PRACTICAL GUIDE: How to Build a Corporate Policy for AI Governance and Management

PREMISE

The adoption of artificial intelligence in a company represents a strategic opportunity, but it requires a structured approach to ensure security, regulatory compliance, and maximization of benefits. This document provides practical guidelines for building an effective corporate policy on AI governance.

1. WHY A CORPORATE AI POLICY IS NEEDED

The Problem: Shadow AI

The "Shadow AI" phenomenon occurs when employees use unauthorized artificial intelligence tools (such as public ChatGPT, Claude, Gemini) without the approval or knowledge of the IT department or management.

Significant data:

17% of large companies have banned unapproved AI tools 77% of companies fear AI hallucinations 74% are unable to scale AI value 0% traceability of uncontrolled AI decisions

Concrete Risks of Shadow AI

Privacy and Security Risks:

• Sensitive company data shared with external providers
• No control over where data goes and how it is used
• Possible use of data for training third-party models
• Violation of corporate data protection policies

Compliance and Regulatory Risks:

• GDPR violation due to improper handling of personal data
• Non-compliance with the European AI Act (in force since February 2, 2025)
• Lack of mandatory human oversight
• Significant legal risks and penalties of up to 6% of global turnover

Operational Risks:

• IT has no visibility into which AI tools are being used
• No traceability of decisions made
• No control over the quality of responses
• Impossibility of conducting audits
• Hidden and uncontrolled costs

2. APPLICABLE REGULATORY FRAMEWORK

Applicable European and Italian Regulations

AI Act (EU Regulation 2024/1689):

• Mandatory training of personnel (from February 2, 2025)
• Classification of AI systems by risk level
• Mandatory human oversight for high-risk AI
• Complete documentation and traceability
• Conformity assessment for critical systems

GDPR (EU Regulation 2016/679):

• Data minimization and privacy by design
• Right to be forgotten and data portability
• Data Protection Impact Assessment (DPIA) for AI
• Informed consent for personal data processing
• Data residency in Europe

ISO/IEC certifications in progress:

• ISO 42001 - AI Management System
• ISO 27001 - Information Security
• ISO 9001 - Quality Management

3. STRUCTURE OF THE CORPORATE AI POLICY

3.1 GENERAL PRINCIPLES

Human-centricity:

AI assists people, it does not replace them. Final control always remains human. Focus on augmented intelligence, not total automation.

Transparency:

Every use of AI must be declared and traceable. Clear documentation of how AI systems work. Transparent communication to stakeholders.

Privacy by Design:

Data protection from the design stage. Minimization of data collection. End-to-end encryption and security.

Human Oversight:

Human control at every critical stage. Ability to override AI decisions. Validation of outputs before use in production.

Regulatory Compliance:

Full compliance with GDPR, the AI Act, and sector-specific regulations. Continuous updates as legislation evolves. Periodic compliance audits.

3.2 ORGANIZATIONAL GOVERNANCE

Structure of the AI Committee

Establish an AI Governance Committee composed of:

1. AI Officer / Chief AI Officer - Strategic lead for AI implementation
2. IT/CTO - Infrastructure management and technical security
3. Legal/Compliance - Regulatory compliance and legal risks
4. HR - Training and change management
5. Business Units Representatives - Representatives from various departments
6. Data Protection Officer (DPO) - Privacy and GDPR compliance

Responsibilities and Duties

• Definition of the corporate AI strategy
• Approval of use cases and pilot projects
• Monitoring KPIs and performance
• Budget and priority management
• Periodic reviews (monthly/quarterly)
• Management of AI-related incidents

3.3 AUTHORIZED AND PROHIBITED TOOLS

APPROVED TOOLS

Centralized Corporate Platform:

Define a single authorized platform for the use of AI within the company.

Characteristics of the approved platform:

• Centralized access management
• Complete traceability of interactions
• Integrated human oversight
• Multi-LLM (no vendor lock-in)
• Flexible deployment (Cloud, Private Cloud, On-Premise)
• Guaranteed GDPR and AI Act compliance

PROHIBITED TOOLS

Unauthorized Consumer Tools:

• Public ChatGPT, Claude, Gemini for sensitive corporate data
• Any AI not approved by IT
• Services that do not guarantee zero data retention
• Providers that do not respect European data residency

Basic rule: Data classified as Confidential or Secret may be used ONLY on the approved corporate platform.

3.4 DATA CLASSIFICATION AND MANAGEMENT

AI Data Governance Rules

1. Data Minimization: Share only strictly necessary data
2. Data Residency: Preference for solutions with data hosted in Europe
3. Zero Data Retention: Providers must not retain data
4. Audit Trail: Complete log of who accesses which data
5. Right to be Forgotten: Ability to delete data upon request

3.5 MANDATORY TRAINING

Training Paths by Level

General Awareness (Whole company - 2 hours):

• What generative AI is and how it works
• Opportunities and risks
• Corporate policy and authorized tools
• Practical examples and use cases

AI Academy Basic (Managers and Power Users - 4/5 days):

• Fundamentals of Generative AI and Large Language Models
• Creation and management of AI Agents
• Effective prompt engineering
• Integration into corporate workflows
• AI Act and GDPR compliance

Advanced Training (IT and Developers - 3-5 days):

• Enterprise integrations (CRM, ERP, API)
• Secure authentication (SSO, OAuth, JWT)
• MCP Server and advanced functions
• Security best practices and deployment
• Monitoring and troubleshooting

Important note: As of February 2, 2025, the AI Act makes training mandatory for personnel using AI systems.

3.6 ACCESS CONTROL AND PERMISSIONS

RBAC Model (Role-Based Access Control)

Access Levels:

1. Viewer - Only consultation of public agents
2. User - Use of agents authorized for their role
3. Creator - Creation and modification of agents for their team
4. Admin - Full management of agents and users in the department
5. Super Admin - Total platform control (IT/AI Officer)

3.7 TRACEABILITY AND AUDIT

Mandatory Logging

Every interaction with AI must be tracked:

• Timestamp of the interaction
• User who made the query
• AI agent used
• Input provided and output generated
• Any manual modifications
• Human oversight applied

3.8 HUMAN OVERSIGHT

Basic Principle: No critical decision can be made exclusively by AI without human validation.

4. AI ADOPTION PATH IN 4 PHASES

PHASE 1: TRAINING (1-2 months)

Objective: Make the team autonomous and aware

Deliverable: Trained team, approved policy, first AI agents created

PHASE 2: CLOUD PoC (2-3 months)

Objective: Validate the value of AI with real cases

Use Case: Knowledge Management, Customer Support, Onboarding, Sales

Deliverable: Documented ROI, feasibility report

PHASE 3: MODEL STUDY (1 month)

Objective: Define final deployment strategy

Analysis: Workload, TCO, Compliance, Vendor Selection

PHASE 4: PRODUCTION (gradual scaling)

Objective: Bring AI to enterprise scale

Options: On-Premise (enterprise) or Private Cloud

On-Premise Advantages: Full control, maximum privacy, 180% Hyper-depreciation

5. AI GOVERNANCE PLATFORM

Essential Features

Centralized Control

RBAC with granular permissions, SSO user management, team segmentation, instant access revocation

Total Traceability

Complete audit log of conversations, decision tracking, agent history, export for compliance

Flexible Multi-LLM

Zero vendor lock-in, support for GPT-4/Claude/Mistral/Gemini, local models, cost optimization

Automatic Compliance

AI Act and GDPR compliant, EU data residency, zero data retention, ISO certifications

The Solution: AIsuru by Memori.ai

AIsuru is the Italian platform that meets every corporate AI governance need.

Key advantages:

• Full IT control: Centralized dashboard, total visibility
• Flexible deployment: SaaS, PaaS, Private Cloud, On-Premise
• Guaranteed compliance: Italian, GDPR and AI Act compliant
• Certified training: AIsuru AI Academy with TD SYNNEX
• Multi-LLM: No lock-in, instant provider switching
• Integration-ready: MCP Server, REST API, CRM/ERP

6. INVESTMENT AND TAX OPPORTUNITIES

2026 Hyper-depreciation (Law 199/2025)

Exceptional Opportunity

Hyper-depreciation allows you to increase by 180% the tax-deductible cost of the investment for goods compliant with Industry 4.0.

Applicable Annexes:

• Annex IV (Hardware): AI servers, GPUs, edge computing, storage
• Annex V (Software): AI platforms, LLMs, Agentic AI software

Practical Example

On-Premise Investment: €150,000

• Hardware (Annex IV): €100,000
• AIsuru Software (Annex V): €50,000

With 180% Hyper-depreciation:

• Higher tax deduction: €150,000 × 1.8 = €270,000
• Tax savings (IRES 24%): €270,000 × 24% = €64,800
• Actual net cost: €85,200 (€150,000 - €64,800)

Validity: January 1, 2026 → September 30, 2028

7. IMPLEMENTATION CHECKLIST

Governance and Organization

• AI Governance Committee established
• Corporate AI Officer appointed
• AI policy written and approved
• Policy communicated to the whole company

Regulatory and Compliance

• GDPR and AI Act compliance assessed
• DPIA completed
• Supplier contracts verified
• External audits scheduled

Tools and Technology

• Centralized AI platform selected
• Deployment decision made (Cloud/Private/On-Premise)
• SSO/Active Directory integration
• Active monitoring and alerting

Training

• Training plan defined
• General awareness delivered
• AI Academy completed
• Certifications issued

Operations

• Pilot use cases identified
• First AI agents created
• KPIs and dashboard configured
• Incident management procedure active

8. CONCLUSIONS AND NEXT STEPS

Why Act Now

1. Regulatory Obligation: AI Act requires training since February 2, 2025
2. Competitive Advantage: Companies with governed AI win
3. Tax Opportunity: 180% Hyper-depreciation until September 2028
4. Shadow AI Risk: Without governance, the company is exposed
5. Market Pressure: Customers demand guarantees on AI use

Final Recommendations

• Do NOT improvise: AI without governance is a risk
• Start with training: The foundation for any success
• Choose compliant platforms: Avoid consumer tools
• Think scalable: PoC with a production vision
• Document everything: Traceability is fundamental

Confindustria Support

Memori.ai has signed an agreement with Confindustria Emilia Centro to support member companies.

Available Services:

• Consulting for building an AI policy
• Free process assessment
• Certified training via AIsuru AI Academy
• Subsidized PoCs to validate ROI
• Support for the 2026 Hyper-depreciation
• On-premise deployment with certified partners

📞 CONTACTS AND RESOURCES

For further information and support:

Memori srl

Email: demo@memori.ai

Phone: (+39) 051 19470234

Website: www.memori.ai

Training

AIsuru AI Academy:
www.memori.ai/it/ai-academy

Course registration:
academy.tdsynnex.com

Documentation:
docs.aisuru.com

Partnerships

• TD SYNNEX - Distribution and training
• Lenovo + NVIDIA - On-premise hardware
• Confindustria Emilia Centro - Agreement for member companies

Document by Memori srl

January 2026 - Version 1.0

This document is provided for informational purposes. For advice specific to your company's situation, contact Memori's experts or your trusted legal/tax advisor.