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Artificial intelligence is redefining the boundaries of what’s possible in go-to-market execution. But for the modern Chief Revenue Officer (CRO), AI tools alone won’t solve for churn, inefficient workflows, or low conversion rates. The CROs who win in this new era are those who rethink their entire revenue strategy around what AI can enable, not just automate.
That’s the central thesis of our latest AI Advantage webinar, where we sat down with Warren Zenna, Founder of the CRO Collective, and hosts Jonathan Kvarfordt (Head of GTM Growth at Momentum) and Cristiano Mendes (VP of Sales at Momentum). Together, they unpacked how top CROs are evolving their role, optimizing decision-making, and building scalable, AI-driven revenue operations that move metrics.
Let’s explore what today’s high-performing revenue leaders need to know and what tomorrow’s top performers are already doing.
The Changing Mandate of the CRO
Today’s CRO is more than a sales leader. They are the orchestrator of revenue-generating initiatives across the entire customer journey, from marketing campaigns to upsell motions to long-term customer retention. But despite their expanding remit, many CROs are still confined by legacy org structures and unclear accountability.
Warren Zenna pointed out that, unlike a CFO or CMO, a CRO's responsibilities often lack standardization. Some oversee the entire GTM engine. Others are limited to frontline sales teams. This inconsistency creates tension, especially as boards expect AI-powered transformation without providing the authority needed to lead cross-functional change.
“You can’t be responsible for AI-driven revenue forecasting if you don’t control the data, the CRM, or the RevOps team,” Warren noted.
In short, the CRO must evolve from a pipeline operator to a full-stack strategist. That means becoming fluent in artificial intelligence, predictive analytics, and automation. Not just to optimize the sales process, but to align the entire business around real-time signals.
Using AI to Drive Revenue Growth
The CRO’s job is to use AI to deliver revenue growth.
Cristiano Mendes made this distinction clear: “Boards aren’t asking, ‘Did you adopt AI?’ They’re asking, ‘How are you using AI to accelerate decision-making and hit revenue goals?’”
That difference is everything. AI must become a foundational layer in how CROs:
- Detect deal risk based on customer behavior
- Streamline pipeline reviews with data-driven signals
- Prioritize accounts and actions with real-time insights
- Predict churn and identify upsell potential in the CRM
- Optimize pricing strategies and marketing campaigns
CROs don't need to turn into technologists. What they need is the visibility and velocity to lead their revenue teams with precision and impact. And it starts with the data.
Before You Automate, You Need to Integrate
Jonathan Kvarfordt laid out one of the most overlooked truths in revenue operations: “Bad data equals bad agents. No data equals no agents.”
Before CROs can deploy generative AI or AI sales assistants, they need to solve for fragmented data. That means unifying inputs across marketing teams, customer success, RevOps, and sales into one structured source of truth. Often the CRM.
But here's the catch: even Salesforce can’t save you if the fields are empty or the workflows are broken.
Momentum’s platform addresses this gap by capturing structured data directly from emails, calls, and meetings, then syncing it automatically into Salesforce, ready for forecasting models and real-time GTM orchestration. For CROs, this turns the CRM from a lagging indicator into a living source of intelligence.
“If you want scalable AI success, clean and complete data is the shovel,” Warren emphasized. “Before you mine for gold, build the infrastructure to dig.”
CROs as AI Leaders: Why You Must Own the Playbook
One recurring theme from the webinar: CROs can no longer delegate AI strategy to IT or RevOps. They must lead it.
And not just by buying tools, but by creating a repeatable system where AI enhances core workflows and aligns the revenue organization around a shared set of outcomes.
That includes:
- Creating an AI playbook for how automation supports each stage of the sales process
- Training frontline teams on how to use AI tools in real-time, not just in onboarding
- Building feedback loops from reps to managers to the c-suite on what’s working
- Using predictive analytics to continuously refine targeting, forecasting, and enablement
“The CRO of the future is part strategist, part technologist, and part teacher,” Cristiano noted. “They must make AI practical for the teams who use it and measurable for the leaders who invest in it.”
Rethinking Org Structure
AI is reshaping teams and making companies rethink their concepts of headcounts and capacity.
Warren reflected on that and shared a blunt assessment: “Most companies are overhired. We don’t have a people problem. We have an efficiency problem.”
CROs are being told to drive revenue growth with reduced headcount. That means shifting from a hiring mindset to a capacity mindset. Instead of asking “how many reps do we need,” ask “how do we make each rep 30% more effective using AI-powered automation?”
With AI streamlining research, data entry, and follow-up tasks, one sales manager can now manage 12 reps instead of four. One RevOps leader can support 50 reps instead of 15. And one CRO can oversee every conversation, without attending every call.
“AI enables leaner, smarter, more efficient teams,” Jonathan added. “But only if you optimize for capacity, not just coverage.”
Revenue Forecasting in the AI Era
Forecasting used to be a combination of rep intuition and gut checks. Now, CROs are deploying AI tools that analyze sentiment, behavior, and buying signals across every opportunity. And not just the ones that get weekly attention.
Jonathan posed the vision: “What if your forecast was based on actual signal reviews, not just exit criteria? Imagine combining internal CRM data with third-party behavior, like competitor pricing research or website activity, and using that to flag deal movement before reps even report it.”
That’s the future of AI-driven forecasting. No more spreadsheet drama. Just pattern recognition at scale, powered by real-time data and predictive models that actually learn.
The True Role of AI in GTM Strategy
Throughout the conversation, Warren returned to one essential idea: AI is not a silver bullet. It’s a catalyst.
CROs must resist the temptation to chase the latest generative AI trend without grounding it in the fundamentals: clear GTM strategy, well-defined sales process, high-quality data, and aligned cross-functional execution.
He advised CROs to focus their AI efforts on areas like:
- Internal systems optimization (not just customer-facing initiatives)
- Data integration and CRM hygiene
- Sales team enablement and coaching at scale
- Smart automation of repeatable tasks
By applying AI where it creates leverage (not complexity) revenue teams can see exponential value.
“If everyone’s using AI to generate pipeline, the winners will be those using it to fix their foundation,” Warren said. “That’s where the moat is.”
Metrics That Matter: Proving ROI and Performance
To secure executive buy-in, CROs must tie AI initiatives directly to business outcomes. That means going beyond surface-level metrics like tool adoption or email opens.
Instead, focus on:
- Revenue influence: Are AI-powered actions accelerating deal velocity?
- Sales performance: Are reps hitting goals faster, with fewer resources?
- Conversion rates: Is AI increasing opportunity-to-close ratios?
- Customer satisfaction: Is AI improving the post-sale experience and reducing churn?
- Forecast accuracy: Are predictive analytics improving confidence and reliability?
This is where tools like Momentum shine: by surfacing real-time insights that connect AI outputs to revenue-generating results.
AI Should Empower, Not Replace
One of the most thought-provoking sections of the webinar explored how AI intersects with human excellence.
“We believe AI should never replace human relationships,” Cristiano said. “It should empower people to show up better, with more insight, more clarity, and more capacity.”
Momentum’s philosophy reflects this. Our AI prioritizes which conversations matter most, surfaces hidden risks, and suggests coaching moments to elevate team performance.
Rather than replacing frontline managers, AI becomes a co-pilot freeing up time for the high-leverage work only humans can do.
Building a CRO Community
Finally, Warren offered perhaps the most underrated advantage available to CROs today: each other.
With the market moving fast and AI capabilities evolving weekly, CROs must lean into peer communities, roundtables, and shared learning opportunities.
“If you want to lead in AI, talk to people who are already using it,” he advised. “Especially CROs at AI-first startups. They’re learning in real-time. That insight is gold.”
This spirit of shared experimentation, of building in public, testing in the trenches, and iterating fast, is what defines the modern, high-performing CRO.
Final Takeaways: The AI-Powered Playbook for CROs
To close the session, our speakers shared their most actionable advice for CROs navigating this shift:
- Talk to other CROs. Build your bench of peers solving similar problems.
- Audit your data. Fix what’s broken before you try to automate it.
- Own the AI narrative. Don’t wait for someone else to define it.
- Start small, prove impact. Use pilot projects to show wins.
- Focus on leverage. AI should save time, not add tasks.
- Invest in enablement. Tools are only as good as their usage.
- Bridge the gap. Use AI to connect systems, people, and outcomes.
The CRO is now a strategic operator role that lives at the center of growth, customer experience, and GTM alignment. And with the right AI-powered infrastructure in place, it’s the role best positioned to lead the next wave of business transformation.
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