Video · November 18, 2025
From reactive to proactive: AI in FP&A
About this video
Explore how AI is transforming FP&A from backward-looking reporting into proactive business guidance. OneStream’s Tiffany Ma and Praj Chatterjee discuss automated forecasting and analysis, unified financial and operational data, and generative AI applications. Learn why trusted data and strong guardrails are essential for delivering reliable insights, accelerating decisions, and positioning finance as a strategic partner.
Key takeaways
- Shift finance from reporting to guidance. AI enables FP&A teams to move beyond backward-looking reports and provide proactive, forward-looking insights that help the business navigate volatility.
- Turn finance into an early warning system. Early adopters use AI to automate rolling forecasts and combine financial data with operational signals from sales, HR, supply chain, and CRM systems to identify outliers quickly.
- Build a trusted data foundation first. Clean, harmonized, secure financial and operational data is essential for producing actionable insights, maintaining stakeholder trust, and reducing compliance risks.
- Automate routine FP&A work. Automating forecast creation, variance analysis, reconciliations, and recurring reports shortens cycle times and frees finance teams to model scenarios, test assumptions, and influence decisions.
- Apply generative AI with guardrails. Generative AI can summarize results, draft management commentary, and answer natural-language questions, but it must operate on trusted data with appropriate controls to limit hallucinations and compliance risks.
Read Full Transcript
Welcome, everybody, to Finance AI Academy by OneStream. My name is Tiffany Ma, Global Director of Product Marketing for AI and Operational Analytics.
I'm joined here today with Praj Chatterjee to talk about AI and FP&A. Thank you, Praj, for being here with us today. Thanks for having me. Hi, everyone. So, Praj, you recently hosted a webinar with Accenture where you focused on AI and how it can help finance teams shift the focus from backward-looking to more forward-looking insights. Can you tell us a little bit about that? So, traditionally, finance has looked backwards, reporting on what's happened the last quarter.
But in today's volatile environment, leaders want to know what's next, and that's where finance comes in. The business looks to finance for that guidance.
What AI does, and what we discussed during that webinar, was that AI helps FP&A take the leap from reactive reporting to more proactive guidance and help the business steer forward. One of the concepts you discussed in the webinar was reinventing finance with AI. Can you talk a little bit more about what you're seeing with customers of early adopters of AI? Early adopters aren't just experimenting with AI. They're reinventing the way FP&A operates as a whole. For example, there are companies that are using AI to automate the rolling forecasts weekly instead of quarterly.
They're also using AI to integrate operational signals from supply chain, HR, sales, CRM, or whatnot.
And integrate that with financial data to spot outliers instantly. And the impact is that finance, again, becomes an early warning system, not just a scoreboard. One of the critical success factors that you mentioned in the webinar for AI adoption was data readiness.
Can you talk about why it's so critical and what happens if organizations overlook this? AI is only as good as the data feeding it. If the data is siloed, if it's inconsistent or incomplete, the models just produce noise. Companies that jump into AI without clean, harmonized data, they might get nice, flashy dashboards, but there's no actionable insights. And worse, leaders and the business that finance supports, they lose trust in finance. So the best practice is establish a unified data foundation first.
With OneStream, for example, that means you can pull your financial and operational data into a single platform so AI learns from a single version of the truth. Let's switch to another topic that you discussed in the webinar, which was automating FP&A processes.
Can you talk about what parts of FP&A can be automated and how that benefits the organization? Sure. For things like forecast creation, variance analysis, reconciliations of your data, even routine reporting that FP&A needs to do, that can all be automated.
And the benefit of this is that the automation, it reduces the cycle times. It eliminates all the repetitive work and really gives finance the time to run more what-if scenarios, test different assumptions and spend much more time influencing decisions.
Think of it as less janitor work and more strategic partner work. One of the hottest topics in AI over the past two years has been generative AI. With tools such as ChatGPT, Microsoft Copilot, Google Gemini and others becoming mainstream, how can organizations leverage generative AI and FP&A to drive business value? Great question, Tiff. And you're right.
Tools like ChatGPT and Copilot, they've gone mainstream and finance is starting to experiment. The opportunity here is that Gen.AI can summarize financial data, help you draft management commentary, or even answer ad hoc questions in natural language. For example, things like what's driving Q2 variants in Europe? It also helps democratize insight.
Business users who aren't finance experts can engage directly with the finance data. While FP&A, they can spend much more time validating insights and advising the business. Now, there are some cautions, however. You need to have guardrails in place.
The Gen.AI needs to sit on top of trusted, secure data, sources like OneStream, in order to avoid hallucinations or compliance risks. Praz, thanks so much for taking the time to join us today and finance AI powered by OneStream. Really appreciate you taking the time and sharing your insights with us. Thanks, Tiff. Had a great time here with you and everyone else and looking forward to being here again.
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