Last updated: February 6, 2026

This page provides a comprehensive overview of all AI and Generative AI capabilities available in the Ardoq platform. This is a living page and will evolve as Ardoq’s AI capabilities continue to expand.

Ardoq uses AI to accelerate modeling, democratize insights, and make architecture data more useful while keeping customers firmly in control. Learn about our Ardoq AI Principles and follow our Ardoq AI Labs ProductBoard tiles to keep up with our AI roadmap & experiments.

Each capability below is tagged with its current maturity:

These capabilities help teams move from blank pages to usable architecture models faster.

Automatically generate multi-level business capability maps based on your organization’s context, industry, or imported data.

Used for: Capability-based planning, heatmaps, cost and risk analysis.

Learn more: Blog: New Ardoq AI Features To Automate Value Streams And Capability Modeling

Create draft business value streams in seconds, providing a structured starting point for refinement and alignment. Automatically suggest and create links between architecture elements (applications, capabilities, initiatives) and business value stream stages.

Used for: Strategy-to-execution traceability, transformation planning

Learn more: Blog: AI for Business Value Streams

Generate draft business value propositions connected to capabilities, value streams, and initiatives.

Used for: Framing business outcomes, stakeholder communication, value realization discussions

Learn more: Blog: AI for Business Value Streams

Convert text descriptions or uploaded images into structured, connected process models. Refine existing process models using natural language instructions, such as adding steps, changing flows, or clarifying logic.

Used for: Process documentation, operational analysis, linking processes to applications

Learn more:

Upload diagrams, whiteboards, or slide screenshots and automatically convert them into structured architecture data.

Used for: Migrating legacy diagrams, accelerating documentation

Learn more:

These capabilities make architecture insights accessible through natural language.

Ask questions about your architecture in plain English and receive answers grounded in your live data.

Used for: Application analysis, dependency questions, impact analysis

Learn more:

Automatically generates Advanced Searches based on natural language input, which users can then refine.

Used for: Faster reporting, advanced analysis without query expertise

Learn more:

Generate draft viewpoints based on natural language prompts, automatically selecting relevant components, relationships, and perspectives.

Used for: Rapid stakeholder views, impact analysis, executive-ready visuals

Learn more: Help Center Article: How to create viewpoints using AI

Automatically generate clear, consistent descriptions for viewpoints and reports, grounded in the underlying architecture data.

Used for: Documentation, stakeholder communication, consistent reporting

Learn more: KB Article: AI-Generated Report & Viewpoint Descriptions

Automatically suggests relationships between components (for example, applications and capabilities) using AI, based on existing architecture data and context.

Used for: Faster modeling, reduced manual linking, and more complete architecture views without deep EA expertise.

Learn more: KB Article: AI-based reference creation in Ardoq with simple Retrieval Augmented Generation

These capabilities help users learn, navigate, and adopt Ardoq more effectively.

Built-in AI assistant that answers “how do I” questions about using Ardoq and applying best practices.

Used for: User onboarding, self-service support, modeling guidance

Learn more:

These capabilities improve data quality, consistency, and usability.

Automatically generate consistent, structured descriptions for architecture components based on their relationships.

Used for: Documentation, portfolio reviews, stakeholder communication

Learn more: KB Article: AI-Powered Component Descriptions

Use AI to help generate survey questions and structure responses into usable architecture data.

Used for: Data collection from application owners and business stakeholders

Learn more:

These capabilities allow secure, governed AI access to Ardoq data from external tools.

Provides read-only, permission-aware access to live Ardoq architecture data for external AI tools such as Microsoft Copilot or Claude.

Key characteristics:

Used for: Asking architecture questions from enterprise AI tools

Learn more:

A practical guide to writing effective, context-aware prompts when using Ardoq AI and external AI tools (such as Copilot or Claude) with architecture data. The playbook covers best practices, example prompts, and governance considerations to help teams get consistent, reliable results from AI — without compromising control or trust.

Learn more: Prompt Engineering Playbook (Guide)

AI Lens gives organizations a clear, enterprise-wide view of how AI is used — from embedded and SaaS AI to emerging AI agents.

Built on Enterprise Architecture, it helps teams govern AI, manage risk and ownership, and stay compliant using a single control plane.

With pre-built EU AI Act assets and the flexibility to support any regulation or internal policy, AI Lens enables confident, compliant AI adoption.

Used for: AI governance, EU AI Act readiness, risk and compliance assessments, executive reporting.

Learn more:

Ardoq’s AI capabilities are designed to support enterprise governance and regulatory requirements.

We’re building deeply embedded, context-aware AI that helps EAs model change, predict outcomes, and guide business decisions. This isn’t AI for show. It’s AI for workflow.

AI respects Ardoq’s role-based access controls and data permissions at all times.

AI features in Ardoq are opt-in and must be explicitly enabled for your organization.

To enable AI:

Once enabled, AI capabilities become available based on your subscription and feature access.

Yes. If you prefer a no-AI experience, you can ask your CSM to ensure AI features remain disabled for your instance.

Ardoq fully supports customers who choose not to enable AI and provides the same core EA platform functionality without AI assistance.

Ardoq uses a combination of leading large language models (LLMs) and proprietary technology.

Key points:

Specific model providers may evolve over time as Ardoq continues to adopt best-in-class AI technology.

No. Ardoq’s AI features generate suggestions, drafts, and recommendations. All changes must be explicitly reviewed and approved by a user before being saved.

Ardoq AI operates in a controlled, non-destructive way.

AI-generated outputs are created inside a separate Scenario, not directly in the live model. Users must review, validate, and deliberately merge any AI-generated content before it is saved to production data.

Yes. All AI features respect Ardoq’s existing role-based access controls.

AI cannot surface or infer information that a user does not already have permission to access.

Ardoq’s Model Context Protocol (MCP) implementation is currently read-only but we are actively working on read/write capabilities.

External AI tools can retrieve insights and context from Ardoq, but cannot modify architecture data today.

When write operations are introduced, they will follow the same human-in-the-loop principles as other Ardoq AI features. Any proposed changes will be created in a separate Scenario and must be explicitly reviewed and manually merged by a user before affecting live data.

Yes. Ardoq’s MCP Server enables you to build context-aware AI agents that can reason over your architecture data and use Ardoq as a trusted source of truth.

Using MCP, AI agents can:

Today, MCP access is read-only, meaning agents can retrieve and reason over Ardoq data but cannot directly modify it. We are actively working on read/write capabilities.

When write operations are introduced, they will follow Ardoq’s human-in-the-loop model. Any proposed changes will be generated in a separate Scenario and require explicit user review and manual merge before affecting live architecture data.

No. Customer data is never used to train external AI models.

Your data remains within your Ardoq environment and is used only to generate responses at query time.

You can review Ardoq’s AI governance approach in the following resources: