AI Governance

Steering artificial intelligence responsibly

Generative AI, intelligent assistance systems and automated decisions open up new possibilities for companies. At the same time, they create risks for information security, data protection, compliance, business processes, reputation and the people affected.

PHO-Consulting helps companies establish clear responsibilities, structured risk controls and ethically sound AI architectures — so that AI systems can be introduced in a controlled way, regulatory requirements are taken into account, and innovative uses are sustainably embedded in the organisation.

Why AI governance?

The use of artificial intelligence raises new questions: Which AI systems are used in the company? For which business processes are they used? What data and information do they process? What risks arise for people, companies and society? Who decides on development, procurement and approval? How are results checked and documented in a traceable way? How is compliance with internal and regulatory requirements ensured?

The EU AI Act distinguishes AI systems by different risk levels — higher risks come with stricter requirements. Effective AI governance creates the organisational framework to answer these questions in a structured way, and enables transparency over the AI systems in use, clear roles, risk-based assessment of use cases, traceable approval processes, consideration of regulatory and ethical requirements, safe use of generative methods, and continuous monitoring.

Our service portfolio

AI governance strategy
Effective AI governance begins with a clear target picture. Together with the company, PHO-Consulting develops a governance approach that fits the business strategy, risk landscape, organisational structure and technological direction.

• Development of an AI governance strategy
• Definition of guidelines, target pictures and governance principles
• Building decision-making and control structures
• Integration into existing management systems
• Development of a step-by-step implementation roadmap

Roles and responsibilities
The controlled use of AI requires clearly defined responsibilities: AI governance leads, decision-making and approval bodies, responsibilities for AI use cases, roles of business units, IT, data protection and information security, control and monitoring functions, and escalation and reporting lines — including along external supply chains.

AI inventory and use case management
Companies need transparency about where and how artificial intelligence is used: recording existing and planned AI systems, structuring use cases, documenting purpose, data, models and dependencies, assessing external AI services, building a central AI register and an end-to-end use case lifecycle.

AI risk management
The EU AI Act aims to promote trustworthy, safe and human-centric AI while protecting health, safety and fundamental rights. Our services: development of an AI risk model, classification of use cases, assessment of business, ethical and technical risks, analysis of data protection and security risks, definition of risk treatment measures and regular risk reviews.

Typical risk areas: unsuitable or incorrect results, bias and discrimination, lack of transparency, loss of confidential information, manipulation of models or input data, insufficient human oversight, dependence on external providers, reputational and liability risks.

Regulation and compliance
PHO-Consulting helps companies translate regulatory requirements into workable governance structures and controls — topics covered: EU AI Act, data protection and GDPR, information security, NIS2 and DORA (where relevant), sector-specific requirements, and internal and contractual obligations. Depending on role, AI system and risk category, the AI Regulation imposes different obligations, in particular on providers and deployers. Services: regulatory gap analyses, mapping of relevant requirements, development of a control framework, building evidence structures, preparing internal audits and integration into existing compliance processes.

Policies and control frameworks
Among other things, PHO-Consulting develops AI governance policies, rules for generative AI, approval processes for AI use cases, policies for data and model use, requirements for human oversight, documentation and evidence requirements, and reporting and escalation processes — designed to support security and compliance without blocking innovation through unnecessary bureaucracy.

Ethical and responsible AI
Core principles: human responsibility, fairness and non-discrimination, transparency and explainability, data protection and information security, robustness and reliability, traceability of decisions, clear purpose limitation, and controlled, appropriate use.

AI architecture and security by design
Governance must be anchored in the technical and organisational architecture: AI target architectures, integration into Enterprise Architecture Management, secure data and information flows, role and authorisation concepts, logging and traceability, separation of sensitive data and areas of application, human control points, and emergency, recovery and shutdown mechanisms.

Provider and supplier management
Many AI solutions are based on external platforms, models, cloud services or data sources. We provide support with risk assessments of AI providers, security and compliance requirements, review of roles, assessment of data processing and locations, contractual control requirements, exit strategies and monitoring of critical service providers.

Monitoring and management reporting
AI governance does not end with the approval of a system: development of suitable indicators, building control and reporting processes, monitoring of risks and measures, status reports for management and governance bodies, and regular review of use cases.

AI awareness and change enablement
AI governance only becomes effective when employees understand the rules and can apply them in their daily work: awareness concepts, training for management and executives, role-specific training, workshops for business units and support for organisational change.

Our process model

1. Create transparency — record AI systems, use cases, data, providers and responsibilities.
2. Determine requirements — map regulatory, business, ethical and security-related requirements.
3. Assess risks — classify use cases and assess risks in a traceable way.
4. Design governance — define roles, bodies, policies, controls and decision paths.
5. Embed implementation — integrate governance into processes, architectures, projects and procurement.
6. Monitor effectiveness — establish indicators, reviews, audits and continuous improvement.

Typical results

• AI governance target picture & AI policy
• Role and responsibility model
• AI inventory and use case register
• Risk classification model, assessment and approval procedures
• Control catalogue and documentation concept
• Provider requirements, management reporting
• Awareness and training concept, implementation roadmap

Why PHO-Consulting?

PHO-Consulting combines strategic, organisational and technical perspectives into a holistic AI governance approach.

• Practice-oriented governance instead of isolated individual measures
• Linking AI, EAM, ISMS, BCM and operational resilience
• Risk-based approach tailored to the organisation
• Clear roles, responsibilities and decision paths
• Integration into existing management systems
• Vendor- and technology-independent consulting
• Support from strategy and design through to sustainable implementation

Your benefits

More transparency
A clear overview of AI applications, data, models, providers and dependencies.

Controlled risks
Systematic identification, assessment and treatment of relevant AI risks.

Regulatory certainty
Structured implementation of relevant legal and internal requirements.

Faster decisions
Clear responsibilities, approval processes and escalation paths.

Responsible innovation
New AI use cases can be developed in a controlled way and introduced at scale.

Greater trust
Traceable decisions strengthen acceptance among management, employees, customers and business partners.

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Shape your AI governance now.

Together we will develop a governance approach that fits your organisation, your use cases and your risk landscape.

Request a strategy session