Target Operating Model (TOM) for Your AI Organization
Creating structures that scale. From uncontrolled growth to a value-adding AI organization.
Target operating model for AI
Have you successfully launched your first AI pilot projects but aren’t sure how to integrate them sustainably into your organization?
We’d be happy to help. With our experienced team of organizational and AI experts, we’ll help you set the right organizational course for productive AI operations.
To do this, we analyze your existing processes, define clear roles and responsibilities (governance), and create a tailor-made target operating model that efficiently bridges the gap between business and AI.
Why AI initiatives often get stuck in "pilot status"
Many companies start out with high ambitions but quickly run up against invisible barriers. Without a clear target operating model for the AI organization, typical inefficiencies arise that jeopardize success:
- Silo formation: Departments build their own solutions (“shadow AI”) without leveraging synergies.
- Unclear responsibilities: There’s no clear definition of who is the “owner” of an AI product and who will maintain it in the long term.
- Compliance risks: Uncertainty regarding data protection (EU AI Act) and ethical standards slows down the rollout.
- Resource bottlenecks: Central IT teams become a bottleneck because processes for collaboration are lacking.
Tailor-made organization instead of a standard template
Every company has its own DNA. A corporation needs different structures than a medium-sized company.
That’s why we don’t impose a theoretical model on you, but work with you to develop the solution that suits your culture and your goals. It’s all about striking the right balance between control and speed.
We are usually guided by three basic archetypes, which we develop individually:
- Centralized (Center of Excellence): Bringing all experts together in one place. Ideal for getting started, to quickly establish standards and infrastructure.
- Decentralized: AI expertise resides directly within the business units. Maximum speed and domain-specific expertise, ideal for innovation-driven units.
- Hybrid (Hub-and-Spoke): The “best of both worlds” approach. A central hub sets guidelines, while the “spokes” in the departments handle operational implementation.
Our approach: We not only analyze your IT, but also how your company “ticks”.
Together we define exactly the mix of centralization and autonomy that makes you fast without sacrificing security.
In 3 phases to a functioning AI organization
We do not impose a standard model on you, but develop structures that fit your corporate culture.
Phase 1:
Status quo & maturity level
We’ll analyze your current setup:
- Where are AI initiatives already taking shape today?
- Where is “shadow IT” prevalent?
- How smoothly do Business and IT really work together?
We not only identify organizational hurdles and technical bottlenecks, but also conduct a detailed skills gap analysis.
This allows us to understand exactly what foundation we can build upon and where targeted recruiting or upskilling is needed.
Phase 2:
Design of the operating model
We define our shared vision.
- Who will have decision-making authority in the future?
- What specific roles (e.g., AI Product Owner, Data Steward, AI Ethicist) are needed for your business model?
- Which processes should be supported by AI?
We design the interfaces between Business, IT, and Legal in a way that ensures compliance without slowing down the pace of innovation.
The result is not a theoretical organizational chart, but an operational “playbook” that provides clear instructions for day-to-day operations.
Phase 3:
Implementation & anchoring
Structures must be put into practice; otherwise, they remain ineffective.
We support the practical implementation of the “AI Competence Center,” establish steering committees such as the “AI Board,” and define robust processes to ensure that models are safely transferred from the laptop to the workplace.
At the same time, we provide support through change management and coaching to ensure that your employees embrace their new roles and actively contribute to the transformation.
The result: an AI organization that delivers
At the end of our project, you can expect the following results:
- Scale Up at Last: Your AI solutions won’t get stuck in the experimental phase—they’ll deliver real value in day-to-day operations.
- Faster to market: With clear standards, you can launch new use cases in weeks instead of months (time-to-market).
- Clarity Instead of Chaos: Everyone knows exactly what they need to do. This puts an end to the back-and-forth over responsibility between business units and IT.
- Security without holding you back: You comply with all regulations (e.g., the EU AI Act) while still remaining innovative and agile.
- Costs under control: Say goodbye to expensive “shadow IT.” You pool your resources and avoid duplicate work across departments.
We look forward to working with you to set up the right target operating model for your AI organization. Get in touch with us!
