Part 1 ended with a promise: to show how Data IQ helps organisations activate AI within Microsoft Fabric in a way that’s governed, auditable, and built for enterprise trust. That’s what this part is about.
Part 1 showed how Microsoft Fabric Planning closes the gap between reporting and planning: bringing actuals, forecasts, budgets, scenarios, and planning inputs into the same environment, extending the dashboards teams already use forward instead of replacing them.
But adding AI to that environment raises a harder question. AI can process more information than any planning team – it finds patterns, models scenarios, and suggests next moves in seconds. What it can’t automatically know is whether those moves are realistic for you.
THE BOTTOM LINE: AI can model what might happen. Your planning environment has to teach it what your business can realistically do – and keep it governed, auditable, and trustworthy.
A sensible forecast can still be the wrong plan
Ask AI to recommend a sales target. It studies the trend, spots an upward curve, and suggests a sizeable increase. On paper, it looks sound.
But your leadership team knows what the numbers leave out: the sales team is at capacity, two regions have recruitment gaps, the growth needs more marketing spend than the budget allows, and operations can’t onboard customers that fast without denting service quality.
None of that makes the AI wrong. It makes it incomplete. A forecast is informed by patterns. A plan has to account for people, money, capacity, timing, risk, and strategic intent.
AI can read the map. You still know the territory.
AI is remarkably good at reading the map: finding relationships across thousands of data points, comparing outcomes, flagging exceptions, modelling routes forward. But your people know the territory. Your managers know a profitable product can still be supply-constrained. Finance knows which budgets can move and which can’t. Operations knows where another 10% of demand would break something. The executive team knows which opportunities support the strategy and which would just distract from it.
Four principles that keep AI grounded in your business reality
1. Give AI the house rules before asking for recommendations
Every organisation has house rules – some documented, most carried in people’s experience. AI doesn’t arrive with them. Hand it raw tables without the relationships and rules around them, and it can produce a mathematically reasonable answer that doesn’t survive contact with the business.
Fabric IQ’s Ontology models the things that matter to a business, how they relate, and which rules govern them — giving AI the house rules. Because it lives inside Microsoft Fabric, those rules travel with the data under the same governance, security, and lineage the organisation already applies to its reporting.
In practice:
2. Keep plans connected to the business as it changes
Context is only useful while it stays current. When planning depends on exports and spreadsheet versions, the spreadsheet becomes a separate version of the business – and AI reasoning from it is reasoning from a plan the business has already outgrown.
Fabric Planning’s writeback persists plans, forecasts, targets, and assumptions in Fabric SQL or OneLake, so a manager’s change is immediately available to connected Power BI reports and other Fabric workloads. No exports, no manual bridge-building, no lag.
In practice:
3. Keep the history, not just the latest number
This is where “governed, auditable, enterprise trust” stops being a slogan. Trust isn’t only whether an answer is accurate; it’s whether a decision can be understood later: who changed it, when, why, under what authority.
Fabric Planning’s writeback keeps planning values together with comments, statuses, categories, and approvals, with optional change capture; you can find it inside the same security and lineage that reporting already relies on. That gives planning teams organisational memory and an audit trail that stands up to scrutiny.
In practice:
4. Start with one decision that creates friction
It’s tempting to make AI-enabled planning a company-wide transformation from day one. That usually makes the conversation larger, slower, and more abstract than it needs to be. A more practical starting point is one recurring decision that already causes frustration.
As a Microsoft Partner, Data IQ works alongside your team to identify the highest-friction decision, define the business context, and run a focused pilot – proving value where it’s visible before scaling further.
In practice, the technology should fit the decision – not the other way around:
The view through the windshield
Part 1 was about closing the gap between reporting and planning. Part 2 answers the question Part 1 left open: how do you activate AI within Microsoft Fabric in a way that’s governed, auditable, and built for enterprise trust?
The rearview mirror still matters; it shows you what the organisation has learned. Fabric Planning connects those lessons with the plans you’re building now – and when AI understands the business behind the numbers, the view ahead becomes considerably more useful.