Will revenue AI finally kill forecasting spreadsheets? Here’s my prediction.

The pressure to hit your sales intake number is relentless. But for years, forecasting was a deeply subjective and flawed process. I’ve seen a sales director manually adjust his personal and painstakingly created spreadsheet to account for whether Bob was too optimistic or Jane was too conservative about commit numbers.

That era is over. Now, revenue AI gives revenue teams a common, transparent language.

It has moved us all from reporting on what happened in deals to understanding why it happened. This is leading to more predictable revenue and sales teams that focus on the right deals. Three core principles of revenue AI use can make this happen quickly inside a sales organization:

Forecasting and sales strategies hinge on AI-powered buyer intent data. Revenue AI can assess a deal's vitality and the intent of the entire buying group, not just a single contact. By integrating data from various touchpoints, including crucial LinkedIn engagement, revenue AI identifies key players within a company. This allows sales teams to focus their energy on the deals and individuals that offer the best chance of winning. This intentional approach directly addresses our perennial challenge of getting more revenue from the same staff.

We need to do more with less, which means maximizing the time our team spends selling. No salesperson I've ever met enjoys updating CRM. The Gong Revenue AI Operating System, through its connection to Salesforce, streamlines their time and, crucially, helps them know where to put their energy. We're seeing sales teams sometimes rank their deals based on size (biggest to smallest) and focus solely on that one large deal. But that $100,000 deal might only have a 10% chance of closing, while five smaller deals could be a near certainty. Revenue AI is helping us understand where our sales team should be putting their energy, who's using it in the right place, and who's working efficiently. This shift will not only boost numbers, but also a team's morale, as they can focus on the deals that truly matter.

Despite being tech-forward, your revenue AI transformation should still stand on one repeatable ritual: weekly meetings. I operate in a monthly forecast organization, but every Wednesday we hold a pulse call where managers review our collective progress.

Crucially, every Monday morning, every seller has to enter their personal forecast for the month. Historically, that number was the sum of their commit deals in Salesforce. With revenue AI, we now encourage our sellers to submit a number based on their experience and what the platform — in this case, Gong — is telling them. AI's prediction is vital here, and Gong gives us a better prediction than the sellers do, especially in the first two weeks of a month. Our sellers were sometimes too low initially, but revenue AI’s reference point forces them to recalibrate quickly.

This visibility has revolutionized our accuracy. We consistently hit within a few points of quota every month, which allows senior leadership to trust the figures they get from us. If you can say in week two that you know where you’re going to be at the end of the month, and you get within five percent, that predictability is invaluable. That’s true not just for sales, but for the entire organization.

We also still hold monthly, one-on-one reviews in which managers use the Deal Board to understand their deals. We’re no longer at that stage where a seller can tell their manager, "This deal's really hot," only for the manager to look in the system and say, "You haven't spoken to them for three weeks, and there's no finance director on the deal." We’re all working from the same Gong Revenue AI Operating System insights, and there’s no hiding from it. No guessing. No BS.

When you’re backed by accuracy, you have the power to kill bad deals. I’ve known companies with millions worth of rolling open pipeline, some of which has been pushed 10 times or more. This “fake” pipeline skews expectations and wastes valuable time.

But now you can track push counters. If a deal has been pushed numerous times and revenue AI scores it low due to a lack of activity, kill it off. This focus ensures that reps and managers concentrate on the deals where they genuinely have a chance of winning.

Revenue AI can also help you eliminate damaging sandbagging traps. Previously, a high-performing seller might hold a deal from December to January to give themselves a head start. With the transparency that revenue AI provides, that behavior is massively reduced. When your sales director and salespeople see the same data, it’s plain when someone’s being overly conservative or optimistic.

Ultimately, revenue AI is about combining years of sales experience with a perfect, unbiased view of the data. It helps sellers make better decisions without replacing their judgment. When revenue AI provides a simple nudge, like “Gary from Widgets.com sent you an email three days ago, and you haven't replied,” it ensures that you never drop the ball. It’s an easy lift, and when you use those suggestions, you convert more customers.

As part of Gong’s Customer Advisory Board, I’ve heard great use cases that focus on this perfect pairing. It’s allowing scale without sacrificing control, and perhaps more importantly, it’s made a very high degree of predictive accuracy possible without a single spreadsheet in sight.