AI in forecasting: The CFO’s next big imperative

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Focused on forecast fidelity? Outreach’s AI helps teams move from reactive forecast calls to more proactive pipeline inspection and deal execution. That means fewer end-of-quarter scrambles and probably fewer sweaty palms around the office. Learn more.

Gone are the days when forecasting was simply a sales reporting exercise. It’s now become a CFO-level business discipline with a major ripple effect.

Particularly in a volatile market like the one we’re seeing now, forecasts can shape decisions around hiring, investment, capacity, board expectations, and growth strategies. And when forecast confidence is low, nearly every downstream decision becomes more difficult.

AI presents a unique opportunity for finance leaders in their forecasting efforts. So we teamed up with Outreach to learn what challenges exist, what can be addressed by AI, and what that looks like in practice. Here’s what we found.

The data dilemma

When it comes to forecasting challenges, most teams aren’t dealing with a lack of data; they’re dealing with disconnected data. Revenue teams often have signals spread across CRM records, seller activity, and customer conversations. When those signals stay siloed, finance and sales can end up debating whose version of the pipeline is correct instead of aligning on what to do next.

Finance and sales teams are two socks that make a pair—they need one another. Sales teams bring an understanding of deal nuance, buyer behavior, and customer momentum. Finance teams bring an understanding of planning discipline, risk evaluation, and business accountability. So what can build trust between these two? A shared view of pipeline reality is a great place to start. And to do that, both teams need to work from the same set of signals.

AI in forecasting

One of the main goals behind AI-driven forecasting is to make pipeline risk easier to see, inspect, and act on. AI can help teams identify changes, spot emerging risk, and understand whether the forecast is grounded in real pipeline activity. And it should do it faster with less manual effort.

For finance leaders, choosing what AI makes sense for forecasting often comes down to measurable impact. Does it strengthen pipeline quality? Does it allow for more confident planning, better visibility, and fewer surprises?

Those are the questions that Outreach has answers to. The forecasting capabilities on their agentic AI revenue platform has features like automated rollups and scenario modeling that help teams deliver predictable, accurate forecasts.

The platform can also create AI projections of where the team might finish, intraquarter models that identify potential new opportunities, and parallel forecasting with previous periods. And the impact is sharp—the automated rollups alone reduce forecast prep time by 44% on average.

The forecast on forecasting

The future of forecasting is looking more and more cross-functional. In practice, that looks like revenue leaders, finance leaders, and frontline teams all coming together to share context, inspect risk together, and align earlier on what needs to change.

Teams using Outreach adopt an always-on practice with forecasting, without a major manual lift. Because their platform unifies engagement data, deal activity, conversation intelligence + insights, and pipeline context, leaders and sellers can take a more informed look at sales activity. And from that look, action follows.

As Outreach CFO Drew Laxton noted, “Forecast confidence shapes almost every planning decision we make, from hiring and investment to the commitments we make to the board. AI earns its place here when it gives finance and revenue a single view of the pipeline and surfaces risk early enough to act on. That kind of always-on visibility is what lets finance plan with conviction.”