I was recently a guest on The Growth Signal, hosted by Alyssa Nolte, and I came in with a hot take that’s been rattling around in my head for a while. 

Too many small businesses are talking about AI automation when what they really mean — and what they really need — is plain automation. That distinction matters more than most people realise. 

Having spent years running Google and Meta ad campaigns for small businesses across Australia and beyond, I’ve watched this play out in real time. Here’s the full conversation.

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Alyssa Nolte: We’re going to get right into it. Jeremy, let’s hear it — what is your hot take?

Jeremy Yang: My hot take is that too many small businesses are talking about AI automation, but I think they’re really just talking about automation. I don’t think they have the resources to do AI at the rate that AI requires in terms of data input and the granularity of it. I think they just want to be on the bandwagon. That’s what they’re really talking about — not real AI.

The Gap Between AI and Automation

Alyssa Nolte: I think this is a very important conversation because nobody wants to feel like they’re behind the times. I still have conversations with people who are like, “I have to have a website.” And I’m like, cool — what is your website going to do? Is it meant to generate leads? Is it more informational? We’re seeing a lot of businesses of all sizes, whether you are a solopreneur or the largest enterprise in the world, feeling this pressure to implement AI without a real plan or understanding of what it will or will not do for them.

Jeremy Yang: I think the biggest part of the challenge is even more pronounced for smaller businesses. I work with a lot of tradies — the Aussie term for people on the ground, driving around in a van or two or three vans. They say, “I want to book something in my diary.” To me, that’s just automation. It’s not like AI is sitting around ordering stock for you. It will tell you how many things are missing or what you’re likely going to use over the next few months based on past data. They’re wanting automation — and there’s such a big gap, but I don’t know how they’re going to fill it.

Alyssa Nolte: They also run the risk of being very disappointed in their experience with AI. I am an AI OG — I was on ChatGPT before it was cool. What I have found as someone who uses it multiple times a day is that it’s only as good as the foundation you build for it. It’s only as good as the data you have to feed into the system, and only as good as your use case. I worry that people are going to roll AI out, and then blame the tool when in reality they didn’t have the right foundation, the right skills, or the right use case. And they’re going to write it off — when I truly believe that AI is a great equalizer for small businesses who can’t afford a dedicated EA or data entry person. This is our great equalizer.

The Elysium Effect — Winners, Losers, and the Race to AI

Jeremy Yang: When you say “great equalizer,” I have conflicting thoughts. I call it the Elysium effect — that Matt Damon movie where the people with more resources figure it out, and everyone else ends up working below them. What if the franchises and the roll-up shops figure this out effectively, while everyone else misses out because they don’t have the right systems or the capacity to enter and analyze the data? After the disappointment of the tools, a lot of blaming happens — and then someone’s going to get this right. It’s probably the people with more resources.

Alyssa Nolte: I haven’t really thought about it that way — that’s a new perspective. On one hand, you’re right. There are going to be winners and losers in this race to AI. And I guess this is my hot take: this is our Bitcoin moment. This is going to be something pervasive that we all need to understand. You can either buy in when it’s early, or wish you did several years later. You don’t have to boil the ocean. You can say, what is one thing I could take off my plate? For me that was scheduling podcast bookings. That’s one thing that goes off my plate, and then another. But yes — we run the risk of the big dogs being the only winners.

Jeremy Yang: And that goes back to your first point about websites. Even if people didn’t articulate why they needed one, getting started earlier was better than not starting at all.

Agencies, Commoditization, and Scope Creep

Jeremy Yang: I run ads for people — that’s my whole life. And AI has now stacked more work because more is expected. They’re like, whatever you were doing before, you should be able to do more with AI. The game has been even more commoditized than it already was.

Alyssa Nolte: As an agency, what you can stand on is your experience across hundreds of thousands of ads. You understand what works in human psychology. LLMs are not human — they are imitations of a generic person. There’s something in statistics called regressing to the mean. If you use AI exclusively to create your ads, it’s all going to regress to the mean. It’s all going to feel average. Agencies have a real opportunity to be true differentiators for their clients. AI where it makes sense — but be special.

Jeremy Yang: I find it very effective when you wire two to three tools together — that becomes your go-to. If you have one tool, then anyone can use it. If you have your knowledge wired through tools, that’s your edge. The thing is, I find myself scope creeping. You finish things faster, but your competitors can too. So you have to do more just to stand out.

Alyssa Nolte: I hadn’t thought about it that way — that we’re going to scope creep ourselves. Ten profitable hours back that we’re just going to fill. I would caution agency owners: don’t just do more simply because you feel like you have to fill the time. If you are bringing true value, you get to charge for that. You spent years building up the expertise that earned that time back.

What the Big End of Town Gets Wrong

Jeremy Yang: What’s your experience with bigger businesses? They’re also made of humans, just like us. I know you’ve spoken about the 8% experiment — testing AI on 8% of a database. But you still needed a human to decide who that 8% is. Was it the least risky group? The people about to leave anyway?

Alyssa Nolte: I would say big businesses have all the resources in the world — and sometimes that is worse than being scrappy and bootstrapping. They become stuck in a paralysis of possibility. They have so many people in the room, so many use cases, and a lot of the time they have become separated from their customer. In all of my businesses I was the founder, the salesperson, the marketing person, and the delivery. You don’t get much closer to your customer than that. But a lot of people in big businesses — when their only job is lead generation, that’s all they think about. They become blinded to the reality of sales and delivery. And then we end up with singular perspectives. Two to three tools strung together is so much better than one. Same thing with people inside a big business — but they don’t always do well at stringing things together because they’re laser focused on their small piece.

Data Silos and the Centralisation Problem

Jeremy Yang: You talk about siloing a lot — spending your whole career making sure silos don’t happen. Is a centralised place where everyone draws from the same data becoming a reality? Because from my experience working with bigger businesses on ads, they go back to Google Sheets and Excel files — and not even formulas in there.

Alyssa Nolte: My dream of a centralised, unified experience is still a dream right now. I think it’s coming. But I’m seeing the same thing — they’re not even using Google Sheets. They’re using actual Excel files that have to be emailed around because it’s not the live file, and then merged together. It’s just not the way it should be. Leaders, from the top down, need to figure out how to create infrastructure and incentives that drive people to centralised behaviour — because it will benefit the customer, which will ultimately benefit us.

Jeremy Yang: It’s just too difficult because every move feels like you’re scrapping everything you’ve already built. And there’s such resistance. There’ll come a day when it becomes standard — this is what we use here, you should have learned that at your last job. Right now we’re just not there.

Alyssa Nolte: I think it’s coming though. I have a 10-year-old and he uses Chromebooks in the classroom the same way I learned to type in computer class. That’s second nature for him now. I know people who still put proficient in Excel on their resume. That’s table stakes now. I’m hoping we get to that point with AI — where it’s just part of the fabric of how we work. I actually taught my son to use ChatGPT to write descriptions and titles for his YouTube videos. Otherwise his title would just be “Fortnite solo.” You’ve got to give it more than that.

Jeremy Yang: I have a five-year-old and I’m already thinking — he can’t type yet, but we should get him onto voice activation. Start using it to get answers, adopt it early. Five-year-olds have a lot of questions.

The Most Practical AI Use Case Right Now

Jeremy Yang: The first use case I heard that really landed as genuinely practical right now was your idea about the salesperson with a live feed on the side of the screen — pulling up everything that’s worked in the past, what others in similar fields have solved. That’s the first thing someone said that I thought, okay, that’s real. That’s useful.

Alyssa Nolte: We have a real opportunity, as business leaders, to almost be superhuman — that Jarvis from Iron Man in the corner, making sure we know what we need to know in the moment we need to know it. And I think that’s hopefully the future of work we’re all moving towards.

Who to Follow

Alyssa Nolte: Considering all the people you know or aspire to know — who else should we be paying attention to?

Jeremy Yang: I like podcasts where people are humble and exploring, instead of coming in as an authority already. One I watched recently was Cody Sanchez on Gary Vee’s show. She’s out there buying small businesses, the level of ambition is really something to aspire to, and she touches on a lot of hot topics. She’s pretty vulnerable. I’ll keep listening to her.

Alyssa Nolte: And if someone is connecting with you and wants to continue this conversation — where can they find you?

Jeremy Yang: LinkedIn is probably easiest. Just look up Jeremy Yang, Digital Goliath. My goal this year is to be more out there on podcasts and having more conversations. In the world of AI especially, I think it’s really helpful to have a human face and let people get to know you.

Alyssa Nolte: Jeremy, thank you so much. There were a lot of things in your perspective I genuinely hadn’t thought about before, and I really appreciate you sharing them.

Jeremy Yang: Appreciate you having me. Thank you so much.

Key Takeaways

• Know the difference between AI and automation. Most small businesses describing “AI” actually just want their scheduling, booking, and repetitive tasks handled. That’s automation, and it’s still incredibly valuable — but calling it AI sets unrealistic expectations and leads to disappointment when the magic box doesn’t deliver.
• The foundation matters more than the tool. AI is only as useful as the data you feed it, the clarity of your use case, and your understanding of its limitations. Businesses that skip that foundation will blame the tool — and miss out on real gains.
• Getting started early beats getting it perfect. Whether it’s websites, Bitcoin, or AI — the people who put their flag in the ground early, even imperfectly, tend to come out ahead. Pick one thing to take off your plate and build from there.
• Your edge is what AI can’t replicate. If everyone uses the same tool, the output regresses to the same average. The real differentiator is human judgment, discernment built from experience, and knowing how to wire the right tools together in a way your competitors haven’t figured out yet.

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