Pigment's latest Office of the CFO research found that only 20% of finance leaders feel confident planning beyond six months. At the same time, nearly every FP&A vendor is now selling some version of AI. That tells you the problem is not a lack of software. The problem is that most teams have added tools faster than they have improved planning.
Most FP&A teams are paying for more capability than they actually use. They buy for the future org chart, not the current workflow. Then six months later, the forecast still lives in Excel, the reporting pack still gets rebuilt by hand, and the shiny new platform is mostly being used as an expensive place to upload numbers.
The Market Is Crowded. The Use Cases Are Not.
Here is the simple version of the landscape as I see it in 2026:
- Anaplan is for real complexity. Multiple business units. Dense driver models. Lots of contributors. Serious scenario planning. When it fits, it is powerful. When it does not, it is too much overhead.
- Pigment is the modern planning platform people bring up when they want speed, collaboration, and a cleaner planning experience across finance, GTM, and headcount.
- Planful is the pragmatic finance-led option. It tends to make sense when you want planning, close, reporting, and consolidation without turning the implementation into a systems science project.
- Adaptive Planning is still the dependable default for a lot of teams. Easier to understand, easier to adopt, and usually a better fit than the heavy enterprise tools for mid-market finance orgs.
- Vena is honest about something many vendors fight: Excel is still where a lot of finance teams actually work. If you want governance without asking the whole team to change how they think overnight, that matters.
- Datarails is the right-size candidate for spreadsheet-heavy teams that need reporting and consolidation to get less painful before they need a giant planning transformation.
That is the vendor view. The operator view is simpler: none of these tools matters if your model is sloppy, your assumptions are unmanaged, and nobody trusts the numbers.
What Is Actually Changing
The interesting split in 2026 is not old vendor versus new vendor. It is workflow-native AI versus demo AI.
Every platform now has AI language in the pitch. Fine. The question I care about is whether the AI is embedded inside the planning workflow or sitting on top of it like a chatbot garnish.
If the system can explain a variance using governed model context, trace where the number came from, update a driver, and show me what changed, that is useful. If it can only summarize a stale export and make the interface look modern, I do not care.
This is why some newer tools feel ahead right now. They were built in a world where teams expect faster model changes, more cross-functional planning, and shorter feedback loops. But legacy vendors are not dead either. If they can embed AI into the actual model, permissions, and workflow layer, they can still win. The divide is not company age. The divide is whether the product helps finance make a decision faster with more confidence.
Not worth your time: features that look impressive in a demo but still leave your team exporting, cleaning, and re-explaining the same data every month.
My Bias, Up Front
I have a simple bias here: I trust adoption more than feature grids, and I trust Excel more than vendor theater.
What has worked for me is never "the most advanced stack." It is a clean driver model, clear ownership, and tools that let the team turn around scenarios fast. What has not worked is buying a platform to solve a process problem the team never defined correctly in the first place.
I have seen teams overbuy this category for years. If you are a lean FP&A team with one legal entity, a handful of department heads, and a monthly forecast, you probably do not need Anaplan. You may not need Pigment either. You may need cleaner data inputs, better spreadsheet discipline, and one layer of workflow and governance.
That is the part people do not like to say out loud because it is not exciting. But it is true. A planning platform earns its keep when the coordination cost of spreadsheets becomes higher than the modeling flexibility spreadsheets give you.
Excel and Sheets are still the right answer more often than software sales teams want you to believe. They break when scale, governance, and coordination break them. Not before.
The Right-Size Stack Argument
Not everyone needs Anaplan. Not everyone even needs a full FP&A suite.
If your team is spending most of its time rebuilding reports, chasing the latest file, and reconciling versions, your first problem is workflow. If your team is spending most of its time changing assumptions, testing scenarios, and rethinking the business model, your first problem is flexibility. Those are different problems, and they should lead to different tool choices.
For a lot of mid-market teams, the right stack is smaller than expected:
- ERP plus CRM as source systems
- Excel or Sheets as the modeling layer
- One workflow or reporting tool that fixes version control, refreshes data, and reduces manual pack-building
That is enough for a surprising number of finance teams. The mistake is jumping straight from spreadsheet pain to enterprise-platform ambition.
The better question is not "Which platform is best?" It is "What is the smallest stack that makes our planning process materially better?"
That answer changes by company stage. A global company with dozens of interconnected models should think very differently from a $50M business with a lean finance team. But the logic stays the same: buy the minimum amount of software required to remove the current bottleneck.
Tool Spotlight: Datarails
Datarails is interesting right now for one reason: it accepts reality.
Most FP&A teams are not abandoning Excel. They want governed data, less painful consolidation, faster reporting, and some AI help without re-platforming the whole finance function. Datarails is compelling when that is the actual problem statement.
That does not make it a universal answer. If you need deep enterprise modeling across many functions and geographies, you will outgrow it. But for a finance leader staring at a spreadsheet-heavy process and wondering how to clean it up without launching a 9-month transformation, it is worth a serious look.
The caution is the same as the appeal: if your spreadsheet layer is chaotic, you can end up governing chaos instead of eliminating it. Use it when Excel is the operating substrate. Do not use it as an excuse to avoid fixing a broken model.
Action Item
Run a 30-minute stack audit this week.
List every tool your FP&A team touched in the last month. Next to each one, write four things: the workflow it supports, who actually uses it, what it costs, and the last decision it materially improved. Anything that cannot pass that test is overhead until proven otherwise.
You do not need another demo before you do that exercise. You need honesty.
Closing
Next issue, I am going to break down how to run an AI pilot inside FP&A without creating a governance mess or wasting a quarter on experimentation theater.
If this issue lands with you, I want the blunt version of your feedback: which tool is your team getting real value from, and which one is mostly shelfware with a good sales deck?