M&A IT complexity
After acquisitions, the IT landscape is fragmented, architecture decisions are inconsistent, and integration priorities are unclear. Controllability and transparency are lacking.
Enterprise Architecture · AI Governance · AI Production
Complex organisations need more than AI initiatives. They need governable AI operating models.
I help organisations structure fragmented IT‑landscapes, establish AI‑initiatives in line with governance requirements, and transition them into stable, production‑ready operating models.
Typical starting situations
Most engagements begin not with a strategy question, but with a concrete tension.
AI pilot consolidation
Multiple teams are piloting AI without shared operating, governance, or prioritisation logic. Parallel initiatives increase costs and risks without a common denominator.
Agentic AI without governance
Copilot, agent, or RAG solutions emerge in silos — without role models, control logic, or clear accountabilities. Auditability and compliance are not secured.
Portfolio and roadmap friction
Architecture work is happening, but failing to influence portfolio, roadmap, and decision forums. Architecture and steering operate in parallel without coupling.
These are exactly the points where I engage.
Three disciplines. One integrated perspective.
I work at the intersection of architecture, governance, and operational capability. Not as abstract advisory, but as structuring and decision-support for complex transformations.
Enterprise Architecture
Target architectures, structuring complex IT landscapes, and architecture governance.
- Target architectures for fragmented system landscapes
- Structuring complex IT landscapes
- Architecture governance and standards
- Roadmaps with implementation logic
- IT consolidation after M&A
AI Governance
Roles, policies, and control logic for responsible AI integration.
- Governance frameworks for Copilot, Shadow AI and Agentic AI
- Roles, policies, and control logic
- EU AI Act-aligned structuring
- Responsible integration of AI
- Governance for production-ready AI
AI Production & Decision Logic
Design of governable AI operating models with measurable impact.
- Design of governable AI operating models
- Use case prioritisation by value, risk and operational readiness
- Operating design and transformation governance
- Decision logic and prioritisation
- Human-in-the-loop models
All three disciplines are available as structured workshops.
View workshopsWhy me?
I work at the intersection of Enterprise Architecture, AI Governance, and AI Production.
TOGAF Enterprise ArchitectCBAP Business AnalystPMP Project ManagerPSM Scrum MasterAI Governance in HealthcareAI Governance in EnergyAI Governance in Finance
Enterprise Architecture as a structuring discipline
I bring structure to complex IT landscapes and ensure new AI capabilities are embedded in sustainable target architectures.
AI Governance over pilot romanticism
I develop governance frameworks, roles, and decision logic that make AI governable and accountable.
AI Production over tool activism
I focus on operating models, standards, and real-world effectiveness rather than non-committal PoC rhetoric.
Senior advisory without overhead
You work directly with an experienced advisor — not a pyramid delivery model staffed by junior teams.
Why not a classic consulting firm?
What sets me apart from large consultancies.
Direct seniority
No pyramid model. No junior teams. You work directly with me — at the mandate level, without translation losses.
Two disciplines. One logic.
Advising Enterprise Architecture and AI Governance separately creates friction. I bring both together — target architecture, governance framework, and operating model in one consistent structure.
Regulated industries. Not a generalist.
Healthcare, Energy, Finance, Commerce. I know the regulatory frameworks and decision logic of these industries from concrete mandates — not from textbooks.
Practical results over presentation weight
Outputs must be viable in real organisational contexts. Decidability and practicality take priority over elaborate concepts without actionability.
Client voices
What clients say.
For reasons of confidentiality, full names are not disclosed.
„Dr. Sienou made our AI governance structures tangible within weeks — no theoretical overhead, directly actionable."
„The combination of Enterprise Architecture and AI Governance is rare. We finally had someone who bridges both worlds."
„No junior overhead, no presentation battles. Direct seniority, clear outcomes."
How I work
Four principles that define my way of working.
Clarity before activism
I start not with tool enthusiasm, but with a target picture, structure, and decision logic. The first step is always: understand before acting.
Seniority without overhead
You work directly with me. No delegation to rotating teams, no junior pyramid, no unnecessary coordination overhead.
Practical results over presentation weight
Outputs must be viable in real organisational contexts. Practicality, decidability, and actionability take priority over elaborate concepts.
Connected to delivery
Where appropriate, follow-up pathways into focused intervention, structured implementation, or targeted capability building can be linked.
More about background, career, and certifications.
About meOutcome patterns
The following patterns illustrate typical situations where my advisory creates impact.
M&A IT complexity
Problem
Post-acquisition IT landscapes are fragmented, architecture decisions are inconsistent, and AI initiatives run without shared guardrails.
Intervention
Establish target architecture, integration logic, governance framework, and AI categorisation.
Outcome
Greater transparency, clearer integration priorities, lower architecture and compliance risks, stronger foundation for production-ready AI.
AI pilot consolidation
Problem
Multiple teams are piloting AI without shared operating, governance, or prioritisation logic. Parallel initiatives generate waste and opacity.
Intervention
Structure the use case portfolio, assess maturity and impact, define official operating models.
Outcome
Less waste, focused scaling decisions, greater transparency on value, risks, and investments.
Agentic AI in processes
Problem
Agents and assistants emerge in silos, disconnected from core processes and without clear accountabilities.
Intervention
Define process-bound agent architecture, role logic, governance hooks, and human-in-the-loop model.
Outcome
Closer process alignment, more controllable AI use, better auditability, and clearer accountability.
Insights
Practical knowledge on Enterprise Architecture, AI Governance and production-ready AI.
Governable AI Operating Models: A Framework for Production Deployment
More than 40 percent of all AI projects never reach production. The reason is rarely the technology. It lies in the absence of an operating model. This article presents a framework of eight building blocks that makes AI systems manageable, accountable, and scalable.
From Prompt Engineering to Prompt Leadership
Prompt engineering has been commoditised. What organisations need is a leadership discipline: the ability to define which tasks AI should perform, what a good result looks like — and who is accountable for it. The MOTIVE Framework provides the structure.
Agentic AI in Enterprise Architecture
Agentic AI does not merely affect technology stacks — it intervenes deeply in Business Architecture, IS Architecture and infrastructure. This whitepaper shows which tensions arise, why classical EA governance is insufficient, and what governance architecture is needed for controllable Agentic AI operating models.
Whitepaper · Free Download
Agentic AI in Enterprise Architecture
Enterprise Architecture is the bridge between strategy, the business model, and the IT landscape. Agentic AI systems deeply affect Business Architecture, Information System Architecture, and infrastructure — they are not a pure IT technology question, but an Enterprise Architecture question.
In this whitepaper, I show how capabilities, processes, and operating models change with autonomous AI agents, what tensions they create in IS architecture, and why the EA function must sharpen its role as an alignment and governance authority.
- Capabilities, processes and operating models with Agentic AI
- Tensions in Business and IS Architecture
- EA as alignment and governance authority
- Governance hooks, human-in-the-loop, and audit logic
For CIOs, CDOs, and Enterprise Architects.
Download whitepaper as PDF
Register with your email and download the whitepaper for free.
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Where you start
Engagements often begin with a concrete trigger:
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"We already have AI in use, but no robust governance model."
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"We have multiple AI initiatives, but no shared architecture and operating logic."
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"Our IT landscape is highly fragmented due to M&A, diversification, or international expansion."
Regardless of the starting point, I work on three levels:
Order in the IT landscape
Structuring, target architectures, and architecture governance for fragmented system landscapes.
Governance for production-ready AI
Roles, policies, control logic, and operating framework for responsible AI integration.
Transition to viable operating models
Operating design, use case prioritisation, and production-ready deployment logic.
Portfolio entry points
Depending on your situation, collaboration can develop in different directions.
SIENOU.ME
Strategic advisory and executive engagement
Senior-level advisory for complex transformations.
abamix · Intervention
Focused AI intervention in 4–6 weeks
Fast, structured intervention for specific AI challenges.
abamix · Implementation
Modular AI implementation for organisations
Structured implementation and scalable AI initiatives for enterprises.
ki-werkstatt.ai
Training and governance readiness
Enabling teams and leaders for governance-compliant AI use.
Frequently asked questions
What decision-makers ask.
What sets you apart from a classic consulting firm?
No pyramid structure, no junior overhead. You work directly with me — an experienced senior advisor with 15+ years in complex transformations. No rotation between teams, no status meetings without substance.
Which organisations do you work with?
Mid-sized and large organisations in regulated industries — Energy, Healthcare, Finance, and Commerce. Typically with a CIO, CDO, or Enterprise Architect as direct counterpart.
What does an initial conversation cost?
The initial conversation is non-binding and free. It serves to understand your starting situation and clarify whether and how I can help.
How long does a typical engagement last?
It depends on scope. Workshops are single days. Short interventions (e.g. AI Governance Framework) typically take 4–8 weeks. More structured mandates — such as target architecture or AI Operating Model — 2–4 months.
Do you help with EU AI Act compliance?
Yes. AI Governance is one of my core topics. I help classify AI systems by risk category, develop governance frameworks, and structure accountabilities in line with the EU AI Act.
What is the difference between AI Governance and AI Production?
AI Governance regulates accountabilities, policies, and compliance — the "who can do what and under what conditions". AI Production addresses the operational deployment: operating models, human-in-the-loop, observability, and scaling pilots into real processes.
Do you work remotely or on-site?
Both are possible. For strategic workshops and kick-offs I prefer in-person. Ongoing collaboration typically works in a hybrid format — with clear deliverable milestones rather than permanent presence.
Next step
A 30-minute conversation to review your situation and determine whether and how I can support you.
No commitment · Confidential · Concrete