How will AI token costs affect marketing budgets?

Transcript

0:00The era of free AI is ending

For the last two years, we've used AI like it was free. You pay your $20 a month, you write some emails, you brainstorm subject lines, you move on. The meter was never running because there was no meter.

That's all coming to an end. Not because anyone's punishing you. Because what you're asking your AI to do is evolving. And the thing nobody explained to marketers is the one thing that's about to decide whether your AI workflows make money or quietly bleed it.

It's called token utilization. I feel it's the most important boring concept in marketing right now that nobody is seemingly talking about. Here's why this never came up before.

0:40Why you never had to think about cost

When you use ChatGPT or Claude in some cases to write a single email, you're doing the AI equivalent of sending one text message. Tiny. Instant. Effectively free. The flat monthly fee covers it a thousand times over, and the AI companies have been subsidizing heavy usage to win market share up to this point.

So an entire generation of marketers learned AI in an environment where cost was invisible. You never saw a bill that scaled with usage. You never had to ask "what did that cost me?" because the answer was always "basically nothing."

That created what is about to be a really expensive blind spot.

1:24What a token actually is

What is a token? A token is a chunk of text — roughly 3 to 4 characters, or about ¾ of a word.

"Marketing" might be one token. "Unsubscribe" might be two or three. Rule of thumb: 750 words ≈ 1,000 tokens.

Two things cost tokens, and this is the part people miss:

• Input — everything you send in the chat: your prompt, the document you pasted, the brand guidelines, the chat history.
• Output — everything the AI sends back.

You pay for both. So a "short prompt" that includes a 40-page PDF isn't short. You just paid for 40 pages of input every time you hit enter.

That's the whole concept. Now here's why it suddenly matters.

2:18The 4 shifts that changed everything

A year or two ago, AI was a chatbot. You typed, it answered, done. Low token use by design.

Today AI is becoming infrastructure — something you build workflows on top of. And four shifts blew token usage wide open:

1. Agents. AI doesn't just answer anymore — it runs. It takes a goal, breaks it into steps, calls itself ten, twenty, fifty times, uses tools, checks its own work. One "task" that used to be one message is now dozens of calls under the hood. Every call burns tokens.
2. Context windows exploded. Models went from holding a few pages to holding entire books — hundreds of thousands of tokens. That's powerful: dump your whole content library in, ask anything. But "dump everything in" means you're paying for everything in, every single call.
3. Reasoning models. The newer "thinking" models generate enormous amounts of internal text working through a problem before they answer you. You don't see most of it — but you pay for it. A single hard question can quietly cost 10x a simple one.
4. You stopped chatting and started building. The moment you move from typing in a chat box to wiring AI into a workflow — auto-generating 500 product descriptions, summarizing every support ticket, running a content engine — you've left the flat-fee world and entered the pay-per-token world. That's the API. And the API doesn't subsidize you.

Put it together: the tasks got bigger, the models got hungrier, and the pricing got metered. The cost that was always invisible is now attached to volume — and marketers are the ones building the high-volume stuff.

4:17Why this hits marketers specifically

Here's where it gets real for marketers like us.

The second you productize an AI workflow, token cost becomes your cost of goods. It's no longer a $20 subscription — it's a per-unit expense baked into every output you ship.

Do the math marketers never do:

• A workflow costs 10 cents a run. Fine.
• Now run it 100,000 times a month. That's $10,000. Suddenly it's a real budget meeting.

And the silent killer is context bloat. Let's say you built a content generator that re-sends your 5,000-word brand guide on every single call. At scale, you're paying to read the same document a million times. Trim that context and you can cut cost 60, 70% — same output.

Same story for anyone selling AI-powered services. If you charge a client a flat retainer for an AI tool, your margin is the gap between what they pay and what the tokens cost. You don't control that margin unless you understand tokens. This is the difference between an AI offering that scales profitably and one that eats you alive at volume.

5:355 ways to prepare right now

This is what I'm really trying to emphasize — you don't need to become an engineer. You need to develop a token instinct.

1. Learn to eyeball cost. Words divided by 0.75 = tokens. Before you build anything at scale, estimate input + output per run, multiply by volume. If that number scares you, fix it now, not after you launch.
2. Right-size the model. You don't need the most powerful model to reformat a list. Cheaper, faster models can be 10–30x less expensive and totally fine for routine work. Match the model to the job. You will need to adjust and maintain models with time.
3. Stop dumping everything in. You need to start thinking more methodically. Send the AI only what it needs for this task, not your entire knowledge base every time. Context discipline is the single biggest lever on cost that will bite people later if you don't correct the behavior now.
4. Use the cost features. Prompt caching — for repeated context like brand guidelines — and batch processing — when you don't need instant answers — can slash bills dramatically. If you're building, learn these before you scale.
5. Think in unit economics, not subscriptions. Stop asking "what's my monthly AI bill?" Start asking "what does one output cost me, and what happens at 10x volume?" That single reframe is what separates marketers who scale AI profitably from the ones who get a nasty surprise.

7:15The bottom line

Let's wrap this up — because this is already way longer than I'm comfortable talking. The flat-fee, all-you-can-eat era of AI was a phase — a land grab to get you hooked. The next phase is metered, and it rewards the people who understand what they're spending.

You don't have to be afraid of it. You just can't be blind to it anymore. Build the instinct now, while the stakes are still low, and you'll have a real edge when everyone else gets their first scary invoice.

If this was useful, please like and subscribe — I'm Nick and I break down the practitioner side of AI for marketers. Drop a comment with the workflow you're trying to scale. I'll see you in the next one.