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

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:

Compliance and Regulatory Risks:

Operational Risks:

2. APPLICABLE REGULATORY FRAMEWORK

Applicable European and Italian Regulations

AI Act (EU Regulation 2024/1689):

GDPR (EU Regulation 2016/679):

ISO/IEC certifications in progress:

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

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:

PROHIBITED TOOLS

Unauthorized Consumer Tools:

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

3.4 DATA CLASSIFICATION AND MANAGEMENT

LevelDescriptionPermitted AI Use
PublicData already public or intended for publicationAny tool (with caution)
InternalNon-sensitive information for internal usePreferred corporate platform
ConfidentialCommercial, financial, strategic dataONLY corporate platform
SecretIP, patents, personal data, critical informationONLY on-premise/private platform

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):

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

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

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:

3.8 HUMAN OVERSIGHT

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

RiskUse Case ExamplesOversight
LowDocumentation research, email draftsUser review
MediumQuotes, customer responsesApproval workflow
HighHR decisions, financial analysisCo-creation
CriticalMedical decisions, safetyHuman veto

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:

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:

Practical Example

On-Premise Investment: €150,000

With 180% Hyper-depreciation:

Validity: January 1, 2026 → September 30, 2028

7. IMPLEMENTATION CHECKLIST

Governance and Organization

Regulatory and Compliance

Tools and Technology

Training

Operations

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

Confindustria Support

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

Available Services:

📞 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

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.