Tagt 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 pilots, but don’t know how to integrate them into your organization in the long term?
We are happy to support you in this. With our experienced team of organizational and AI experts, we can help you set the right organizational course for productive AI operations.
We analyze your existing processes, define clear roles and responsibilities (governance) and create a tailor-made target operating model that efficiently combines business and AI.
Why AI initiatives often get stuck in "pilot status"
Many companies start out ambitiously, but quickly come up against invisible limits. Without a clear target operating model for the AI organization, typical frictional losses arise that jeopardize success:
- Silo formation: Specialist departments build their own solutions (“shadow AI”) without using synergies.
- Unclear responsibility: There is no definition of who is the “owner” of an AI product and who maintains it in the long term.
- Compliance risks: Uncertainty about data protection (EU AI Act) and ethical standards is slowing down the rollout.
- Resource bottleneck: 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:
- Central (Center of Excellence): Bundling all experts in one place. Ideal for the start in order to quickly establish standards and infrastructure.
- Decentralized: AI expertise lies directly in the specialist departments. Maximum speed and technical proximity, 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 implement them operationally.
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 analyze your current setup:
- Where are AI initiatives already emerging today?
- Where does “shadow IT” prevail?
- How smoothly do business and IT really work together?
We not only identify organizational hurdles and technical bottlenecks, but also carry out a detailed skills gap analysis.
This enables us to understand exactly what foundations we can build on and where targeted recruiting or upskilling is necessary.
Phase 2:
Design of the operating model
We define the common target image.
- Who gets to decide what in the future?
- Which specific roles (e.g. AI Product Owner, Data Steward, AI Ethicist) are required for your business model?
- Which processes should be supported by AI?
We design the interfaces between business, IT and legal in such a way that compliance is maintained without slowing down the speed of innovation.
The result is not a theoretical organization chart, but an operational “playbook” that provides clear instructions for day-to-day operations.
Phase 3:
Implementation & anchoring
Structures must be lived, otherwise they remain ineffective.
We support the practical development of the “AI Competence Center”, establish steering committees such as the “AI Board” and define robust processes so that models move safely from the laptop to the company.
At the same time, we provide support through change management and coaching so that your employees accept their new roles and actively support the transformation.
The result: an AI organization that delivers
At the end of our project, you can expect the following results:
- Scale at last: Your AI solutions don’t get stuck in the experimental stage, but create real added value in operations.
- Faster to market: Thanks to 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 have to do. This puts an end to the responsibility ping-pong between the business department and IT.
- Safety without a handbrake: you comply with all regulations (e.g. EU AI Act), but still remain innovative and fast.
- Costs under control: put an end to expensive “shadow IT”. You bundle your strengths and avoid duplication of work in the 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!
