What you'll learn:
- Identify high-impact GenAI use cases across marketing, sales, pricing, and customer ops—and tie each to a revenue KPI.
- Build a practical AI growth roadmap (impact vs. feasibility) to avoid “pilot purgatory” and scale what works.
- Design GenAI-powered marketing personalization and A/B tests to prove lift in conversion, CAC, and revenue.
- Improve sales productivity with CRM copilots: call summaries, next steps, outreach drafts, and cleaner pipeline data.
- Apply GenAI to pricing and forecasting using what-if simulations, bundling ideas, and RevOps automation to reduce leakage.
- Set governance guardrails (privacy, bias, HITL review, logging) so GenAI is safe, compliant, and trusted.
Generative AI is already reshaping how companies grow—not just how they save time. Consider this: McKinsey estimates generative AI could add $2.6T–$4.4T in annual value across use cases. And that value shows up right where revenue is made: marketing, sales, pricing, and customer operations.
Here’s the problem: most teams are still stuck using AI as a “content toy” or a productivity hack—while revenue leaks through slow sales cycles, generic campaigns, manual RevOps work, and pricing decisions driven by yesterday’s spreadsheets. Meanwhile, Salesforce research found sales reps spend less than 30% of their time actually selling—because admin and CRM busywork eats the rest.
That’s exactly what this course fixes. You’ll learn how to use generative AI as a revenue engine—to personalize customer engagement, equip sales teams with copilots, improve forecasting and pricing decisions, and streamline the workflows that quietly slow down revenue.
You’ll learn how to:
Spot high-ROI GenAI use cases across marketing, sales, pricing, and customer ops
Personalize campaigns at scale (without losing brand voice or control)
Use GenAI to draft, summarize, and accelerate CRM workflows so reps spend more time selling
Apply AI to pricing and forecasting through scenario planning and smarter bundling ideas
Reduce friction in RevOps workflows (quotes, contracts, invoicing, renewals) to shorten cycle time
Build an AI roadmap that avoids “pilot purgatory” and scales what works
Set metrics and experiments (A/B tests, holdouts) to prove real lift
Put guardrails in place (privacy, bias checks, human review) so adoption sticks
And this isn’t just theory. Research has shown measurable productivity gains when GenAI is embedded into real workflows—for example, a large-scale field study in customer support found a GenAI assistant increased productivity by 14% on average (with even larger gains for less-experienced workers).
Whether you’re leading growth, running RevOps, owning pricing, or building GTM strategy, this course will help you connect generative AI to the metrics that actually matter: conversion, retention, deal velocity, margin, and revenue.
