Our customer, a leading German telecommunications company, demanded a consistent way to turn AI ideas into governed products and make potential savings and revenue opportunities visible. Working together, we created an Alfabet-based approach that connects demand, use cases and AI products with portfolio governance, technical architecture and business value.
01 The challenge
Why AI products need more than an idea list
AI initiatives often begin in different teams, with varying levels of detail and different routes into delivery. Without a shared process, teams may pursue similar ideas independently and overlook data or models that could be reused. As a result, decision-makers lack a complete view of costs, value, risks and technical dependencies.
Our customer therefore needed more than an inventory of AI use cases. The goal was to establish a clear route from the first idea to a product that can be delivered, operated, improved and eventually retired. Responsibilities, governance requirements and the connection between business demand and the technical product had to remain clear throughout.
02 The approach
A governed route from idea to portfolio
Capture the opportunity
New AI ideas enter Alfabet through a standardised demand process. Each demand records its owners, sponsoring IT unit, stakeholders, operational responsibility and expected business value. Its status shows whether the idea is open, being assessed, under review, approved or complete.
Assessment and prioritisation take place within the demand. The outcome is clearly recorded: the idea is either rejected or becomes an approved AI use case. This creates a traceable handover from exploration to delivery without the need for a separate shadow list.
Shape the AI product
The operating model distinguishes between three related elements. A demand follows an idea from discovery to decision, while an AI use case describes how AI will address an approved business need. The AI product is the solution that is ultimately delivered and operated.
This distinction matters because one AI product can support several use cases. The product has its own architecture, ownership and lifecycle, while each use case retains its specific business purpose, value and governance context. Products and use cases receive separate identifiers but remain connected through a many-to-many relationship.
Alfabet connects each product with its use cases, data products, technology platform, hosting components, AI models and supporting technologies. Teams can identify dependencies, opportunities for reuse and the people responsible for the product in operation.
Govern the complete lifecycle
The AI Product Operating Model covers discovery, delivery, maintenance and retirement. Discovery begins with an initial assessment and continues with a detailed review of business and technical viability, while delivery covers development and rollout. Once the product is in operation, maintenance includes monitoring, fixes and operational support.
Governance is built into each stage, beginning with an early assessment that filters ideas before significant effort is invested. Product councils document decisions about further assessment and delivery, while portfolio, project, privacy, cyber security and AI risk processes provide the necessary approvals.
The playbook also provides a structured basis for prioritisation. It considers strategic fit and expected value, as well as confidence, reusability, implementation costs and the effort required from IT and AI teams. This helps direct limited capacity towards initiatives with credible value and a realistic path to delivery.
Steer products as a portfolio
Alfabet reports provide an overview of the AI portfolio and show dependencies between use cases, products, data and technology. Colour coding highlights relevant attributes, while Kanban views track progress through the process. Business value is presented alongside technical and governance information.
Decision-makers can see which opportunities are being assessed, which products are in delivery or operation and which use cases rely on the same assets. This allows teams to compare similar initiatives before building separate products. It also makes shared data, platforms and models visible, turning reuse into a deliberate portfolio decision.
The product connects business value with delivery reality. It turns an approved AI use case into something that can be owned, operated and improved.
03 The outcome
A connected foundation for the AI portfolio
The implemented Alfabet model gives our customer a structured foundation for managing AI demands, products and the wider portfolio. Instead of remaining isolated entries, ideas, use cases and AI products stay connected to the relevant data, models, technologies, owners, risks and business value.
The operating-model playbook defines the wider process around this foundation. Although some elements continue to evolve, the direction is clear: one transparent route from an idea to a governed AI product, with decisions and dependencies visible throughout its lifecycle.
AI portfolio management is one of the use cases we implement in Bizzdesign Alfabet. Explore our Alfabet capabilities or talk to us about your own operating model.