AI has moved from experimental to essential.
From copilots in office tools to predictive models in production, it now powers decisions across the enterprise.
But for all the progress, visibility hasn’t kept up.
According to Gartner, only one in five AI initiatives achieve ROI, and just 11% of organizations report clear business value. Meanwhile, 84% of IT leaders say they lack a formal process to track AI accuracy or governance.
As Sean Gibson, Governance, Risk & Compliance Lead at Ardoq, puts it:
“As artificial intelligence becomes central to business operations, organizations need clear visibility and governance over their AI systems.”
For enterprise architects, visibility starts with collecting, analyzing, and transforming information into meaningful insights, empowering decision-makers to bring order, accountability, and confidence to how AI is managed, adopted, and governed across the enterprise.
Ardoq provides the first EA-native AI governance solution, AI Lens, that helps organizations manage and govern AI effectively.
Built by enterprise architecture experts, AI Lens includes ready-to-use Ardoq dashboards to empower architects, CIOs, and CISOs to move from reactive oversight to proactive, transparent AI governance, while keeping human accountability at the center.
Learn more about each of these dashboards, the valuable overviews they provide, and who they benefit most:
The Enterprise AI Value Dashboard provides a high-level view of how AI supports your most business-critical capabilities. It helps organizations track whether AI is being used where it matters most within market-differentiating processes and applications that directly impact performance and innovation.
It visualizes three essential metrics:
Together, these metrics give enterprise architects, CIOs, and business leaders a clear picture of AI’s strategic value, helping them align technology investments with measurable business outcomes.
For more in-depth resources on AI governance, the latest trends in EA innovation, and our prompt engineering guide for EAs, visit our AI Resource Hub.
This dashboard shows all AI systems across the enterprise and helps answer an increasingly challenging question: “Where are we using AI, and who owns it?”
AI adoption often starts organically: a department experiments with an AI tool, or a team embeds a model into a product. The result? A growing, untracked sprawl.
💬 As Simon Field, co-author of AI Lens, notes:
“Governance starts with visibility. You can’t manage what you can’t map.”
In Ardoq, linking an application or service to an AI capability automatically registers it as an AI system. This builds a living inventory without manual overhead.
In the example above, most AI systems are classified as applications (88%), while technology services make up a smaller portion (12%). This highlights how embedded AI has already become in core business systems, not just technical infrastructure.
The lifecycle data shows that 82% of AI systems are live, 9% are being implemented, and only a few are being phased out, signaling rapid operational adoption rather than experimentation.
Tracking these trends over time helps enterprise architects answer key leadership questions:
EAs can dive deeper into any of these charts, e.g., explore the AI system dashboard to see which department or applications consume this AI.
With these insights, EAs can give the CIO and CISO a clear picture of AI adoption and maturity, supporting more informed investment and risk management decisions.
This Data Usage View in the Ardoq platform is a part of the AI Management assets and helps trace how AI systems consume and share data.
The view above reveals how AI models interact with sensitive or business-critical data. For example, how customer information flows from CRM tools through machine learning models and into analytics platforms. Understanding these relationships helps ensure data governance policies extend all the way into AI use.
“If you want to understand what your AI is doing, you have to start with what data it’s using, and where that data ends up.”
- Simon Field, Senior Enterprise Architect and Co-author of AI Lens
Ultimately, this gives enterprise architects the data transparency needed to keep AI explainable, trustworthy, and well-governed across every system.
The AI Governance Dashboard gives enterprise architects and compliance leaders a single view of all AI systems across the organization. Its purpose is to make AI oversight tangible, turning complex governance requirements into measurable, visual insights. It helps answer key questions like:
This dashboard is especially valuable for CIOs, CISOs, and Heads of Compliance who need to report on AI adoption and regulatory readiness without chasing spreadsheets or struggling with disconnected tools.
In the example above, 42% of AI systems are compliant, while 52% have not yet been assessed, and five systems currently lack an assigned owner. These aren’t just numbers; they’re early warning signals for potential risk and accountability gaps.
“Non-compliance can be costly, with fines reaching up to €35 million or 7% of global turnover. For organizations developing or deploying AI, traceability, documentation, and governance are absolutely essential.”
- Sean Gibson, Governance, Risk, and Compliance Lead at Ardoq
This dashboard tracks compliance assessments, renewal cycles, and AI health checks, showing how AI systems perform against key principles such as transparency, accountability, and security. It transforms compliance from a static report into a living process that evolves alongside your AI landscape.
“By embedding compliance into enterprise architecture, organizations can move from reactive to proactive AI governance.”
- Sean Gibson
The result is a continuously updated, audit-ready overview of AI accountability: one that helps you prove, not just claim, that your AI is being managed responsibly.
When AI governance links to performance, it earns a permanent seat at the strategy table.
Watch this demo to explore all the insights you can gain in Ardoq for AI Management and Governance.
These pre-built assets monitor AI compliance and readiness and answers:“Are our AI systems compliant, and can we prove it?”
The EU AI Act has made compliance a strategic concern, not a side project. Non-compliance can now cost millions.
AI Lens allows organizations to schedule, document, and renew compliance assessments directly within their architecture, linking every AI system to its risk classification, audit record, and evidence trail.
In this example, the EU AI Act Overview Dashboard helps organizations translate complex regulatory requirements into a clear, actionable compliance picture. It’s designed for compliance leads, risk managers, and enterprise architects who need to demonstrate readiness under the world’s first comprehensive AI regulation.
With this you can instantly see how your organization is performing against the regulation. In the example, the dashboard shows:
Each unmapped requirement represents a potential compliance gap from ensuring human oversight to maintaining technical documentation to monitoring high-risk AI systems.
“The EU AI Act classifies systems by risk, from minimal to high. High-risk AI, such as recruitment or education systems, carries strict requirements for data governance, transparency, and human oversight.”
- Sean Gibson
The model view in the Ardoq platform complements the dashboard by showing how each article of the EU AI Act connects to established frameworks such as NIST AI Risk Management Framework or ISO/IEC 42001. This allows you to visualize dependencies between policies, controls, and AI systems, ensuring nothing falls through the cracks.
For CISOs, this dashboard provides evidence of regulatory alignment and helps prioritize high-risk areas. For CIOs, it gives a real-time overview of compliance progress across business units.
And for enterprise architects, it brings structure to complexity, showing how governance connects directly to architecture and business outcomes.
“With Ardoq, compliance is no longer a checklist. It’s a living, data-driven process that evolves with your AI landscape.”
- Sean Gibson
This dashboard transforms regulation from a static burden into a manageable, visual workflow, ensuring your organization stays ahead of both auditors and competitors.
The AI Health Dashboard provides a continuous pulse check on the ethical, operational, and technical health of your AI systems. It helps enterprise architects, compliance leaders, and risk managers identify where governance is working and where immediate attention is needed.
The dashboard tracks AI health checks across core principles, including Bias Mitigation, Transparency by Design, Accountability, and Security and Robustness. Each principle is scored for both importance and concern, creating a clear picture of priorities. For instance, while “Security and Robustness” and “Transparency by Design” may be performing well, “Accountability” or “Bias Mitigation” might surface as higher-risk areas requiring prompt action.
From the dashboard, architects can drill down into a heat map view that visualizes these principles in terms of importance versus concern. This helps leaders see at a glance which dimensions of AI ethics and safety are most pressing for any given AI System. The bubble chart above shows the a health check of a specific AI System, showing what is important for that system's context and which principles are causing concern in their implementation.
For CISOs, this means clear visibility into AI’s alignment with ethical standards and security expectations. For enterprise architects, it provides a structured, visual way to examine key AI Systems and achieve continuous improvement by looking across the whole portfolio. For business leaders, this visibility gives confidence that AI is not just compliant, but trustworthy and sustainable.
The result: a transparent, data-driven approach to responsible AI. One that turns oversight into actionable insight and keeps governance aligned with business outcomes.
Want to see how Ardoq brings EU AI Act compliance to life? Watch the full demo below.
As AI becomes embedded in every part of business and technology, the role of enterprise architects is changing fast.
What was once a discipline focused on systems and standards is now expanding to include governance, communication, and strategic alignment.
That shift creates both opportunity and responsibility.
In this new era, visibility, communication, and ethical awareness are just as critical as modeling and design.
Enterprise architects are becoming the bridge between innovation and control, ensuring AI is not only implemented efficiently but governed responsibly.
See how Simon, co-creator of AI Lens, envisions AI helping enterprise architects do their jobs better:
The Ardoq platform continues to rapidly evolve alongside the growing importance of AI governance, empowering Enterprise Architects to take a central role in ensuring responsible, transparent, and value-driven AI adoption. By handling the manual work, Ardoq lets them focus on what truly matters - connecting people, communicating insights, and guiding the organization toward trusted AI maturity.