Strategy Over Tools: Alex Greenshpun on Building Marketing Moats in AI

Most marketers chase tools. Alex Greenshpun chases strategy.

I first connected with Alex Greenshpun on LinkedIn.

She’s one of the few marketers I’ve met who doesn’t just tinker with AI tools. She builds AI workflows, codes her own MCP servers, and thinks deeply about where AI & marketing is really heading.

Since then, we’ve had long, unfiltered conversations about AI and marketing. And every time, her perspective stood out: blunt, strategic, and refreshingly free of hype.

Some of my favorite AI-related posts from Alex on LinkedIn:

• A masterclass in storytelling

• MCP Guide

• It’s all about strategy

That’s why I asked Alex to share her thoughts in this Q&A, so more people can hear the way she thinks about AI & marketing.

My work of art! Created using Google’s Nano Banana image generation model.

Question #1: Why do you think strategy is the real moat for marketers in the AI era?

Alex: Strategy is the baseline.

But it’s not the only thing. What makes marketers defensible in the AI era is the combination of strategy, curiosity, taste, and empathy.

• Strategy matters because if you don’t understand the problem you’re solving, the audience you’re solving it for, and what people actually expect, no tool or workflow will save you.

• Curiosity is critical because AI changes so fast. If you’re not experimenting and asking new questions, you’ll fall behind.

• Taste and empathy separate the noise from what’s valuable. Audiences already filter out generic “AI slop.” To create content that resonates, you need human judgment, taste, and the ability to put yourself in the customer’s shoes.

So yes, strategy is the moat, but it only works if you combine it with curiosity and taste.

That’s what will separate great marketers from everyone else as AI makes execution cheaper and easier.

My Thoughts: 

I think strategy comes from an innate grasp of marketing fundamentals. The stuff you only build by solving with real problems, not with shortcuts.

The thing about AI is it tempts marketers with an easy way out. You can skip the understanding, get a decent answer fast, and move on. But it’s exactly that hard work, the failures and the experimentation that builds real strategic thinking, 

Question #2: Does AI make it harder for younger marketers to build strategy?

Alex: Yes and no. Nobody sat me down early in my career and taught me “strategy.” I learned it by jumping into tactics, failing, then breaking things down and realizing what worked and what didn’t. That trial-and-error process is what builds strategic thinking.

The risk with AI is that younger marketers may skip that process. They can get answers fast, but they lose the struggle that usually forces deeper understanding.

That’s why leaders have to step in. It’s our responsibility to expose younger marketers to strategy:

• Explain the “why” behind decisions (why we chose this playbook, why we ignored that channel).

• Show them how positioning and messaging are built, not just hand them a tool.

• Give them space to experiment. To think, problem-solve, and find their own answers.

AI can accelerate parts of the work, but without mentorship, I think that junior marketers risk staying stuck in tactics.

My Thoughts: 

I used to be a very tactical marketer, always hunting for inefficiencies in the market we could exploit for quick results. The problem is, those gaps never last. You end up chasing short-term wins instead of building something sustainable. 

Learning strategy is what allows a marketer to shift from quick wins to building something sustainable.

Question #3: What does a strategy-first approach to building AI workflows look like?

Alex: When it comes to AI automation, it's easy to confuse strategy with complex workflows, but those tend to backfire.

Those complex no-code workflows look shiny, but they break easily, waste time, and often require developer skills anyway.

A strategy-first approach starts with the problem: what are we actually trying to solve? From there, it’s about choosing what’s worth automating and what isn’t.

That usually means starting small:

• Using tools you already have (like Gemini inside Sheets) to save hours on analysis.

• Building lightweight workflows that solve one real bottleneck.

• Automating only once you know it works in practice.

Chasing end-to-end agents that promise to "replace your marketing team" won't get us far. But stacking small, reliable wins that align with our strategy will.

My Thoughts: 

For me, strategy in AI workflows starts with one question: what specific problem are we solving?

The workflow should exist only to solve that problem. Nothing more.

Most of the time, that means the workflows aren’t complicated. They’re focused, singular, built to solve for X and only X.

Question #4: Part of strategy is focus. With new AI tools every week, how do you decide what’s worth exploring?

Alex: "Shiny tool syndrome" is real. With endless updates on new tools, features, models, and "no-code" workflow templates, it's too easy to be distracted.

The way to stay focused is to start from first principles: what actually makes a difference for your marketing strategy and pipeline? Strategy means deciding not just what to do, but what to ignore.

That often means doubling down on smaller, proven wins such as plugging AI into Google Sheets to analyze thousands of rows of data, instead of chasing the latest tool.

Focus is a discipline: ignore 90% of the noise and go deep on the 1–2 things that create real impact.

My Thoughts: 

I’m a lot more selective with AI tools now. When I first started, every new launch felt like a “game-changer,” and I wanted to try them all.

But after spending time building actual AI workflows, my approach has shifted. 

Today, I look at tools on a needs basis. If I’m repeating a task often, that’s when I’ll look for an AI tool to augment it, not before.

Question #5: If AI makes execution a commodity, what else besides strategy gives marketers an edge?

Alex: If AI commoditizes execution, the edge won’t come from a productivity and efficiency boost, as everyone will have that.

The edge comes from what AI can’t replace: taste, empathy, and authenticity.

• Taste: knowing the difference between high-value content and generic “AI slop.” Audiences are already filtering out posts that feel machine-written. Marketers with taste will know how to steer AI to produce quality that resonates.

• Empathy: being able to put yourself in the customer’s shoes, understand what actually matters to them, and translate that into campaigns.

• Authenticity and community: people will crave human-to-human connection more than ever. Live events, founder-led brands, and communities will become some of the strongest differentiators.

So beyond strategy, the moat is human judgment and the ability to build real trust. That combination is what will separate marketers who thrive in the AI era from those who get drowned out.

My Thoughts: 

It’s funny how things change. I started my marketing career right when social media was taking off. Back then, brands were ditching human-to-human connection to go online.

Ten years later, we’ve gone full circle in the age of AI. 

Wrap Up: A Marketer’s Real Moat

The future of marketing won’t be defined by who tries the most AI tools. It will be defined by who uses them with focus, judgment, and strategy.

That’s Alex’s core message: AI is just the accelerator.

The real moat comes from how you think, what you choose to ignore, and the edge only humans bring… Which is taste, empathy, and authenticity.

Big thanks to Alex for sharing her candid perspective!

PS: Do follow Alex on LinkedIn for hype-free AI use cases for marketers and GTM teams, which she shares regularly.

I test AI workflows on real marketing problems.

And turn the useful ones into 10x Playbooks.

So business owners and solo marketers doing it all themselves can skip the guesswork… and copy what actually works.

→ I drop one of these 10xPlaybooks 🚀 every week, don’t miss the next.

John