Start with your application portfolio. Flag all applications that are providing AI features, then document the AI features each one delivers, the models powering them, and the technologies those models rely on. This four-layer structure, covering AI use cases, AI features, AI models, and AI technologies, gives you a complete and traceable picture of AI across the enterprise. Tools like Bizzdesign Alfabet are built specifically to capture and govern this structure, giving organizations a single source of truth for AI usage across the business.

The goals are the same: align investments to business strategy, reduce risk, and keep costs in check. What's different is the entity being governed. An application is a discrete, definable object with a clear owner and a known user base. AI manifests across the organization in multiple forms simultaneously, at the level of the business use case, the feature that delivers it, the model that powers it, and the underlying technology. Each layer needs to be documented and governed separately, which is why AI portfolio management requires its own structure.

Enterprise architecture defines how an organization's strategy, processes, data, and technology fit together. In the context of AI governance, EA plays three critical roles: it connects AI use cases to business capabilities and portfolio priorities, it establishes the architectural framework and standards for AI adoption, and it ensures traceability from AI use cases all the way down to the underlying technology stack. Without EA, AI governance lacks the structural foundation to be consistent or defensible.

Effective AI governance requires five connected roles. The Application Owner flags AI-enabled applications and defines their AI-driven features. The Technology Architect identifies the technologies behind AI models and categorizes what's in use. The CTO and AI Competency Center ensure adoption stays aligned with business goals. The Enterprise Architect designs the governance framework and sets standards. The Risk and Compliance Manager ensures regulatory compliance across the portfolio. None of these roles works well in isolation, and all five need a shared view of the portfolio to function as a governance system. Bizzdesign Alfabet provides that shared view, with predefined business questions and executive-ready reporting built in.

If you can't answer basic questions about your AI with confidence, you need one. Specifically: Can you produce a complete list of AI running across the enterprise? Do you know which use cases have been formally approved and by whom? Can you trace any AI feature back to the model powering it and the technology beneath that? Can you show which business priority each use case supports and whether it warrants continued investment? If those questions require significant effort to answer, or produce different answers depending on who you ask, the portfolio isn't under governance.

Shadow AI refers to AI tools and workflows being used across the organization without the knowledge or oversight of IT, EA, or risk functions. It typically spreads through embedded AI features, independently acquired tools and business-led experimentation outside formal technology and approval processes. Getting it under control requires enterprise-wide standards that define how AI can be used, by whom, and within what boundaries, combined with a connected view of what's been deployed across the application landscape. Bizzdesign Alfabet supports this by tracking AI-specific attributes across applications and components, making it possible to identify ungoverned AI and bring it into the portfolio.

Building a governed AI portfolio follows seven steps, each one adding a layer of visibility and structure. Start by flagging all applications providing AI features, then document the AI features each one delivers and assess their risk levels. Map those features to their providing applications, then document the AI use cases they support and define the approval process. Create an inventory of approved AI models by location and jurisdiction, map those models to the features and components they power, and finally define the AI technologies being provided by those models. Each step builds on the last, moving from application-level visibility through to a complete, traceable picture of the full AI architecture. Bizzdesign Alfabet's AI Portfolio Management Accelerator is designed to support this process, with preconfigured structures and views that make each step faster to execute and easier to maintain.