If you’re a TM1 professional and have been near the finance or FP&A world lately, you’ve probably heard the buzzword of the season: Agentic AI.
It sounds fancy and must have wondered why suddenly everyone is talking about it, but honestly, it’s just AI that doesn’t sit around waiting for you to poke it. It does things — proactively and automatically.
And when you mix that with platforms like IBM Planning Analytics / TM1, things start getting interesting.
Imagine if your TM1 rules, processes, and chores had a brain.
Not just “if X then Y”, but something that can:
Notice something’s off
Decide what to do
Do it
Tell you what it did
Learn from the outcome
That’s, in a nutshell, agentic AI in the TM1 paradigm.
Think of it as giving your FP&A stack its own mini team member — minus the coffee breaks or the usual shenanigans that you’ve to bear with daily.
In practical terms, agentic AI can help rather than just be a buzzword decoration floating around in everyone’s LinkedIn posts or formal/informal conversations.
I like to highlight below a few basic things - yet very important – that agentic AI is really good at doing:
Every TM1 admin knows the pain: source system changes, missing records, late files… chaos.
Agentic AI can:
Basically, your nightly chore is that you just hired an assistant.
Instead of a typical TM1 process error message that looks like it was written in 1995, agentic AI can:
Something along the lines of:
“Hey, sales in APAC are 4x higher than normal for Mondays. It could be a missing filter. Want me to check?”
Yes, please.
Sure, TM1 can forecast, and it can predictive forecast really well.
But agentic AI can simulate scenarios on its own and recommend the best one.
Examples:
It’s like giving your CFO a crystal ball… a slightly nerdy one.
This is the part TM1 developers love.
Agentic AI can:
Fix failing processes
Rewrite TurboIntegrator code
Clean up unused object
Suggest how to reduce the cube size
Admittedly, given it's all subjective, and it's easier said than done, but the possibilities do exist with the more quality data we can ingest and the more we can train the model.
We’ve already seen this with AI chat Assistant in PAW where instead of navigating a million cubes and views, we can prompt Planning Analytics such as, “Give me gross margin by product for Q3 vs last year and show me drivers of variance.”
And it does it a fine job.
No view-building. No subset drama. No filter pain.
Finance teams love workflows and agentic AI is perfect for building the workflows.
It loves automating those workflows.
Approve expenses based on policy
Kick off TM1 processes when thresholds hit
Trigger emails, Teams alerts, Slack actions
Update commentary automatically
So instead of actively entering the forecasts or budgets, the agent proactively taking steps to initiate those steps for you.
With time, we’re only going to see more of:
AI agents running close cycles
AI agents building dashboards
AI agents talking to ERP, CRM, S3, APIs without humans touching integrations
AI agents are debugging your model while you sleep
As we know, TM1 is:
Real-time
Calculation-heavy
Highly scriptable
Connected to everything
Used for tons of repetitive work
Which is exactly the playground where agentic AI thrives.
Plus, TM1 developers are already half-cyborg 😉 with the stuff they automate — agents just take it further.
So the biggest takeaway from all of this is that Agentic isn’t coming “in the future”, it's already there! Things are definitely moving and moving at a very fast rate in this space.
It’s already sliding into FP&A tools, APIs, planning models, and the daily grind of finance teams. If TM1 was the engine, then agentic AI is the turbocharger bolted on top.
And yes — as a disclaimer, it might even finally stop your chore from failing at 3 AM for no reason 😉