EU AI Act Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used EU AI Act
Alwin G.
Last position:
IT Interim Manager & AI Strategist
- Founder of CheironX: AI-supported GRC management (ISO 27001, BSI IT-Grundschutz, TISAX, DORA)
- Strategic focus on Agentic AI and GenAI for modern IT Governance, Risk & Compliance Management
- IT interim management and strategic consulting
Hannah K.
Last position:
Lecturer in AI Fundamentals for the Digital Workplace at grandedu
- Lecturer in AZAV-certified, one-month training programs on AI fundamentals and practical applications, with several cohorts since February 2026
- Design and delivery of all modules for participants from different professional fields
- Teaching how generative AI works, its areas of application and limitations, as well as prompting and evaluation practices
- Created all teaching materials and exercise formats independently
- Supporting participants throughout the entire course period
Florian S.
Last position:
AI Product Manager / Product Owner at AI Product
- Generative AI products for corporate clients, owned from strategy through specification to production.
- Central strategy, local configuration: multi-tenant AI assistant for occupational pension schemes (bAV), delivered as an interactive avatar with text and voice path. Three tenants run on one codebase, each with its own conversation guide, while the knowledge base, guardrails and escalation paths stay central
- Versioned, AI-ready knowledge base composed into a tenant-agnostic voice context and tenant-specific text prompts — the configuration layer that keeps local adaptation from forking the product
- Conversational design: answer limits, scope and off-topic handling, anti-hallucination rules, escalation and lead handover to human advisors
- Five eval suites as a quality gate before any prompt or model change (anti-hallucination, LLM-as-judge failure modes, multi-turn consistency, voice KPIs, action vocabulary with confusion matrix); user test with 10 testers (Hamburg, 07/2026) drove the rework from alpha to beta
- Coordinated external developers, compliance and client stakeholders; GDPR-compliant EU stack, IDD-compliant, EU AI Act classification documented
- Second product line: white-label social media generator for consultancy chilli mind (CH/DE) — one codebase, per-client branding and configuration
- Results: 239+ deployments and a pilot with corporate customers · 108+ deployments for the white-label product · repeatable pattern for multi-tenant AI products in a regulated environment
Roland C.
Last position:
Founder, Agents for Day-to-Day Business at CXO AI OS
CXO AI OS is an agent system made up of six building blocks. Instead of using AI as a chat window, it creates a system that understands a company’s context, makes decisions according to its rules, and acts on its behalf.
- For mid-sized companies: a guided sprint followed by operation for a team, department, or prioritized cluster, based on an AI assessment
- For self-employed professionals: a program in which participants build their own agent system
- Sequence in the company: assessment, prioritization, sprint, operation
- Implementation in Claude Cowork or ChatGPT Work, without coding
- Architecture: Chief of Staff, Goals, Advisors, Agents, Context, Catalog
Jörg K.
Last position:
Exec. Coach / Consultant / Agilist at HASOMED GmbH
Repaired a broken “ScrumBan” process, then established a pure Kanban system; increased output in the Kanban flow by 22% within four weeks
Increased team autonomy and decision-making ability by implementing new decision strategies; resulting in up to 25% better outcomes
Redesigned retrospectives (including one-to-one coaching and workshops), which led to consistent implementation of the resulting action items
Intensive coaching of Product Owners (POs) to develop and support “Empowered Teams”, alongside leadership development to place agile frameworks and methods in a realistic context (“de-illusioning”)
Supported change management processes to promote an agile company culture among management and teams, improving internal communication to increase transparency and effectiveness in agile processes
Khalid E.
Last position:
Lead Architect & Developer at kem-consulting
Development of an agent-based governance platform for the automated assurance of EU AI Act compliance and ODA-compliant orchestration of AI services in complex enterprise environments.
Design and implementation of an agent-based "Mission Control" framework (Aletheia Conductor) for autonomous state monitoring and process control.
Development of "Compliance-as-Code" (CaC) solutions based on OPA/Rego for system-wide enforcement of regulatory guardrails.
Integration of TM Forum ODA standards (TMF630, TMF622, TMF642) to ensure interoperability and standardization.
Building a highly available event-driven architecture using Redpanda and CloudEvents v1.0 for near-real-time event processing.
Implementation of an audit-proof "Evidence Chain" through cryptographic linking of trace logs in preparation for automated audits.
Tech Stack: Java 21 (Quarkus Native), TypeScript (Next.js), Redpanda (Kafka API), CloudEvents v1.0, OPA (Open Policy Agent) & Rego, TimescaleDB, ZincSearch, Redis, TM Forum ODA, Git, GitHub, Clean Code Development, Like-C4.
Jens H.
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilization of an Azure/.NET landscape in live operation.
- Architecture, DevOps, and operational readiness; technical decisions under time pressure
- Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics
Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps
Michael S.
Last position:
Establishment of Compliance/TPRM at Haftpflichtkasse
Establishment of Compliance Department & DORA Operationalization
- Establishment of a complete compliance organization in accordance with DORA
- Development and operationalization of the SfO
- Use of AI agents for automation:
- Evaluation of due diligence questionnaires including risk classification
- AI-supported contract analysis (DORA/MaRisk compliance)
- Monitoring of external data sources (cyber incidents, newsfeeds)
- Establishment of a decentralized risk and action register
- Preparation of GAP analyses and derivation of measures
- Establishment and maintenance of the Outsourcing Information Register
- Use of proprietary TPRM frameworks, checklists and process models
Establishment of Compliance Department & DORA Operationalization
- Establishment of a complete compliance organization in accordance with DORA
- Development and operationalization of the SfO
- Use of AI agents for automation:
- Evaluation of due diligence questionnaires including risk classification
- AI-supported contract analysis (DORA/MaRisk compliance)
- Monitoring of external data sources (cyber incidents, newsfeeds)
- Establishment of a decentralized risk and action register
- Preparation of GAP analyses and derivation of measures
- Establishment and maintenance of the Outsourcing Information Register
- Use of proprietary TPRM frameworks, checklists and process models
- Project controlling - presentation and structured measurement of project goals achieved as part of management reporting.
- Overall responsibility for establishing a Compliance, Governance and Risk organization
- Establishment of an integrated GRC model and executive reporting for the Management Board.
Henry H.
Last position:
Interim Manager IT-Compliance at Int. Fertigungsunternehmen
- Industry: mechanical engineering, vehicle manufacturing
- Regulations: Data Act
- Project focus: data governance, legally compliant use of machine data, data platforms
- Assigned by: CFO, platform product owner
Successes/Results (early phase):
- Compliance support for the setup of an internal standardized data usage platform based on Databricks.
- Created the basis for the legally compliant and effective use of machine data, including:
- Technical: gap analysis and closing of gaps in the segmentation and maintenance of collected machine data.
- Technical: consideration of data flows from the platform to users and third parties.
- Organizational: drafting and finalizing the required data usage agreements.
Sergei M.
Last position:
Interim Program Manager at parcIT
Time-limited interim assignment filling a vacant program leadership position: joint leadership of a complex software project and orchestration of several agile teams (business, development, and DevOps teams), as well as actively driving change processes.
- Program Management & Planning: Responsibility for creating and updating milestone, resource, and budget plans to ensure project objectives using agile and hybrid methods.
- Cross-functional Collaboration: Promoting cooperation and knowledge sharing across teams; resolving blockers through proactive conflict management and targeted facilitation.
- Stakeholder Management & Transparency: Ensuring transparent and audience-appropriate communication within and outside the project organization using modern project management tools.
Matthias S.
Last position:
Technology Lead & Co-Founder at LegalMind GmbH
- Redesign of legal operations: standardised workflows reducing routine effort by up to 80%, with source citation, hallucination check as quality gate, role model, logging and audit trail.
- Compliance-by-design operating model (EU AI Act readiness, GDPR, eIDAS) with documented, releasable process steps.
- Roadmap, sprint planning and release management for an agentic RAG platform with counsel-in-the-loop approval, audit trail and German hosting.
- EU AI Act readiness, GDPR and eIDAS requirements managed as first-class project deliverables; go-to-market for two customer verticals.
Franz B.
Last position:
Product Development (AI) at Own initiative
AI telephone assistant platform
Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL
- Conception and hands-on development of an AI-supported telephone assistant platform (voice AI / LLM) – from idea and architecture to MVP/product.
- Built agentic workflows and full automations with Claude Code and Google AI Studio.
- Also delivered AI-supported work in client engagements: used Claude Code for governance documentation, requirement drafts, and automations.
Marc H.
Last position:
Own AI Product Project & AI Training at Self-employed
- Built and validated SupportPiloten, an AI-powered content operations service; won the first paying pilot customer
- Tested agentic workflows with Claude Code and Codex for analysis, research, documentation, and prototyping
- Continued developing my own AI product; training in AI governance, AI compliance, and the EU AI Act (ongoing)
Bidya B.
Last position:
Product Manager – Payments & Platform at Pipedrive
CRM and revenue platform managing billing and subscription workflows.
- Scaled payments infrastructure across data products, direct debit expansion and automated abuse prevention, generating $416K in annualized operational savings ($8K/week) by eliminating redundant gateway calls.
- Owned backlog and sprint execution for autonomous checkout abuse detection pipelines, designing real-time risk guardrails and velocity heuristics that blocked card testing attacks.
- Architected enterprise billing migrator user stories and data reconciliation mechanisms, achieving zero-downtime subscription state transitions and cutting $60K in infrastructure overhead.
- Expanded European direct debit (SEPA) payment capabilities, managing cross-squad API dependencies and automated webhook error-handling to eliminate checkout friction.
Michele H.
Last position:
Chief Digital Officer at DAT Vermögensmanagement GmbH
- Project manager for the analysis, implementation, and optimization of digital processes
- Concept, management, and optimization of comprehensive marketing campaigns for lead generation via Paid Social (incl. Meta Ads, TikTok Ads)
- Concept and implementation of content production and marketing activities
- Project management in omnichannel marketing and process automation
- Implementation of digital tools to improve customer acquisition and support
- Internal stakeholder management and coordination of external service providers
Discover over 15,000 top freelancers
Statistics of experts using EU AI Act
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
2.1 years
Positions per freelancer
12
Top business areas
Information Technology, Project Management, Product Development
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
95%
Master's degree or higher
67%
Doctorate
15%
Certifications per freelancer
5
Most common languages
German, English, Spanish
Speak two or more languages
94%
Based on our profile pool as of 9 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Discover detailed EU AI Act rate benchmarks:
Explore rate insightsAverage rates of experts in Germany using EU AI Act
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 9 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
EU AI Act experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (90%)
- Professional Services (66%)
- Banking and Finance (47%)
- Automotive (36%)
- Manufacturing (36%)
- Retail (31%)
- Government and Administration (30%)
- Energy (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What the EU AI Act covers
The EU AI Act is the European Union’s risk-based framework for artificial intelligence. It sets duties for providers, deployers, importers and distributors of AI systems, with rules that vary by risk level. The regulation covers prohibited practices, high-risk systems, transparency obligations and general-purpose AI models.
Risk classification
Companies use the Act to determine whether an AI application is prohibited, limited risk, high risk or subject to lighter obligations. Classification depends on the system’s purpose, context and role in a product or process, not simply on the model technology. Specialists assess intended use, affected people, data flows and human oversight.
- Inventory AI systems and their providers
- Map use cases to the Act’s risk categories
- Identify transparency and documentation duties
- Review prohibited practice exposure
Compliance workstreams
EU AI Act projects often produce an AI inventory, risk assessment, technical documentation, instructions for use and governance procedures. Professionals also establish monitoring, incident handling, record keeping and human oversight. For high-risk systems, they may coordinate conformity assessment, quality management and post-market monitoring.
Ecosystem and adjacent skills
The regulation intersects with GDPR, product safety, cybersecurity and sector-specific rules. Useful expertise includes data protection impact assessments, model risk management, procurement controls and information security. Specialists may work with ISO 42001, ISO 27001, NIST AI RMF, MLOps teams, legal counsel and internal audit functions.
When companies need specialists
External expertise is valuable when a company is building an AI governance programme, launching a regulated product or reviewing systems already in operation. It can also support supplier assessments and preparation for audits or regulatory inquiries.
- A company cannot assign clear AI Act roles
- AI suppliers provide incomplete compliance evidence
- A product may qualify as high risk
- Teams need practical controls for deployment
What strong professionals deliver
Strong EU AI Act professionals connect legal requirements with how models are built, procured and used. They document assumptions, separate provider and deployer duties, and turn obligations into workable controls. In Germany, collaboration may involve German-language stakeholders, EU-wide teams and remote work across legal, product, security and data functions.
Frequently asked questions
Key details about EU AI Act, drawn from the questions we get asked most.
The EU AI Act is used to regulate artificial intelligence according to its potential risk. It defines prohibited practices, requirements for high-risk systems, transparency duties and responsibilities across the AI supply chain.
The EU AI Act governs the safety, transparency and governance of AI systems, while GDPR focuses on personal data and individual rights. They can apply to the same project, so a sound assessment connects AI risk classification with data protection obligations.
An EU AI Act specialist should understand GDPR, cybersecurity, product safety and AI governance. Experience with technical documentation, supplier management, model risk, ISO 42001 or NIST AI RMF is also useful.
The EU AI Act does not call for one fixed level of project experience. The right specialist should have handled the relevant system type and risk category, and should be able to translate regulatory duties into evidence, controls and accountable processes.
The EU AI Act can be implemented through remote collaboration when documentation, workshops and access to system owners are well organised. On-site sessions may help with sensitive products, German-language stakeholders or complex governance decisions.
A strong EU AI Act specialist can explain why a system falls into a particular risk category and show how that conclusion affects controls. Ask for examples of inventories, technical documentation, supplier reviews and human-oversight processes, while protecting confidential information.
The EU AI Act can affect organisations outside the EU when their AI systems are placed on the Union market, used in the EU or produce certain effects there. Applicability depends on the organisation’s role, the system and the relevant activity.
An EU AI Act freelancer may provide an AI system inventory, role and risk assessment, obligations matrix, governance policy and supplier evidence review. For relevant systems, deliverables can also include technical documentation, transparency notices, monitoring procedures and an implementation roadmap.
The average hourly rate of freelancers in Germany who have used EU AI Act in their recent projects is 117 €, which corresponds to a daily rate of about 935 € based on an 8-hour working day.
Of the freelancers in Germany who have used EU AI Act in their recent projects, 95% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 15% hold a doctorate.
On average, freelancers in Germany who have used EU AI Act in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.1 years.
The most common languages among freelancers in Germany who have used EU AI Act in their recent projects are German (100%), English (94%), and Spanish (17%).
The most common industries among freelancers in Germany who have used EU AI Act in their recent projects are Information Technology (90%), Professional Services (66%), and Banking and Finance (47%).
The most common business areas among freelancers in Germany who have used EU AI Act in their recent projects are Information Technology (94%), Project Management (88%), and Product Development (67%).
Main locations of FRATCH Experts, who have recently used EU AI Act
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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