Part of the Active Governance Framework™

How to Build Active Governance for AI

Move governance from documentation to active enforcement at the point AI consumes data and acts on decisions.

DATA TILES GUIDE·7 min read·For CDO, CIO, Data Leader·Active Governance

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Why this matters

AI does not pause for governance councils. Without active governance, organizations face invisible risk at machine speed.

The challenge

· Governance is documented but not enforced at runtime.
· AI consumes data with no awareness of policy or trust.
· There is no audit trail of AI-supported decisions.

What good looks like

Policies execute as machine-readable signals, not PDFs.
AI consumption of data is governed at the moment of use.
Every AI decision is explainable, accountable and auditable.

The Data Tiles framework

Stage 1
Codify
Turn policies into machine-readable signals.
What to do
Codify the top ten AI-relevant policies.
Where it gets stuck
Policy lives in slide decks.
How Latttice helps
Latttice attaches policy signals to data products.
Stage 2
Enforce
Enforce policy at the point AI consumes data or acts.
What to do
Wire enforcement into the AI runtime.
Where it gets stuck
No path from policy to runtime.
How Lenz helps
Lenz enforces policy at the point of decision.
Stage 3
Explain
Make every AI-supported decision explainable and auditable.
What to do
Capture decision context and reasoning.
Where it gets stuck
Black-box AI with no auditability.
How Lenz helps
Lenz captures and explains every AI decision.

Practical roadmap

First 30 days

· Inventory the top AI-relevant policies.
· Identify the runtime systems where AI consumes data.

Next 60 days

· Codify the first five policies as machine-readable signals.
· Pilot enforcement on one AI use case.

Next 90 days

· Roll out active enforcement across priority AI use cases.
· Stand up auditing and reporting.

Prioritize

· High-risk AI use cases.
· Decisions with regulatory exposure.

Avoid

· Treating AI governance as separate from data governance.
· Cataloging without activation.

Common mistakes

· Building AI governance as a new silo.
· Documenting policy without runtime enforcement.
· Ignoring the data layer.

How Data Tiles helps

We connect data governance signals from Latttice to runtime enforcement and explainability in Lenz, giving you active governance without rebuilding either layer.

How Latttice enables this

Stage	Challenge	Capability	Business outcome
Discover	Teams cannot find or trust the data behind AI-consumed data.	Latttice publishes data products with business meaning, ownership and trust signals attached.	Faster reuse, less duplication, fewer escalations.
Build	Building AI-consumed data repeatably without replatforming.	Latttice industrializes data product build on top of the existing stack.	Lower cost to build and operate, faster time to value.
Govern	Governance lags behind delivery.	Latttice attaches quality, lineage, ownership and policy signals to every data product.	Active governance without a manual review bottleneck.
Operate	Ownership defaults to IT after launch.	Latttice gives business owners the controls they need to take real accountability.	Sustained business ownership and trust over time.

How Lenz enables this

AI requirement	Capability	Governance benefit	Business outcome
Explainability for AI decisions	Lenz captures decision context and explains the reasoning behind every AI-supported action.	Auditable, defensible decisions.	Confidence to deploy AI on real decisions.
Policy enforcement at runtime	Lenz applies governance signals from Latttice as policy at the point of decision.	Active enforcement, not after-the-fact review.	Risk is managed in the moment, not the audit.
Accountability for AI decisions	Lenz attaches the named human owner and the decision instrumentation to every AI action.	Clear ownership of AI outcomes.	AI is adoptable by the business, not just the lab.