Written by Paige Fowler, 07/17/2025
When IBM first introduced Planning Analytics AI-powered features, the question on everyone’s mind was: “Is this just another shiny tool—or will it actually change the way I work?” Spoiler alert: it’s both.
At Lodestar Solutions, we’ve spent years working with clients across industries to modernize their financial planning, forecasting, and reporting. We can confidently say that the AI features in IBM Planning Analytics aren’t just cool—they’re crucial. Here’s why.
What Is the Integrated AI Assistant?
IBM’s AI Assistant in Planning Analytics leverages natural language processing and machine learning to help users interact with their data more efficiently. Whether you're a seasoned TM1 modeler or a business user with minimal technical skills, this assistant can guide you, generate insights, and surface trends without requiring you to build complex queries.
Let’s break down a few real-world examples of how it’s being used today.
1. Natural Language Querying (NLQ): Ask, and You Shall Receive
Gone are the days of digging through dimensions and subsets to find the right data. With NLQ, users can ask questions like:
- “What were total sales by region in Q2?”
- “Show me a breakdown of expenses by department for 2024.”
The AI assistant interprets your question, fetches the relevant data, and even builds a visualization—instantly.
Real-World Use Case: A VP of Finance needs a quick visual for an executive meeting. Instead of asking IT or opening multiple views, they type a quick question into the AI assistant and get a chart-ready answer within seconds.
2. AI-Powered Forecasting: Accuracy with a Click
Predictive forecasting is no longer a luxury—it’s a necessity. Planning Analytics now includes AI-assisted predictive modeling that helps you forecast future trends based on historical data.
No need to be a data scientist. You can select a time series, and with a single click, the AI assistant will run multiple algorithms behind the scenes and pick the most accurate model. The result? Smarter decisions, faster.
Want more tips on improving model performance before forecasting? Check out Why Your TM1 Model Is Slowing Down—and How to Fix It.
3. AI Assistant for Planning Analytics Workspace (PAW)
In the latest releases of PAW, the AI Assistant helps with more than just querying—it guides users through common tasks like:
Building visualizations
Creating explorations
Navigating dimensions and hierarchies
Identifying insights and outliers — The assistant can surface unexpected trends or anomalies in your data, helping you spot issues before they become problems or discover opportunities you might have overlooked.
It’s like having a Planning Analytics expert at your side 24/7.
Demo Scenario: Imagine a new analyst joins your team. Instead of spending hours training them on the structure of your TM1 cubes, they can use the AI assistant to explore and self-learn how your data is modeled—while producing real insights.
Why It Matters
The AI capabilities in Planning Analytics aren’t just bells and whistles. They represent a major shift in how teams collaborate with data. Whether you're creating driver-based budgets or tracking KPIs in real time, AI enables:
- Faster decisions
- Greater self-service
- Smarter planning strategies
WARNING! IBM is sunsetting Architect and Perspectives this October, which means you MUST transition to Planning Analytics Workspace (PAW)—where these AI tools live.
So… Cool or Crucial?
We say both. The AI features in IBM Planning Analytics make your life easier—and your planning smarter. In an environment where agility and accuracy are everything, AI is no longer optional. It’s the edge.
Ready to Leverage AI?
If you’re curious about the full capabilities of Planning Analytics AI or want help setting up predictive models, we’re here to help. Join one of our upcoming training sessions or contact us for one-on-one consulting at services@lodestarsolutions.com.
In the meantime, explore more game-changing features in What’s New in Planning Analytics Workspace 2.1.11 (104) and keep upgrading your skills.
