Busy Sales Teams vs Real Revenue Engines

Mar 11, 2026 · 34 min

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Show Notes

In this episode of AI with Bry, we explore leadership at the intersection of artificial intelligence and revenue growth.

AI is accelerating execution across every function. But speed without structure creates chaos. The real work for leaders is not just adopting tools—it is defining processes, embedding repeatable systems, and ensuring that human judgment drives meaningful outcomes as machines multiply capacity.

This conversation reframes AI adoption as a people and execution challenge, not just a technical one.

Guest Introduction

Rich Makover

Full Name: Rich Makover

Rich is a Fractional Chief Revenue Officer and Managing Partner at Tech CXO. He works with companies across consumer goods, beauty, jewelry, and technology to build scalable revenue engines. With decades of experience at KPMG, Avon, and Citizens Watch Group, Rich now embeds investor-grade repeatable execution into growth-stage and PE-backed companies. He is also a certified executive coach and former D1 Penn State lacrosse captain, translating high-performing team principles from the locker room to the boardroom.

His perspective matters because he operates at the intersection of strategy, people, and process. Rich helps organizations turn founder intuition into disciplined, repeatable revenue execution while leveraging AI to multiply team effectiveness.

Core Conversation Summary

We unpacked a central tension facing revenue organizations today: speed versus adoption.

Rich emphasized that AI is not about replacing relationships—it’s about enabling teams to perform at scale with clarity, preparation, and confidence. When adoption is structured into workflows, AI improves meeting prep, lead qualification, proposal creation, and handoffs to customer success. Without intentional integration, tools fail to stick.

One of the biggest challenges in AI adoption is critical mass. Early adoption by a few key team members drives momentum, while isolated usage leads to stalled implementations. Leadership through example—walking the walk—drives adoption and builds trust.

We explored repeatable systems versus accidental success. Embedding AI into defined processes increases usage, accountability, and measurable results. Rich shared real-world examples where AI increased meetings, streamlined proposals, and freed leaders to focus on coaching talent rather than manual tasks.

On leadership, Rich highlighted that AI accelerates execution but does not replace judgment. Experienced leaders use AI to amplify their perspective, speed planning, and enhance team performance. Younger team members may over-rely on AI, so balancing automation with critical thinking is essential.

Ultimately, AI adoption on the revenue side is about process, culture, and leadership, not just shiny tools. The leaders who succeed are those who structure systems that allow teams to perform repeatedly under pressure.

What You Will Learn in This Episode