Business data & reporting
Pull numbers from the systems you already use into one place an agent can analyze and explain.
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Data governance is how an organization decides who owns data, who can access it, how accurate it must be, and how long it is kept. AI raises the stakes: assistants and agents can read and copy data at machine speed. Good governance makes AI answers more trustworthy and leaks less likely.
IBM describes data governance as the data-management discipline focused on the quality, security and availability of an organization’s data. It defines the roles, rules and processes for how data is handled. AI raises the stakes, because assistants and agents can read and copy data at machine speed.
An example classification (IonBin’s illustration, not a standard):
| Class | Examples | AI rule of thumb |
|---|---|---|
| Public | Website copy, published prices | Any approved tool |
| Internal | Plans, meeting notes | Business-plan tools with training turned off |
| Confidential | Contracts, financials | Named tools only, owner approval |
| Personal | Customer and employee details | Only where your legal basis and the vendor’s terms allow it |
Pull numbers from the systems you already use into one place an agent can analyze and explain.
Hand repeat admin (receipts, logs, notices, handoffs) to workflows your agent can trigger.
Not tool-specific. See Agent-ready for connector support by tool.
Levels come from each tool's recorded, sourced compatibility. How the levels work.
Practitioner views are restated in our words and labeled as views, not measured results. Product facts come from official sources dated above.
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