From aspiration to achievement: How revenue AI emboldens leaders to embrace the present and reimagine a fresh future

Revenue leaders have long known what success looks like: A sales team operating at peak performance, with every rep executing winning strategies, and every deal progressing with precision. We’ve had the vision of what sellers should achieve, but haven’t had a way to get there because we’ve been limited by the lack of data and technology.

The vision was never the problem. The problem was that, win or lose, it was largely educated guesswork.

Revenue AI is changing all of that. What was once aspirational is now achievable. The technology that emerged just a few years ago has matured into a powerful engine that enables revenue teams to execute at unprecedented scale and speed, transforming vision into reality with less effort and faster results.

The question is no longer whether your team has the talent to succeed. It's whether you have the systems in place to unlock that talent. To get there, revenue leaders must leave traditional selling methods in the past, understand how revenue AI is transforming the present, and grasp what it can do for their teams in the future.

Let’s analyze this transformation through three illustrative examples:

Past: Many revenue teams suffered from poor data quality and little to no automation, which limited their ability to use the data they had to derive insights quickly and at scale. The vision existed, but there was a gap between where revenue teams were and how they should get there.

Present: Revenue AI makes it much easier to gather high-quality data at scale, enabling real-time, prescriptive action based on high-fidelity data. Now, sellers have access to data and AI insights that automatically prescribe specific actions, eliminating the need for help from a data team.

Future: Less guesswork and the ability for data to drive more autonomous action means more winning motions for every rep.

Past: Revenue leaders would spend up to 12 hours each week in one-on-one calls with sellers. Instead of working on coaching or helping sellers move their deals forward, this time was largely spent on deal status updates.

Present: Automation eliminates this administrative background work. This is where The Gong Revenue AI Operating System can come in to deliver a summary of past actions and where the seller has found the most success. It’s easy for managers to review Deal Boards, identify areas of opportunity, and focus on the areas where the sellers need help.

Future: Having this information at the ready transforms 12 hours of low-impact activity to two hours of high-impact coaching per week, with a much greater focus on high-value, deal-driving activities. Revenue leaders will have more time to dig into execution and guide sellers through the work that will help them achieve more.

Past: Each member of a revenue team used to assume their gut feelings would guide them to closed-won. Sometimes it did and sometimes it didn’t, but there wasn’t a track record, making it hard for new or underperforming team members to learn from consistently winning sellers.

Present: There’s a direct connection between seller confidence and seller performance. The best way to build seller confidence is for revenue leaders to give them an objective path to success, and revenue AI does this in minutes. Instead of relying on gut instincts, revenue AI helps revenue leaders and their teams discover the strategies of the most successful sellers and build an automated playbook.

Future: By tailoring processes and automations to match the workflows and actions of the most successful sellers, everyone can learn how to win faster and with fewer mistakes. Being able to follow a proven success route instills the confidence necessary to reach revenue growth.

The present holds so many possibilities, and revenue leaders can make sure their teams aren’t stuck in the past by leveraging revenue AI in these three plays:

1. Out-quarter pull-forward: Use forecasting solutions to identify large deals set to close in the next quarter, then connect with managers and reps to determine which levers they can pull to move the deal into the current quarter. This transforms guesswork into a strategic, calculated acceleration of revenue.
2. Objective-first: Establish a standard practice for managers to use AI-generated deal summaries and review those insights before a call so they spend no time playing catch up and all of their time on a single objective.
3. The best-seller cadence: Identify the actions, talk tracks, and deal hygiene used by your most successful sellers. Then, work within the Gong Revenue AI Operating System to automate the process so that it becomes the default workflow.

The biggest problem in revenue management was never the talent of our teams, but the gap in our systems. Revenue AI is making that a thing of the past, allowing our teams to move away from piecemeal data to data that’s not just informative, but actionable.

We don’t have to ask revenue leaders what their teams could be doing. Now, the question is how quickly they can deploy the right systems so businesses can realize the returns of a revenue team that’s firing on all cylinders.