Navigating AI Ethics

"How are we using AI internally?"

The drumbeat is real. Boards are leaning in. Investors are leaning in. Yet, too many leaders hardly use it. Most CS teams? Still making excuses.

🤦🏼 "We’re not ready."Translation: We don't know where to start, so I'm waiting to run into someone who has done something with it.

🤦🏼 "We need cleaner data."Translation: We’re still hoping bad inputs from fractured processes will magically produce good outputs. Everyone's data is a sh*tshow. Trust me. 🤹🏼♂️ "We're playing with it."Translation: We have that one person messing with ChatGPT - experimenting.

😕 "Just don't have the resources right now."Translation: We're too overwhelmed manually building reports, wrangling renewals, and answering tickets forwarded by the support teams.

🫃🏼 "We've got too many tools."Translation: We’re overwhelmed by the tools we bought that created a bunch of silos and forced us into constant app-switching.

🤓 "Our IT team won't let us use AI."Translation: We’ve outsourced innovation to a risk-averse inbox.

It's time to put some cowboy under that hat 🤠 . No one’s asking you to rebuild the data warehouse or perform some sacred data ritual. You don’t need a PhD in AI.

You can start small.

Nearly every AI vendor has a way for you to try their wares without hiring a team of talking heads to perform unworldly 🧙🏼 acts of digital transformation.

Where to start.

✔️ Pick a use case that will give you a revenue boost or reveal something you didn't know about your customers.

✔️ Choose something that directs valuable work to the valuable people you've hired.

✔️ Pick something with outcomes that other teams can use.

Pro Tip: Your CEO doesn't care about chatbots, knowledgebase articles, or things that write emails to customers.

What do you have to lose? More customers? Your seat at the table?

We obsess over hiring A-players. But even the best GTM talent will flounder if the foundation isn’t there.

I’ve seen companies overpay for “rockstars” who quit in 6 months—not because they weren’t capable, but because they were dropped into chaos. No ICP. Bad data. No process. No enablement. No system to measure or coach.

Great GTM teams aren’t built on purple squirrels. They’re built on a strong foundation.

That foundation looks like this:

✅ A crisp, written ICP and buyer persona (not just tribal knowledge)

✅ Accurate prospect data to target the right ICP

✅ A playbook that outlines how you win—and how you lose

✅ A clear point-of-view that your team can rally around in every email, call, and deck

✅ Defined stages, handoffs, and accountability across marketing, sales, CS

✅ A baseline reporting system to see what’s working—and what’s not

When this exists, you can onboard faster, coach better, and scale smarter. It's not easy, and it’s not sexy, but it works.

Want to cut CAC and increase ramp speed? Start with your infrastructure. Hire into a structure.

Most B2B SaaS companies still operate like it's 2020. Everything changed: customer expectations, growth efficiency, and competitive dynamics have flipped.

Here’s what’s changed:

Net-New Growth is Slowing: Recent benchmarks show it’s not just a feeling—it's a trend. The 2024 SaaS Capital Performance Metrics Benchmark report notes a pivot from "growth at any cost" to "lower growth at reduced efficiency," with CAC Ratios, Payback Periods, and Net Revenue Retention all trending in the wrong direction. The biggest slowdowns? Private SaaS companies in the $10-$20M ARR range, where growth rates dropped sharply from 2022 to 2023.

Real-Time Expectations: Today’s customers don’t wait for a QBR. They expect immediate action when things go wrong—or when their needs change. When ignored, they escalate quickly. If your team is still relying on survey responses or notes from a quarterly meeting, you’ve already lost.

Lower Switching Costs/More Competition: SaaS is saturated. Data portability, budget flexibility, and competitive pricing mean your customers can and will leave. Loyalty isn't dead—it just has to be earned every day.

The old playbooks are outdated. In the past, churn was a problem you could try to fix before renewal. Now? It’s a daily risk.

📌 The solution isn’t more headcount (flesh) or more software (abstraction layers). It’s visibility and intelligence/insights. Business need knowledge that uncovers what customers are actually saying—across every channel/silo—and turns it into action before the renewal is at risk.

The playbook is changing fast. AI is raising the bar by transforming how teams detect realtime revenue threats, identify cross-sell opportunities, and respond to customer signals/behaviors beyond just login/usage data, opinions, and surveys. The delta between AI-powered companies and everyone else is widening very fast.

SaaS teams that win in 2025 will focus on minding GRR and stop reacting to churn—and start preventing it.