How to meet rising revenue targets in 2025 (When budgets don’t keep pace)

Every revenue leader is facing the same problem right now: targets are rising and budgets aren’t. 

And with the traditional operating model for growth, the math simply no longer works.

Companies are stuck with inconsistent performance across their team, an inability to up-level more sellers to top performers, a burden of unproductive work that keeps teams from executing top performer behavior, and no way to standardize those best practices at scale across the organization.

So, to hit targets in 2025 and beyond, companies need to fundamentally change that operating model.

They need to undergo a complete revenue transformation.

This is possible now with AI — which has unearthed a richer set of insights from unstructured data, paving the way for three key components of revenue transformation that leading companies are adopting:

To explore how some leading companies have successfully leveraged AI to drive this revenue transformation, and hear about the real world results they’ve achieved, I convened RevOps leaders in an open roundtable peer discussion.

Here’s what we learned.

Enabling revenue transformation is reliant on a shift in data. Everything has to stop working entirely off of data entered into a CRM, to instead leveraging AI-powered data that is captured autonomously. There’s no way to get the scale and velocity of data we need for AI without this shift.

Historically if leaders wanted information on a deal, they had to put a mandatory field in Salesforce or send a message out for more information. And that’s a very difficult process to get really deep information in a timely manner.

With AI automatically capturing all contextual data on every single customer interaction, revenue teams build a wealth of unstructured data that generates powerful insights and drives real business outcomes. 

AI-driven data is the necessary fuel for the three components of an effective transformation, helping RevOps leaders:

In the days of CRM-dependent data, uncovering the key behaviors of top sellers was difficult, if not impossible. Management would spend hours listening to sales calls, reviewing inconsistent CRM entries, and oftentimes still come up empty handed.

AI has changed that.

For example, some leaders use AI to close the gap between top performers and the rest of the sellers. This can help lower-performing reps elevate their performance to match a company’s best salespeople. 

As leaders scale top seller behavior throughout their organization, the focus goes next to freeing salespeople from unproductive tasks.

At Klaviyo, Terry Green found his team using four different sales orchestration tools, making it impossible to understand what was actually working. “You can’t really understand what content’s being successful or how these tools are even being used consistently,” he explains. By consolidating on Gong, they eliminated the productivity drain of constant context-switching and created seamless handoffs between teams.

This shift has given Klaviyo’s sales team valuable time back to focus on what actually moves deals forward. And since AI tangibly helps them do their jobs better, sellers instantly recognize what’s in it for them and choose to use the technology not because they’re told to, but because it’s the easiest and most effective path forward.

Once revenue leaders identify key behaviors of top performers, and unlock their team’s productivity so they can properly execute them, the third step is to run the entire organization on new, AI-driven operating rhythms.

At Boomi, Andrea Jones, a leader in Revenue Operations & Productivity, has transformed the company’s sales approach by leveraging AI to optimize their MEDDPIC methodology. Rather than treating all components of their sales process equally, her team uses Gong’s Initiative Boards to identify specific strengths and weaknesses across their organization.

As Andrea explained, “Using Gong’s Initiatives Boards has been extremely helpful for us in taking all the pieces of MEDDPIC and helping our management team understand where we’re strongest and weakest.”

Gong’s AI automatically understands and creates suggestions to fill in the fields of MEDDPIC (or any other methodology), allowing reps and managers to focus on fulfilling key gaps and steps instead of inputting notes manually. This allows Boomi’s enablement team to take a more targeted approach — focusing on improving just two letters of the MEDDPIC framework in a quarter, for example, versus trying to address everything at the same time. 

With AI revealing where they’re strongest and where gaps exist, Andrea’s team is allocating resources more strategically and driving meaningful improvements in their sales effectiveness.

With revenue AI, leaders can ask questions they’ve never been able to ask and get insights that were previously inaccessible.

AI isn’t just another technology — it’s transforming how revenue organizations operate. 

By focusing on business outcomes rather than technology for its own sake, forward-thinking revenue leaders are using AI to build best-in-class teams by scaling top seller behaviors, saving reps’ productivity, and building new AI-powered operating rhythms — even in the face of rising targets and constrained resources.

To get more insights from Andrea, Terry, and more about meeting rising revenue targets, check out our entire conversation here.