Cube is evolving its approach to artificial intelligence with the launch of AI Hub, a new space designed to make AI easier for financial planning and analysis (FP&A) teams to use. The aim is to enable finance professionals to query their data and launch analyses using questions phrased in natural language, without having to determine which tool or agent to use themselves.
Charlie, a single entry point for financial questions
At the heart of AI Hub is Charlie, Cube’s AI assistant. Users can ask it questions directly about their financial data, for example to understand a budget overrun, analyse cash flow trends or identify the main variances between actual results and the budget.
Charlie interprets the request and automatically routes it to the most appropriate agent team. Users therefore do not need to know the relevant scenario, report or agent in advance.
Four agent teams for different FP&A needs
AI Hub also offers a catalogue of ready-to-use prompts organised around four agent groups: Analysts, Planners, Business Partners and Data Managers.
Analyst agents cover areas including variance analysis, reporting, month-end close, and analyses related to revenue, expenses or headcount. Planners focus more on budgeting, forecasting and scenario modelling.
Business Partners are geared towards preparing summaries for executives, boards of directors or investors. Finally, Data Managers provide analyses focused on data quality, financial hierarchies and close processes.
Prompts that can be adapted to team needs
Cube does not limit its catalogue to fixed templates. Each prompt can be modified before execution to adapt it to the relevant periods, departments or entities.
This capability enables finance teams to start with an already structured use case while retaining the ability to tailor it to their own context. A budget scenario, variance analysis or financial projection can therefore be prepared based on a request defined more precisely by the user.
AI integrated directly with financial data
One important aspect of this new approach concerns data access. Queries made through AI Hub remain subject to each user’s access scope in Cube.
In practical terms, if someone does not have the necessary rights to view a scenario, entity or dimension, the AI agents cannot access it on their behalf. Administrators can also define the AI parameters and features available to their organisation.
AI closer to everyday FP&A use cases
With AI Hub, Cube is primarily seeking to bring artificial intelligence closer to the tasks finance teams already perform on a daily basis. The challenge is no longer simply to have an assistant capable of answering a question, but to connect this capability to concrete processes such as variance analysis, forecasting, budget planning or the preparation of financial materials.
This development reflects a broader trend in the EPM market: AI is gradually being integrated into the tools used by finance departments, with the aim of reducing the time spent on certain analytical tasks and enabling teams to focus more on interpreting data and making decisions.
Cube nevertheless points out that AI-generated results should be verified before being used in a decision-making process. AI Hub is therefore presented more as a support tool for FP&A teams than as a substitute for their financial expertise.
source: Cube
