Revenue in the Age of AI: Where Strategy, Technology, and Human Skill Collide
Summary
Everyone is talking about AI—but are revenue organizations actually becoming more effective, or simply adopting more technology?
In this episode of Conversations in the Future of Work, Rachel Cossar sits down with Seth Marrs, Chief Strategy Officer at Sandler, to discuss how AI is reshaping revenue organizations—and why the biggest opportunity isn’t adding more tools, but using them with intention.
Drawing on more than three decades of experience in sales, marketing, customer success, and go-to-market strategy, Seth shares why leaders need to move beyond AI hype and refocus on the fundamentals of growth: solving real business problems, enabling better conversations, and helping people perform at their best.
You’ve said AI is incredibly useful—but not a substitute for real conversations. Where do you see leaders over-rotating on AI right now in revenue organizations?
According to Seth, many organizations are adopting AI simply because they feel pressure to be “AI-first.” Instead of starting with the business problem they’re trying to solve, leaders often begin by implementing new tools and agents, creating unnecessary complexity.
Rather than asking, “How do we use AI?” Seth believes organizations should first ask:
“What problem are we trying to solve?”
Only then should they determine whether AI—and which AI solution—is the right fit.
You’ve talked about strategy actually becoming a blocker—what are the most common ways leadership teams unintentionally slow down their own revenue growth?
Growth doesn’t always stall because organizations lack strategy.
Sometimes it stalls because they’ve accumulated too much of it.
As new technologies, initiatives, and processes pile up, teams become overwhelmed and execution slows. Seth argues that effective leaders focus on simplifying operations, removing friction, and ensuring every investment supports measurable business outcomes.
Sometimes the fastest way to grow is by eliminating unnecessary complexity.
With better data, tools, and automation than ever—why are so many teams still missing targets? What are they fundamentally getting wrong?
Technology has made revenue teams more efficient, but efficiency alone doesn’t create growth.
Without a clear plan for how AI-generated capacity should be used, organizations often end up doing the same work faster—or simply filling their schedules with more activity.
The companies seeing the greatest impact are using AI to improve coaching, strengthen customer conversations, and help sellers continuously develop—not simply automate administrative tasks.
If you walked into a modern revenue organization today, what’s the first thing you’d rip out or completely redesign?
Rather than replacing people or investing in another AI platform, Seth would redesign how organizations make technology decisions.
He encourages leaders to maximize the capabilities of the tools they already own before purchasing additional software. New technology should only be introduced when existing systems genuinely limit business growth.
For Seth, the future of revenue isn’t about having the most AI.
It’s about using AI to amplify human capability, improve decision-making, and enable better conversations that ultimately drive better business outcomes.
Transcript
Rachel Cossar: Hello everyone, and welcome to another episode of Conversations in the Future of Work. I’m your host, Rachel Cossar, and I’m excited to welcome our guest—and a longtime friend of Virtual Sapiens—to the show today, Seth Marrs. Welcome, Seth.
Seth Marrs: Thank you. It’s great to be here.
Rachel Cossar: I always enjoy our conversations, but before we dive in, could you tell our audience a little about your background, your perspective, and what you’re focused on these days?
Seth Marrs: Absolutely. I’ve spent about 30 years working across go-to-market functions, including sales, marketing, and customer success. Before joining Sandler as Chief Strategy Officer, I spent six years as an analyst at Forrester, where Rachel and I first connected through our work covering sales technology and revenue growth.
Today, my role at Sandler is focused on helping the business become an even stronger growth engine. That means expanding the impact of our training while helping customers improve business performance through measurable outcomes.
One of the things AI does exceptionally well is transform conversations into insights. For years, organizations have struggled to understand whether training actually changed seller behavior or improved performance. Now we can observe conversations, measure adoption, and connect better communication directly to business results.
That’s been a major focus for us—helping organizations see a measurable return on investment by improving the quality of customer conversations.
Rachel Cossar: That’s fascinating because you’ve had a front-row seat to one of the biggest technological shifts we’ve seen in years.
Everyone agrees AI has enormous potential, but where do you think leaders are over-rotating on AI today, particularly inside revenue organizations?
Seth Marrs: Honestly, I think “over-rotating” is almost an understatement.
It’s difficult to talk with revenue leaders today without AI dominating the conversation. Many leaders are worried about being left behind, while others feel pressure to prove they’re embracing AI.
The vendors certainly don’t help.
When customers ask me how they should use AI, what they’re really asking is which AI tool they should use.
Take writing emails as an example. Many organizations now have five or six different tools capable of generating emails.
The challenge isn’t whether AI can do it.
The challenge is knowing which tool should be used for which situation.
One product might be ideal for prospecting, another for managing opportunities, and another for internal collaboration.
Very few organizations are thinking that strategically today.
Instead, they adopted AI because they felt they needed to. Now they’re trying to figure out how to manage dozens—or even hundreds—of AI tools and agents that were implemented without a clear strategy.
Fortunately, I think that’s beginning to change.
Organizations are moving beyond simply collecting AI tools and starting to ask how AI can actually create business value.
Rachel Cossar: That brings up another interesting question.
Many of the foundational, repetitive tasks people traditionally learned early in their careers are exactly the kinds of activities AI is beginning to automate.
What happens to younger salespeople entering the profession today?
Do they miss out on developing important skills, or will they simply learn differently?
Seth Marrs: I’m actually not too worried about the next generation.
They’re entering a completely different world.
People often talk about how they learned by doing repetitive work, and there’s certainly truth to that. But now we’ll have to rethink what learning looks like when those repetitive tasks no longer exist.
Take account planning.
Salespeople used to spend hours researching companies and building detailed account plans.
Most of those documents ended up sitting in a folder, never to be opened again.
The value wasn’t really the document itself.
It was everything the seller learned while creating it.
Today, AI can generate a much better account plan almost instantly.
The challenge is making sure people still develop the understanding that used to come from doing that work manually.
Learning becomes less about producing documents and more about interpreting, questioning, and applying the information AI generates.
I don’t think anyone has fully solved that challenge yet.
Rachel Cossar: That’s a really interesting perspective.
There’s also this broader conversation happening around the idea that the traditional career “conveyor belt” no longer exists.
People entering the workforce today have an opportunity to think much more creatively about how they build their careers.
Another thing I’m curious about is communication.
As AI automates more administrative work, salespeople should theoretically have more time to build relationships, establish rapport, and spend time with customers.
Do you think that’s actually what will happen?
Seth Marrs: I think it depends entirely on leadership.
If leaders simply create additional capacity without deciding how that capacity should be used, people naturally take the time back.
They still believe they’re doing everything required to succeed.
If AI helps them complete those activities faster, many people simply work fewer hours.
We saw something similar after the shift to remote work.
People eliminated commuting time but didn’t automatically become more productive.
The organizations that benefit most are the ones with a deliberate plan.
They intentionally redirect that new capacity toward higher-value work—better customer conversations, stronger coaching, and activities that directly contribute to revenue growth.
That’s where AI creates real business value.
Rachel Cossar: That’s such an important distinction.
Technology has always promised greater efficiency, but efficiency doesn’t automatically lead to productivity.
When you’re working with leaders trying to build an AI strategy, where do you actually begin?
Seth Marrs: I actually try not to start with AI at all.
I start by asking:
“What problem are you trying to solve?”
That creates the foundation for everything else.
Then I ask another question:
“What technology do you already own?”
Most organizations already have tools capable of solving many of their challenges.
I don’t think companies should buy another AI platform until they’ve reached the limits of what they already have.
Only then should they consider investing in additional technology.
That approach dramatically improves adoption because people understand why the new capability matters.
Rachel Cossar: I love that approach. It’s classic sales thinking.
You don’t begin with the solution.
You begin with the customer’s problem.
Yet AI has become such a powerful buzzword that many organizations immediately jump to technology before defining the actual challenge they’re trying to solve.
Seth Marrs: Exactly. People become distracted by the shiny object.
Technology should support strategy—not become the strategy.
Rachel Cossar
Do you ever get tired of talking about AI?
Seth Marrs: Sometimes. I love what AI can do.
I love solving problems with it.
But every conversation seems to become an AI conversation.
I remember sitting in a meeting where everyone was comparing the number of AI agents they had deployed.
Someone said they had forty-five.
Someone else had eighty-five.
Another had more than two hundred.
When it came to me, I explained that we were using AI extensively but defined AI agents much more narrowly.
Suddenly it looked like we weren’t using AI at all.
That experience really highlighted how much of the conversation had become about appearances rather than outcomes.
Fortunately, I think organizations are beginning to ask harder questions about costs and measurable business impact.
Rachel Cossar: Absolutely. People are beginning to evaluate not just what AI can do, but what it actually costs.
At Virtual Sapiens, we recently expanded our team, and there was plenty of discussion about replacing certain roles with AI.
Instead, we hired people.
And it’s been wonderful.
Having people who bring initiative, curiosity, creativity, and independent thinking is incredibly valuable.
Seth Marrs: I completely agree. Especially for roles that require judgment, adaptability, and collaboration.
AI can’t replace someone who proactively thinks about how to move the business forward every day.
Rachel Cossar: You have a compelling vision for where AI fits into revenue organizations.
What would you love to see over the next few years?
Seth Marrs: For me, AI should amplify people.
That’s where the greatest value exists.
I’m particularly excited about coaching and training.
Historically, organizations invested heavily in sales training but had very little visibility into whether those skills actually appeared in customer conversations.
Now that’s changing.
We can analyze conversations, observe behavioral change, and connect better communication directly to business outcomes.
That’s incredibly powerful.
Longer term, I think AI can help organizations personalize best practices.
Rather than forcing every seller into exactly the same methodology, AI can help tailor proven approaches to individual people, teams, and businesses.
That’s something that simply wasn’t practical before.
Rachel Cossar: I couldn’t agree more.
At Virtual Sapiens, our mission has always been helping people become better communicators.
It’s exciting to use AI not to replace human interaction, but to strengthen it.
As AI automates more routine work, communication, relationship-building, and critical thinking become even more valuable.
Seth Marrs: Exactly. That’s what excites me most.
AI should help people become better at being human.
Rachel Cossar: I love that.
Seth, thank you so much for joining us today.
If people want to follow your work and stay connected with your thought leadership, where’s the best place to find you?
Seth Marrs; LinkedIn is definitely the best place.
I also publish a regular newsletter where I curate the research, trends, and ideas I’m following across revenue growth, AI, and go-to-market strategy.
My goal is to help others learn alongside me.
Rachel Cossar: Fantastic.
Thank you so much for joining us, Seth.
And thank you, as always, to everyone listening.
We’ll see you next time on Conversations in the Future of Work.