentrate on more high-level strategic operations by automating monotonous jobs with GenAI, lowering the possibility of human error. Additionally, GenAI-powered technologies can analyze enormous amounts of data, allowing teams to make data-driven decisions and spot trends and patterns that might not initially be obvious.
GenAI can improve communication and collaboration within project teams in addition to process automation and data analysis. GenAI can help with report writing, email drafting, and even real-time language translation, removing barriers to communication and fostering more productive teamwork.
Many project management processes require past performance experience and lessons learned from previous shortcomings. Applying project management areas of knowledge such as Project Integration Management, Project Scope Management, Project Time Management, Project Cost Management, Project Quality Management, Project Resource Management, Project Communications Management, Project Risk Management, Project Procurement Management, and Project Stakeholder Management is progressive and elaborative on its nature and adaptable to change. Therefore, engaging GenAI in the project management area of knowledge will create excellent benefits. For Example,
Project management plans, status reports, communication facilitation, and post-project reviews can all be produced by GenAI with assistance. Project scope statements, Work Breakdown Structures (WBS), managing scope modifications, streamlining scope verification and control, and conducting post-project reviews are all tasks that GenAI may assist with. GenAI can assist with developing Gantt charts, estimating activity durations, creating project schedules, optimizing critical routes, and tracking project progress, and may connect to Primavera P6 and Microsoft MS-Project. GenAI can help with budgeting, cost-benefit evaluations, project expense tracking, and risk management. The development of a quality management plan, identifying quality risks, supporting activities related to quality control, and streamlining communication and reporting related to quality performance can all be aided by GenAI. GenAI may aid in creating a Resource Breakdown Structure, resource estimation, planning, and leveling, as well as resource monitoring and control. The creation of stakeholder-specific communication materials and plans, support for communication monitoring and control, expediting the documentation of lessons learned, and assistance with crisis communication and problem-solving are all vital tasks that GenAI can help with. GenAI may support contingency planning by assisting with identifying, assessing, and mitigating risks, as well as the creation of risk reports and risk response strategies. GenAI can help develop procurement plans, requests for proposals (RFPs), supplier evaluation and selection, contract negotiation, and monitoring and control of the procurement process. Stakeholder analysis, register creation, communication plan building, engagement methods, dispute resolution, and stakeholder satisfaction evaluation can all be aided by GenAI.
Industry 4.0 undoubtedly has immense promise for the economy and society, but its implementation has also sparked worries about its potential adverse effects on both. The effect of Industry 4.0 on employment and jobs is a major source of anxiety. According to several authors
Erik Brynjolfsson and Andrew McAfee, Roger Strange and Antonella Zucchella, “Industry 4.0, Global Value Chains and International Business.” Bernhard Dachs, Steffen Kinkel, Angela Jäger, “Bringing it all back home? Backshoring of manufacturing activities and the adoption of Industry 4.0 technologies.”
The special issue advances our knowledge of Industry 4.0’s opportunities and constraints were compiled in five papers that were presented at the Transformative Technologies: The Impact of Industry 4.0 on Employment, Global Value Chains, and Sustainable Development event held in June 2019 at the Université Côte d’Azur. The three thematic areas covered in the workshop were (1) the impact of new automation technologies on jobs, employment, and earnings; (2) the transformation of logistics and the restructuring of value chains; and (3) the effects on environmental sustainability. The engineer will briefly explore the key issues and debates surrounding the deployment of Industry 4.0.
(1) The impact of new automation technologies on jobs, employment, and earnings; the European Manufacturing Survey (EMS)’s 2012 round, which included manufacturing sectors in Spain, France, Germany, Austria, Sweden, Switzerland, and the Netherlands, produced the most recent data. According to a regression study, the use of industrial robots by adopting businesses increases productivity while having no effect on the expansion of their workforce as measured over the two years that follow the adoption. The results indicate a positive relationship between business size, bigger batch sizes, and exporting as drivers of the decision to deploy robots. The relevance of economies of scale as a prerequisite for industrial robot investment is indicated by the positive relationship between batch size and adoption.
While studies of European countries have found that, after accounting for compensating effects, the overall impact of robots on employment is either neutral or positive, a significant study by Daron Acemoglu and Pascual Restrepo
Daron Acemoglu and Pascual Restrepo, “Robots and jobs: Evidence from US labor markets.”
(2) The transformation of logistics and the restructuring of value chains; while Industry 4.0 is undoubtedly bringing some businesses financial benefits, there are some hazards it poses to the operations of logistics organizations. Dmitry Ivanov et al.
Dmitry Ivanov, Alexandre Dolgui and Boris Sokolov, “The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics.” Oldřich Kodym, Lukáš Kubáč and Libor Kavka, “Risks associated with Logistics 4.0 and their minimisation using Blockchain.”
Figure. 2. illustrated the Main risks of Industry 4.0 to Individual Security.
Figure 2.
Main risk of 4IR to individual security (Source: Oldřich Kodym, Lukáš Kubáč and Libor Kavka)
Oldřich Kodym, Lukáš Kubáč and Libor Kavka, “Risks associated with Logistics 4.0 and their minimisation using Blockchain.”
The location of industrial activity and the global division of labor may change due to the deployment of Industry 4.0 technology for managing trade flows through global value chains. From the standpoint of developed countries, this locational impact has primarily been taken into account in terms of the expanded potential it gives for reshoring production to developed countries. Furthermore, there are worries that Chinese producers will not follow the prior pattern demonstrated by developed country multinationals of gradually offshoring the more labor-intensive parts of the production process to lower-wage economies because of the rapid adoption of robots and other advanced automation technologies in China, which has emerged from the 2000s as the world’s top producer of manufactured goods
Claire H. Hollweg, Global value chains and employment in developing economies.” In: Global Value Chain Development Report 2019, p. 74
(3) the effects on environmental sustainability; the circular economy concepts have the potential to be favored by Industry 4.0 disruptive technologies both at the firm and territorial levels (cleaner production and eco-design vs. industrial ecology and smart cities).
Higher value-added and more competitive products can also be produced using cleaner production techniques. A multi-method simulation-based tool, for instance, was developed by Asif et al. (2016)
Farazee M.A. Asif, Michael Lieder, Amir Rashid, “Multi-method simulation based tool to evaluate economic and environmental performance of circular product systems.”
The adoption of Industry 4.0 technologies at the scale of urban conurbations is directly linked to the creation of “smart cities” programs that aim to improve urban transportation and lessen their adverse environmental effects by conserving energy and water. For example, the Saudi Arabia Smart City NEOM: The New Smart City - The Land Of The Future
NEOM/ 2023. (n.d.). NEOM: Made to change. NEOM: Made to Change.
Industry 5.0 acknowledges the ability of the private sector to contribute to social objectives beyond employment and economic growth. It aims to transform the private sector into a resilient supplier of wealth by ensuring that production respects the limits of our planet and prioritizes the health and safety of industry workers. The shift to a sustainable, human-centered, and resilient European industry is driven by research and innovation, which complements the existing Industry 4.0 paradigm (Breque M, De Nul L, Petridis A. (2021.))
Maija Breque, Lars De Nul, Antanasios Petridis, Ray Y. Zhong, Xun Xu, Eberhard Klotz, Stephen T. Newman, “Intelligent manufacturing in the context of Industry 4.0: a review.”
Figure. 3. below illustrated the Industry 5.0 Main Pillars.
Figure 3.
Industry 5.0 Main Pillars.
The need for environmental sustainability pushed the envelope of the Industry 4.0-driven economy toward a more circular economy, which furnished the path for the Industry 5.0-driven economy that revisions how the economy achieves circularity to emerge.
Since releasing its first Circular Economy Action Plan (CEAP) in 2015, the European Union has been obsessed with the circular economy. That got strong momentum about the “circular economy” and, for some, incorporating it into their plans. It sparked certain modifications to the law’s standards, which immediately affected a wide range of electronic device categories.
The EcoDesign Framework Directive (EFD) regulations (also known as “implementing measures”) have changed as a result of CEAP. Beyond just energy efficiency, which had been the goal since 2005, their purviews were expanded. For instance:
An “eco program” is now required for household dishwashers. This operating mode must be identified as “eco” and adhere to specific functional and energy efficiency standards. It must be made the default setting. The product documentation, which must be available on a “free” website, must provide information about water use and energy efficiency in this mode and others. After the last unit of the product model is put on the market, spare components, including firmware and software, must be made available to “professional repairers” for a specific amount of time. Additionally, “repair and maintenance information” must be available to them. This requirement is present in most implementation measures; the specifics of the need depend on the product type. Enterprise-class server and data storage system manufacturers must disclose information regarding the weight range of cobalt in batteries and neodymium in hard drives. Halogenated flame retardants are not permitted in enclosures and stands for displays, monitors, and televisions.
Figure. 4. shown the Industry 5.0 Circular Economy.
Industry 5.0 recognized the following six enabling technologies:
Customized solutions for human-machine interaction that connect and combine the advantages of both types of systems. Adopting the Cobot synergistic way of working with humans and utilizing the Chatbot technology enables conversation between humans and the Cobots. Bio-inspired technologies and intelligent materials that enable recyclable materials with embedded sensors and improved functionalities. The use of simulation and digital twins to model entire systems. Technologies for data transmission, storage, and analysis that can manage data and system interoperability. Artificial intelligence that can be used to detect causalities, for instance, in dynamic, complicated systems. Energy-efficient, renewable, storage, and autonomous technologies.
As was mentioned before, Industry 5.0 is a value-driven project that promotes technological change for a specific goal rather than being a technology-driven revolution. (European Commission. (2020).)
European Commission. (2020).
Figure. 5. demonstrated the Industry 5.0 goals and the technological enablers.
Figure 4.
Industry 5.0 Circular Economy (Michael Kirschner)
Michael Kirschner, (2022, April 18). “A brave new circular world.”
GenAI creates legal concern because it seems to violate the copyright and proprietary information policies due to its capability of reviewing, accessing, and analyzing numerous and large amounts of data available on the cloud and processing them seamlessly through supercomputers without the requirement of consent nor authorization from the original creator(s) to generate meaningful information to the end user, human(s). While that is a great effort and phenomenal, it may most likely dissolve the genuineness of materials and copyrights.
The U.S. Copyright Office’s determination not to grant copyright protection to artificial intelligence (AI)-generated artwork that does not involve any human interaction was accepted by the U.S. District Court for the District of Columbia. A federal judge affirmed a ruling that copyright protection does not apply to works produced by artificial intelligence (AI)
Trishla Ostwal, “Judge rules GenAI content does not have copyright protection.”
Figure 5.
Industry 5.0 goals and the technological enablers. (Valeria Villani et al.)
Valeria Villani et al., “The INCLUSIVE System: A General Framework for Adaptive Industrial Automation.”
The decision could affect how much human engagement there is in the positions that AI is projected to take over. It establishes a precedent for content producers, agency executives, and others increasingly employing these tools. As a result of the GenAI boom, this decision represents the first legal boundary in the US for AI-generated artwork. The development of various GenAI tools, such as OpenAI’s ChatGPT, Midjourney, and Stable Diffusion, means that this decision may serve as a model for future legal disputes involving Intellectual Property (IP) when they relate to AI.
It is an interesting rule for marketers because it illustrates what can and cannot be copyrighted under the law for marketers increasingly investing in generative AI, particularly for content creation reasons, such as creating visuals for a campaign. Human inventiveness is still essential for such efforts to keep marketers out of legal challenges. Such employment that GenAI may otherwise replace could potentially be protected in this way.
Additionally, data privacy and security of proprietary information are fundamental to regular businesses in all industries and economies. Many companies have proprietary information and trade secrets that must be protected and kept confidential. With GenAI accessing clouds and servers across Industry 4.0 and 5.0, a concern is how GenAI distinguishes between confidential and proprietary information and what is not, and if GenAI does recognize that, will GenAI act in a meritorious and sincere manner?
Furthermore, in project management practice, the project manager and the project team are responsible for their decision-making, whether right or wrong, and accountability is defined through the project management plan and, project charter, stakeholder plan. When project managers initiate a new project, extensive documentation and materials are usually required, which are time-consuming tasks to read, analyze, and critically think of what it takes to prepare project documents. Nowadays, with GenAI’s presence and steadily getting into the project management domain, how would GanAI be held accountable for errors and omissions, misguided actions carried out by the project team as a result of an unintentional mistake? All these previous areas of concern for legal and judicial resolutions.
However, implementing a governance policy of tracking and auditing processes on GenAI decision-making would establish proper accountability and responsibility. Additionally, adopting a multi-layered strategy that involves extensive risk assessments, robust security implementation, ongoing monitoring, training, machine learning, and evaluation of GenAI outputs mitigates these issues. For example, companies such as IBM have developed their GenAI named “IBM watsonx,” which has 3 levels of layers that assist with security and validation, which are: a.) watsonx(.data); b) watsonx(.ai); and watsonx(.governance) that third layer is important on legal and security purposes. IBM encourages watsonx participants not to become AI Users but, instead, AI Value Creators; this way, the participant can control the AI access to data and choose from different libraries of tools and technologies, and most importantly, make AI abide by security measures
Dario Gil, IBM Research. (2023). Generative AI for business. YouTube.
Many people believe that GenAI and what Industry 4.0 and 5.0 are heading to is making our world prone to more vulnerability and insecurity, from denying Industry 5.0 existence under the current definition to losing jobs, affecting the value chain, legal copyrights, proprietary information breaches, and privacy and accountability compromises.
The supporting evidence for the counterclaims is explored in section 3.5 according to Paul Miller
Paul Miller,
The rebuttal for these counterclaims is as follows, as explored in subsection 3.3. the definition of the Techno-Social Revolution that was discussed by Dr. Xun Xu at the University of Auckland (2023) states that the technology of GenAI and robotics of Industry 4.0 complemented by the social capability of Industry 5.0 in a hybrid model, as shown in Figure. 6 below illustrated Fuzzy Set concept, a mapping of a set of real numbers ( Golovianko, M., Terziyan, V., Branytskyi, V., & Malyk, D. (2023). Industry 4.0 vs. Industry 5.0: Co-existence, transition, or a hybrid. Procedia Computer Science, 217, 102–113.
Figure 6.
Future smart factories a hybrid of industry 4.0 and industry 5.0 (Mariia Golovianko, Vagan Teziyan, Vladyslav Barnytskyi and Diana Malyk)
Furthermore, according to a study by Cézanne, Lorenz and Saglietto
Cézanne,
Lastly, subsection 3.5.4. GenAI, presented by IBM watsonx, has a hierarchical layer of protection by harnessing the emergence of the Foundation Model and GenAI with proper governance, generating immense opportunities for control of GenAI. IBM urges participants to become AI Value Creator and not AI User because the user is limited to just promoting others’ AI model, which is not owned by the user, and have no control over the model or the data; on the other hand, as an AI Value Creator, the participant will have multiple entry points that can bring Value Creator’s data, AI models to watsonx. A Value Creator can train, influence, prompt, protect, and govern their GenAI model. A Value Creator can also tune and have transparency and control over the governing data and their GenAI Model. This is evidence that companies can have venues to implement legal control and accountability over their GenAI and should be able to define their own Foundation Model and Large Language Model (LLM) privacy parameters.
The set forth rebuttal argument contains evidence that GenAI’s role in transforming Industry 4.0 into Industry 5.0 is not harming humanity, and the argument of making our world prone to more vulnerability and insecurity has no solid ground.
In the Engineers' opinion, we assertively believe that GenAI’s role in Project Management is vitally promising for a better and more effective project management workstyle. For example, when an engineer and marketing team prepare a response to a potential Request for Proposal (RFP), that process is cumbersome, depending on the RFP’s unique requirements, and requires a lot of reading and analysis to understand what the RFP wants, and first generate a soft decision of (GO) or (NO GO) based on the RFP language, and if the decision was (GO), then the second task will be to breakdown the RFP to small pieces and distribute responsibility among the project management team; all these steps are repetitive but rather crucial, therefore, have GenAI looking into these RFP first hand and train it to think as the engineer, and machine learn from specific company previous project data and tactics on responding to RFPs will go a long way of time-saving and also not going to replace neither the engineer nor the marketing team members. The professional experience support for using GenAI will save time preparing RFPs for potential projects and assist project managers in looking into what matters the most.
Furthermore, the legal concern of copyrights and proprietary information can be illuminated by harnessing the governance and value-creating approach to determine what to access and share and what not to access and share. It, for sure, will require comprehensive collaboration and elaboration in the way any organization can protect and train its foundation model and GenAI to abide by the legal rules and laws. For example, many people use flights to travel around the world. A long time ago, Autopilot broke through and was programmed to follow statutes and aviation regulations and has been used in many airline carriers. When an airline catastrophe crash occurs due to autopilot erroneously reversing the altitude, for example, Boeing 737 MAX (Ethiopian Airline crash 2019), governments first grounded the Boeing 737 MAX model. Then, governments drew a fine line for who would bear responsibility and accountability.
Lastly, GenAI will not wipe out all jobs and businesses but will transform how we can use and do things. By nature, the industry constantly evolves, ultimately making some tools and materials obsolete but not human. Humans are a Miraculous Machine creation that can adapt to change, be nimble, and have empathy that GenAI does not have. For example, in the construction industry, Cranes are ancient, lasting machines developed over time and modified to what we see nowadays. The Occupational Safety and Health Administration (OSHA) does not set maximum limits or standards for workplace lifting. Still, it does recommend that employers offer safe lifting training to employees(OSHA Section 5(a)(1) The Maximum Weight Person May Lift. (n.d.).)
OSHA Section 5(a)(1) The Maximum Weight Person May Lift. (n.d.). Occupational Safety and Health Administration.
This paper scholarly reviewed the role of Generative AI in managing industry projects (not ongoing routine activities), transforming the current Industry 4.0-driven economy into an Industry 5.0-driven economy, and worth saying that it is almost impossible to foresee all of GenAI’s role in transforming the Industry 4.0-driven economy into Industry 5.0-driven economy security ramifications because its complexity and multidimensionality. However, the world is currently undergoing a fast-paced industrial transformation into a GenAI and collaborative robot (Cobot), which is enabling the human workforce, enhancing project management procedures, and optimizing manufacturing and supply chain processes by utilizing supercomputers and Generative Artificial Intelligence (GenAI) capability. The use of GenAI is expanding and gaining popularity in many industries as well as in constant operations for organizations and individuals. The Fourth Industry Revolution (Industry 4.0), which was primarily driven by information technology (IT) and automation and focused on technical innovation, efficiency, profitability, and quality, left a gap for complementation by the Fifth Industry Revolution (Industry 5.0), which built on Industry 4.0’s accomplishments but gave a stronger emphasis to human resilience, environmental sustainability, and wellbeing. These modifications have an impact on society and the economy. Others are unintended and undesired, while some are desired and meant. Technology is at the heart of Industry 4.0, much like its predecessors. However, Industry 5.0 is value-driven. The former needs the latter to serve as a reminder of the primary society demands, values, and responsibilities and the driving force behind technological advancements. The current Industry 4.0 is complemented by Industry 5.0, which carries more societal responsibility for human-centric issues while preserving economic growth objectives, and the two together create what is known as the “Techno-Social Revolution.” Although GenAI has a beneficial role in project management and would greatly aid project managers, especially in massive data analysis, decision-making, and process automation, GenAI will likely face numerous legal challenges that would prevent its use. Accountability for mistakes and omissions, poorly thought-out acts taken, data privacy, and security of confidential information are a few of these. Implementing a governance strategy, however, would create sufficient accountability and responsibility by monitoring and evaluating the processes used to make GenAI decisions. A multi-layered approach that incorporates thorough risk analyses, robust security implementation, ongoing monitoring, training, machine learning, and evaluation of GenAI outputs also mitigates these problems. The legal issues will be reduced by close cooperation between value creators/project team members in establishing best practices and regulations for using GenAI. Finally, selecting suitable legal terms and conditions depends on being forthright and upfront with stakeholders about using GenAI and the security and privacy measures taken.