Inside the Conversation: AI-Ready Revenue Leadership
By Tim Daloisio, VP of Strategy & Operations
At our recent Boston event, hosted by Eyeful Media and our partners, Hyperscayle and Syncari, we brought together senior leaders in strategy, operations, marketing, and technology to explore the evolving relationship between AI and Revenue Operations (RevOps). What unfolded was a rich and practical dialogue about building AI-ready organizations, not just tools and data, but mindset, governance, and culture.
The panel included:
Nick Rose, Co-Founder at Hyperscayle
Scott Edmonds, Co-Founder & CRO at Syncari
Angela Cirrone, Sr. Director of Marketing Technology & Operations at Workiva
Tim Daloisio, VP of Strategy & Operations at Eyeful Media
Together, we explored key themes such as data infrastructure, change management, and the challenge of aligning expectations with impact.
Nick Rose, Scott Edmonds, Angela Cirrone, and Tim Daloisio discuss the impacts of AI on revenue leadership at an event at Trillium Brewery in Boston, MA on May 14, 2025.
Here are the highlights:
AI Is No Longer a Future State. It's Now.
Right out of the gate, our panelists agreed: AI is no longer a theoretical discussion. It’s happening now, and it’s reshaping how businesses operate, make decisions, and go to market.
"AI is no longer a future consideration for us—it is here. It's reshaping how we think about execution, strategy, and growth." - Tim Daloisio, Eyeful Media
The takeaway here is urgency: not panic, but preparation. Organizations that still treat AI as a peripheral or experimental tool will be at a disadvantage. From customer insights to predictive modeling, AI already impacts how leading teams plan and execute. The question isn't if AI belongs in your GTM strategy, but how deeply it's embedded across your operations.
"Knowing what you want to do and why is so important. Too often, people say they want to ‘close more revenue,’ but that could involve 15 different things. AI can help with a part of that, but the hardest part is setting clear, narrow expectations. Scoping matters.” - Scott Edmonds, Syncari
Foundational Readiness: Data, People, Process
A recurring theme was that AI fails when foundations are weak. The most common reason AI pilots stall or underdeliver isn't the technology itself; it's the lack of clean, aligned, accessible data, or the absence of transparent processes that AI can enhance.
"We've seen AI make bad data even worse. If you don't unify things like state or region data across your platforms, the insights you get will be meaningless or even misleading." - Nick Rose, Hyperscayle
"Start where you have good data and a good process. That’s the part of the business ready for AI." - Tim Daloisio, Eyeful Media
Foundational readiness is about more than IT hygiene; it’s about trust. When business users don't trust the data, they won't trust AI outputs either. That undermines adoption and leads to shadow systems. The panel emphasized the need for governance and clarity around how data is structured, tagged, and moved between systems. AI should amplify good data practices, not compensate for poor ones.
AI Fluency: Training People to Make Better Decisions
Technology alone isn’t enough. Teams need to know how to interact with AI tools, question outputs, and integrate those insights into their daily decisions.
"You need to train your people to be fluent in how to use the tools, validate information, and build maturity across the organization." - Tim Daloisio, Eyeful Media
"It's about reaching data and insights we never had access to before; research, opinions, even market dynamics. The accessibility is profound." - Angela Cirrone, Workiva
AI fluency is emerging as a core competency for modern revenue teams. It’s not about turning everyone into a data scientist; it’s about giving them the confidence and context to engage with AI outputs critically. This includes knowing how to prompt tools effectively, verify results, and escalate inconsistencies. Organizations that invest in this human side of AI will build more resilient, adaptable teams.
From Pilots to Systems: Building for Scale
A key pitfall for many organizations is treating AI as a siloed initiative, owned by one team or deployed in one use case. That doesn’t scale. Mature organizations embed AI across their systems and decision-making processes.
"It’s not about one pilot system with one pilot team. It has to become systemic, something with structure, process, and accountability behind it." - Tim Daloisio, Eyeful Media
The conversation pointed to the danger of "AI theater," where flashy demos or narrow pilots create excitement but fail to deliver sustained value. The real unlock comes when AI capabilities are integrated into business rhythms and layered across functions, from marketing to sales to finance. That requires strategic intent and operational discipline, ensuring AI isn’t a bolt-on but a built-in.
Effective Decision-Making Is the North Star
Ultimately, the panelists agreed that AI’s true promise is helping teams make better decisions faster and with less organizational effort.
"The effectiveness of a decision is: the speed of that decision × the quality of the process and data × the yield of the result, all divided by the effort it takes to make it." - Tim Daloisio, Eyeful Media
This equation struck a chord with many attendees. AI is most valuable not when it dazzles with complexity, but when it quietly improves the quality and consistency of decision-making. It enables GTM teams to move with speed and precision. But it also reframes the conversation. AI is not just a tactical asset but a strategic lever for leadership.
Clarity of Purpose Is Everything
Many AI initiatives falter because they try to do too much, too soon. The advice? Start small. Focus. Know why you're doing it.
"Knowing what you want to do, and why, is more important than the tools. Without that, even the best AI won’t deliver real value." - Nick Rose, Hyperscayle
This may be the most deceptively simple insight from the event. As one panelist noted, AI is a magnifier; it scales what’s already working and exposes what’s broken. Success starts with tight scoping: identify one or two clear business problems, tie them to measurable outcomes, and build from there. Clarity reduces friction, aligns stakeholders, and creates momentum.
Building Community, Building Readiness
We closed the session with shared optimism: AI has immense potential to reshape revenue teams’ operations, but it requires intention, collaboration, and thoughtful design.
Thank you to our panelists and everyone who joined the discussion.
If you’re interested in learning more about how Eyeful Media and our partner ecosystem can help your organization become AI-ready and your people become AI-fluent, maximizing the potential of AI across your sales and marketing efforts to drive revenue growth, please reach out.