Strengthening AI governance and EU AI Act compliance through a structured enterprise framework

How a global manufacturing company established AI governance, system monitoring, and regulatory readiness to support the responsible and compliant adoption of artificial intelligence across its global operations.

SECTOR: Manufacturing | COMPETENCIES: Data Platform, Cloud Architecture, Data Governance

Strengthening AI governance and EU AI Act compliance

CONTACTS

Carmine Di Menna
Director Italia Data & AI Governance @BIP xTech

Marina Tenconi
Data & AI Governance Lead @BIP xTech

CHALLENGE

AI Governance Challenge

As artificial intelligence adoption accelerated across its global operations, a leading manufacturing company needed a structured approach to align AI initiatives with the requirements of the EU AI Act. The organization faced the challenge of identifying and classifying AI systems already in use, assessing potential regulatory risks, and establishing governance mechanisms capable of supporting future AI development. In a highly regulated industrial environment, ensuring transparency, accountability, and compliance became essential to mitigate risk, support innovation, and prepare the organization for upcoming regulatory deadlines.

OUR SOLUTION

Structured AI Governance Framework

BIP xTech supported the organization in designing and implementing a comprehensive AI Governance Framework aligned with EU AI Act requirements. The initiative began with the creation of an AI System Register structured across Business, Technical, and Risk dimensions, enabling the collection and classification of key information for each AI system. A dedicated risk assessment checklist was introduced to identify AI Act risk categories and support compliance activities.

To strengthen monitoring capabilities, an AI System List was developed to provide a centralized inventory of AI solutions deployed across regions and to identify systems potentially falling into prohibited or unacceptable-risk categories. The project also included the definition of an AI Policy establishing principles for ethical, responsible, and transparent AI usage.

Governance capabilities were further reinforced through the implementation of operating models, decision-making processes, roles and responsibilities, and monitoring activities covering the entire AI lifecycle. Finally, targeted AI Awareness sessions increased organizational understanding of regulatory obligations, risk classifications, compliance milestones, and governance responsibilities.

RESULTS

Governance and Compliance Outcomes

The initiative enabled the organization to establish a centralized inventory of AI systems and a standardized methodology for AI classification and risk assessment. Governance processes were formalized across business, technical, and compliance functions, improving visibility and accountability throughout the AI lifecycle.

Key outcomes included:

100% visibility of mapped AI systems within the governance perimeter.
Standardized AI risk classification aligned with EU AI Act requirements.
Formalized AI governance processes, roles, and responsibilities.
Enhanced organizational awareness of AI regulatory obligations and compliance deadlines.
Improved readiness to identify and phase out non-compliant AI systems.

BENEFITS

Readiness

Traceability

Risk Reduction

Scalability

Conclusion

Through a structured governance and compliance program, the industrial enterprise transformed its approach to AI management, creating the foundations for responsible and transparent AI adoption. By combining system inventory, risk classification, governance processes, policy definition, and awareness initiatives, the organization strengthened its regulatory readiness while enabling sustainable AI innovation aligned with business objectives and evolving European regulations.