The technological revolution is advancing at an unprecedented pace, and while innovation has been constant, the real turning point came in 2023 with the emergence of ChatGPT-4. Although artificial intelligence (AI) already existed, its mass adoption democratized access and transformed daily life, business management, and institutional functioning. The 2020s marked the transition from experimentation to the consolidation of generative AI as essential infrastructure, reconfiguring how companies report and interact with customers, partners, and investors. Corporate information—financial, legal, non-financial, and sustainability—has ceased to be a retrospective exercise and has become a dynamic, predictive, and automated flow driven by AI. However, this advancement poses social, legal, and ethical challenges. The entry into force of the EU AI Act in August 2026, along with the Corporate Sustainability Reporting Directive (CSRD), has created a highly demanding environment for executives and legal officers, who must adapt to an unprecedented regulatory framework. The implementation of these regulations has generated uncertainty among companies using AI in their internal processes or in interactions with third parties. Although the AI Regulation was approved in 2024, its real impact will be felt in August 2026, especially due to the regulation of high-risk systems and the demand for radical transparency. The AI Regulation introduces a new regulatory paradigm, redefining the relationship between companies and their stakeholders under the so-called "new hygiene of transparency." Article 50 establishes the obligation to inform users about any AI-mediated interaction, particularly affecting corporate communication and the use of Large Language Models (LLMs) in customer and investor service. Article 50 becomes the central axis of the regulation, imposing on companies the duty to ensure that anyone knows if they are interacting with an automated system. This principle translates into three key areas: - Labeling of synthetic content: AI-generated images, audio, or videos must be clearly identified, helping to combat misinformation and deepfakes. - Protection of biometric and emotional data: The regulation requires total transparency in the use of systems that infer emotions, especially in selection processes, to avoid biases and protect candidates. - Customer service interfaces: The warning about the use of AI must be constant and explicit, ensuring that users are always informed. Transparency becomes essential in light of the rise of synthetic content and emotion detection. The financial sector, aware of the value of truthfulness, must prepare to manage reputational crises arising from misinformation and pay special attention to technologies that infer emotional or biometric states. The new regulatory framework for high-risk AI introduces the principle of proactive responsibility: companies must self-assess the compliance of their systems, document thoroughly, and ensure effective human oversight. This autonomy is complemented by state oversight, as authorities can audit systems at any time, forcing organizations to maintain total traceability and fostering the emergence of specialized compliance consulting firms. Regarding civil liability, the lack of a harmonized European directive creates legal uncertainty. The Product Liability Directive (PLD) classifies software as a product, establishing strict liability for damages caused by algorithmic failures, but regulatory fragmentation among countries complicates uniform risk management and favors inequalities in access to technology. The financial function is also undergoing a radical transformation. Cognitive automation allows for nearly continuous accounting closures, and generative AI facilitates the drafting of reports and the integration of structured and unstructured data. Examples like Siemens, which has optimized global financial management through AI, illustrate the leap towards Finance-as-a-Service models and the reduction of manual burdens. Predictive analysis, in turn, has improved liquidity management and cash flow forecasting, allowing for the anticipation of financial tensions and reducing dependence on external financing. Real-time monitoring and AI's ability to identify anomalies have revolutionized auditing and tax management, where automation and prediction are consolidating as key tools. The CSRD has elevated non-financial transparency to the level of accounting, requiring thousands of companies to report under ESRS standards. Manual data collection is unfeasible given the complexity and volume of information, making advanced digitalization and AI indispensable allies to comply with regulations and avoid penalties. Generative AI allows for connecting unstructured documents with regulatory frameworks, facilitating the extraction of metrics and access to real-time data, as demonstrated by Unilever. However, the use of AI can also increase the risk of greenwashing, prompting investors and NGOs to employ automated audits to contrast corporate information with external data, raising the reputational cost of any inconsistency. The phenomenon of Shadow AI—the use of unauthorized tools by employees—represents a governance risk that companies cannot ignore. Lack of control over AI use can lead to information leaks and legal vulnerability. The new regulation demands real and proactive oversight, and insurers are already adjusting their policies to exclude claims arising from AI if adequate monitoring is not in place. In summary, AI redefines business management, transparency, and responsibility, requiring organizations to undergo profound adaptations in their processes, controls, and corporate culture to face the regulatory, ethical, and operational challenges of the new digital environment.