Challenges of the Fourth Industrial Revolution(4IR)
Challenges of the Fourth Industrial Revolution(4IR) On International Contracts and Transactions in the Industrial Sector: A Detailed Analytical Reading of Their Legal Implications for Sustainable Development
Since the 18th century, the world has witnessed numerous qualitative industrial shifts, from the steam engine to artificial intelligence, accompanied by many global challenges that underscore the importance of a coordinated international response. In this context, the United Nations launchedThe Global Digital Compact is a strategic initiative aimed at establishing a shared legal and ethical framework to regulate the digital space and ensure the responsible use of emerging technologies, particularly artificial intelligence. This compact responds to growing legislative gaps, increasing risks related to privacy and algorithmic discrimination, challenges to transparency and accountability, and the urgent need to promote digital justice and protect human rights in the digital environment.
Based on the role of International CompanytoAdvisors Consulting, and in line with our participation in the Global Industry Summit 2025, we will review with you in this article the most prominent legal challenges and present our recommendations regarding each challenge individually, as detailed below:
A historical overview of the qualitative shifts in the industrial sector globally:
| Industrial Revolution | Approximate timeframe | Dominant Technology / Principle | direct legal reflection |
|---|---|---|---|
| First(1IR) | 1760 – 1840 AD | Steam and mechanization. | Establishing labor laws(Labour Laws) to protect workers and regulate the factory environment. |
| Second(2IR) | 1870 – 1914 AD | Electricity and mass production. | The emergence of antitrust laws(Antitrust) to regulate cross-border companies and product safety laws. |
| Third(3IR) | 1950 – 2000 AD | Electronics and Digital Automation. | The emergence of e-commerce laws, software protection (as part of intellectual property), and initial privacy legislation. |
| Fourth(4IR) | 2010 AD – Present | Cyber-physical systems and autonomy(AI/IoT). | The need to redefine responsibility, intellectual property rights for AI-generated content, and to standardize data governance.. |
Key legal challenges of the Fourth Industrial Revolution:
Determining legal responsibility in autonomous systems is one of the most significant challenges facing modern legislation. It is difficult to identify who is liable for damages resulting from AI decisions, especially in complex or collaborative systems where multiple roles overlap between developers, users, and the systems themselves. This complexity necessitates the development of new legal frameworks that accommodate the nature of these systems and clearly define responsibilities.
Conversely, privacy protection emerges as a pivotal issue in the context of cross-border data flows, where data protection standards vary from country to country, making it difficult to monitor data movement in an open and transnational digital environment. Furthermore, algorithmic biases present both ethical and technical challenges, requiring the development of effective mechanisms for monitoring and correcting them to ensure fairness and non-discrimination in the outcomes of intelligent systems.
On the regulatory level, achieving transparency in complex systems, such as those based on deep neural networks, remains extremely difficult, limiting individuals’ ability to understand decisions that affect their lives. Added to this is the challenge of harmonizing legal standards globally, given the diversity of national legislation and the difficulty of aligning it with international standards, particularly in developing countries or those lacking advanced legal frameworks.
Intellectual property also presents an increasing challenge in the artificial intelligence environment, where it is difficult to determine the rights associated with the outputs produced by intelligent systems, especially when these outputs are creative, artistic, or literary in nature. The question of who owns the copyright—the developer, the user, or the system itself—remains a subject of legal and ethical debate. Furthermore, the use of copyrighted data to train models raises issues related to permission, fair transfer, and compensation, necessitating the development of new legal frameworks that balance innovation with the protection of original rights..
Legal recommendations proposed for the Fourth Industrial Revolution:
Firstly – Undoubtedly, the most prominent applications of artificial intelligence are inextricably linked to literary, industrial, and artistic productions. Given that the current approach of intellectual property offices across various jurisdictions is to issue guidelines, and the absence of binding legal texts that can regulate these outputs, including the associated rights and obligations, we recommend…Data use governance inInternational ContractsRelated to artificial intelligence through definitiondata layer ownershipLimits of its use (Data Layers): (1) Training Data, (2) The Algorithm Itself, and (3) The Final AI Output. Failure to include such contractual clauses can lead to serious disputes regarding profit distribution and compensation in cases of shared intellectual property rights.
Secondly – with regard toLiability and compensation determination in autonomous systems (Product Liability: We see the necessity of distinguishing between causing harm and directly causing harm. The direct perpetrator is the person who performs the act leading to the harm without an intermediary, such as someone breaking a window with their hand or killing someone with a weapon. The indirect perpetrator, on the other hand, is the one who creates the cause without directly performing the act. We note that artificial intelligence is based on the principle of training data and processing algorithms, and here liability revolves around the presence or absence of the strongest influence. Therefore, we recommend adopting a Layered Liability Framework that takes into account the varying roles, risks, and benefits within the AI system. This framework would distribute legal responsibility fairly and realistically among the stakeholders—developers, data providers, operators, and end users. It is based on the principle of proportionality between the degree of control over the system and the expected gains from its use, versus the level of potential risks to individuals and society. The greater a party’s ability to influence the design or operation of the system, or the more financially they benefit from it, the greater their legal liability for the resulting harm. This flexible model allows for addressing accountability gaps, particularly in collaborative or multilateral systems, and fosters a climate of proactive compliance and responsible innovation.
Third – Given the increasing challenges posed by the contemporary digital environment, the issue of industrial data governance and its cross-border transfer stands out.Data governance is a fundamental pillar for ensuring digital sovereignty and protecting national interests. In this context, we commend the approach adopted by some jurisdictions worldwide, which involves enacting strict legislation to regulate access to data and restrict its transfer across borders, thus achieving a balance between digital openness and the protection of cybersecurity and privacy. From this perspective, we applaud the pioneering efforts of the government of the Kingdom of Saudi Arabia, represented by the Saudi Data & Artificial Intelligence Authority (SDAIA), which has established a robust framework for national data governance. We also acknowledge the growing role of the Digital Government Authority in regulating the artificial intelligence sector, ensuring its compliance with the highest ethical and technical standards, and enhancing the Kingdom’s position as a leading regional hub for the digital economy and sustainable technological transformation.
