AI and RevOps: Embedding RevOps to Speed Business Growth

AI Knowhow: Episode

117

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Every leadership team wants predictable growth, but very few have the operating systems or discipline in place that are required to achieve it. When some executives hear of extending RevOps beyond the sale and into account management, the immediate reaction is often fear: of more meetings, more overhead, and a slower business.

But what if the opposite is true? What if implementing high-level commercial operations for your clients doesn’t slow the business down at all, but instead accelerates your growth?

On this episode of AI Knowhow, we explore the fundamental shift from looking at RevOps as strictly a pre-sales discipline to extending it all the way through the client lifecycle as a lever for driving client growth and satisfaction.

On this episode, we discuss:

  • IBM’s Bold Move: Why Big Blue is packaging its internal productivity tools to sell to clients, effectively selling the consulting killer.
  • RevOps for Clients: Why treating operations as a GPS (not a stop sign) is the key to navigating client success at scale.
  • CX and Human Psychology: A conversation with Alyssa Nolte of Ology and TruVue on why AI isn’t magic in a box for customer success.

The News: IBM and the End of Selling the Hour

We kick off the episode with Pete Buer and Courtney Baker breaking down a fascinating move by IBM. They’ve built an internal AI platform that made their consultants 50% more productive, and now they are packaging it up and selling it to clients as IBM Enterprise Advantage.

It’s ironic: they are selling the very thing that reduces the need for their traditional consulting hours.

The Strategic Takeaway: In the AI era, the value isn’t in how many hours you work; it’s in the outcomes you deliver and the proprietary scaffolding (assets) you use to get there. If you don’t build the tools to automate your own service, someone else will.

Roundtable: RevOps is the Scaffolding for your Skyscraper

David DeWolf and Mohan Rao join Courtney Baker to tackle the post-sales process problem. What is the process problem? Far too often, it’s that there isn’t much of one. All the rigor and discipline that goes into earning new clients essentially goes out the window once a deal is closed.

So how can you implement a reliable system for commercial management post-sale, without slowing the business down? David argues that RevOps for Clients is actually the GPS for growth.

You can’t build a skyscraper without scaffolding, David notes. If you try to scale a professional services firm without a structured operational layer (RevOps for Clients), you’re just adding more people to a broken system. RevOps creates the alignment necessary to make sure everyone is looking at the same data and moving toward the same goal.

Expert Interview: Alyssa Nolte on the Reality of CX

Alyssa Nolte joins Courtney Baker for this week’s expert interview to discuss AI’s role in Customer Experience (CX). While the world wants to believe AI is a magic box that replaces human labor, Alyssa brings us back to reality.

While the world wants to believe AI is a “magic box” that replaces human labor, Alyssa brings a sobering perspective: it’s not magic; it’s data and psychology.

It’s Not “Magic in a Box”

“As much as we want it to be magic in a box, it is not,” Alyssa explains. She breaks CX down into four pillars: code, science, human psychology, and process. AI can handle the code and the science, but it struggles with the nuances of human emotion and the rigidity of broken processes.

The “Unsexy” Work of AI

The biggest hurdle to AI in customer success isn’t the tech, it’s the data. Alyssa emphasizes that for AI to be successful, organizations have to do the “ground-level work” they’ve been avoiding for years.

  • Data Integrity: Do you trust your CRM?
  • Process Alignment: Is your AI automating a workflow that actually works, or just making a bad experience happen faster?

Before you can wave a magic wand, you have to do the unglamorous work of cleaning up the foundation.

Note: This is Part 1 of our conversation with Alyssa. Stay tuned for Part 2 next week, where we dive deeper into specific AI applications for CX.

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