The year 2024 marks an operational shift for companies integrating artificial intelligence into their processes. The focus is no longer on adoption, but on regulatory compliance and restructuring internal skills around these tools.
AI Act and regulatory compliance: the game-changing framework for businesses
The European regulation on artificial intelligence (AI Act) came into effect on August 1, 2024. Its implementation is gradual and relies on a classification of AI systems by risk level. Companies deploying high-risk AI tools (credit scoring, application sorting, assisted medical diagnosis) must now document their models, ensure the traceability of training data, and establish human oversight.
This timeline also includes measures on prohibited AI practices, such as social scoring or subliminal manipulation. Legal departments and IT directors must collaboratively map internal uses to identify those falling into high-risk categories.
The skills dimension is often underestimated. The regulation requires a mastery of AI by the individuals using it, transforming internal training into a regulatory obligation. Training an operator to use a tool is no longer sufficient: it must be proven that they understand the model’s limitations and potential biases. We observe that companies that have anticipated this governance aspect gain several months on their compliance timeline.
Sectoral monitoring published on the Journal des Professionels allows tracking the evolution of these obligations by sector as the implementing texts become clearer.
CSRD sustainability reporting: a data project, not just environmental
The CSRD directive requires affected companies to produce their first sustainability reports for the 2024 fiscal year. A quick reading of the text suggests an environmental exercise. The reality is different: it is a cross-cutting data structuring project.
The CSRD introduces the principle of double materiality. The company must simultaneously examine its impacts on sustainability issues (climate, biodiversity, working conditions) and the effects of these issues on its financial situation. This dual perspective requires cross-referencing indicators that until now belonged to distinct services: finance, CSR, HR, procurement.
The relevant teams must collect qualitative and quantitative information that exceeds the traditional financial perimeter. Three axes structure this work:
- The mapping of material impacts across the entire value chain, including second and third-tier suppliers
- The alignment of extra-financial indicators with ESRS (European Sustainability Reporting Standards), which impose a specific format and granularity
- The integration of this data into the management report, rather than in a separate document, which modifies the audit process
For SMEs and mid-sized enterprises, the challenge is not so much data collection as the lack of suitable internal tools. Standard ERPs do not natively manage ESRS indicators, leading to specific developments or the adoption of dedicated platforms.
Digital transformation of small and medium enterprises: real maturity and blind spots
Cybersecurity remains a constant concern, but protective investments do not keep pace with the threat curve. Small enterprises remain vulnerable to ransomware attacks and targeted phishing, lacking backup policies and regular team awareness training.
Artificial intelligence appears in intentions, but its actual adoption by small structures remains marginal. The barrier is not the cost of tools (many are accessible via SaaS), but the lack of internal skills to configure and utilize these solutions. A poorly configured chatbot degrades the customer experience instead of improving it.
Sectors where digital maturity is progressing the fastest
Retail and hospitality are accelerating in online ordering and real-time inventory management. Construction professions are adopting BIM (Building Information Modeling) under pressure from public markets. Professional services, on the other hand, lag behind in the dematerialization of customer journeys.
Data governance and security: the technical foundation of all innovations
Every trend of 2024, whether it involves generative AI, CSRD reporting, or digital transformation, relies on a common prerequisite: data quality and governance. Without a reliable data catalog, an AI model produces erroneous results. Without traceability, a CSRD report fails the audit.
Companies that derive the most value from these innovations are those that have invested in a structured data architecture before deploying tools. This requires an identified data owner by business domain, automated quality rules, and a shared reference framework between technical teams and operational management.
Continuous Threat Exposure Management (CTEM) is gaining traction as a cybersecurity approach. Instead of conducting one-off audits, it maintains a permanent assessment of attack surfaces. This method complements traditional tools (firewalls, EDR) by identifying vulnerabilities before they can be exploited.
- Automated inventory of exposed assets (APIs, misconfigured subdomains, cloud services)
- Regular attack simulations to prioritize fixes based on their actual exploitability
- Integration of results into management dashboards, accessible to executive committees and not just IT teams
The innovations of 2024 share a common trait: they shift added value from tools to the processes and skills surrounding them. The competitive advantage is built on governance, not on adoption. Companies that structure their regulatory compliance, data management, and skills development of their teams gain a sustainable lead over those that pile up technological solutions without a framework.
