Financial planning is entering a new phase of maturity. Long centred on rigid cycles and models that are often complex to maintain, it is now evolving towards more dynamic approaches driven by artificial intelligence.
In this context, Planful announces the launch of Planner Assistant, a feature designed to bring together two worlds that are still too often disconnected: financial analysis and decision-making.
Bridging the gap between analysis and forecasting
Within finance departments, current tools generally make it possible to understand what has happened: reporting, variance analysis and consolidation.
However, quickly turning these analyses into reliable forecasts or actionable scenarios remains a slower process, often dependent on manual manipulation or complex models.
With Planner Assistant, Planful offers a different approach:
enabling finance teams to move from analysis to forecasting, and then to simulation, within the same environment and without disruption.
Planning driven by natural language
One of the key developments introduced by Planner Assistant lies in the use of natural language.
Users can query their data, generate forecasts or adjust assumptions simply through text-based instructions.
This approach aims to:
- accelerate planning cycles
- reduce reliance on technical models
- make forecasting more accessible to business teams
The aim is not to replace existing models, but to make them more agile and more usable on a day-to-day basis.
Anticipating rather than reacting
Beyond forecast generation, Planner Assistant introduces a logic of continuous monitoring of financial data.
Thanks to signal detection mechanisms, the tool can:
- identify anomalies or emerging variances
- provide early alerts of potential impacts
- provide context to support decision-making
This ability to anticipate marks an important evolution: the finance function is no longer limited to explaining the past; it is gradually becoming a key player in forecasting and anticipation.
Scenarios built in real time
Another notable contribution is the ability to model scenarios on demand.
Teams can test different assumptions: revenue trends, cost variations and operational changes — without having to rebuild their models entirely.
This flexibility makes it possible to:
- explore strategic options more quickly
- adjust plans continuously
- better align planning with operational reality
AI grounded in company data
Planful also places emphasis on the reliability of the results produced.
The projections generated by Planner Assistant are based on:
- existing financial data (P&L, general ledger)
- analysis of trends and seasonality
- identification of the main performance drivers
According to the publisher, the aim is to ensure outputs that are consistent, explainable and directly actionable, .
A central challenge: trust and governance
In a context where the use of AI in finance raises questions around control and security, Planful highlights several core principles:
- data remains strictly within the customer environment
- it is not used to train external models
- existing access rights and governance rules are respected
This approach aims to facilitate the adoption of AI in demanding environments, where traceability and compliance remain essential.
A new standard for financial planning
With Planner Assistant, Planful is not simply offering a new feature; it is contributing to a broader evolution in financial planning.
The change is clear:
- move from static cycles to continuous planning
- reduce the time between analysis and action
- enable finance teams to play a more strategic role
As companies operate in increasingly volatile environments, this ability to adjust forecasts quickly and inform decisions could become a decisive advantage.
source: Planful
