AI's Unsustainable Economics: The Path to Positive Margins

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📰 Today's Edition

Let me share something nobody tells you when you launch an AI startup: your costs will absolutely balloon. And I’m talking more than a hippocorn’s waistline after Thanksgiving dinner.

I think we've all read about this in the news, but most people have not internalized what this means. 

You might not notice it at first. When you're just starting out with a handful of users for your startup and sitting on a pile of free credits from cloud providers, everything seems sustainable. The party's in full swing.

But then reality hits.

Suddenly you're generating $10k-20k in MRR per user, but it's costing you nearly that much to service each customer. Your margins are razor-thin or non-existent.

And you're stuck asking the uncomfortable question: can you price higher when everyone else in the AI space isn't? Or worse, everyone seems to be giving away so much free stuff!

It's harder than convincing a hippocorn to go on a diet - technically possible, but nobody's succeeded yet.

This isn't just a problem for the little guys. Even the giants are struggling with this fundamental economic challenge.

Look at OpenAI – they keep raising massive funding rounds despite having tons of paying customers. Why? Because their GPU costs have ballooned to match their growth.

The Modern Pets.com Dilemma

This situation reminds me of the 1990s dot-com bubble, specifically Pets.com.

Remember them? They were selling dog food online at prices lower than what it cost them to fulfill orders. It was an unsustainable business model dressed up as "growth”.

Sound familiar?

Today's AI companies are facing a similar dilemma. When you're selling a largely commoditized AI product and can't raise prices without losing customers to competitors, what's the solution?

How do you stop selling proverbial dog food at a loss? Or in our case, how do you stop selling magical rainbow oats to hippocorns at bargain-basement prices?

This isn't just theoretical – I'm seeing AI startups across the board hitting this wall. They've built impressive technology, attracted users, but can't figure out how to make the unit economics work.

Continuing to raise venture capital might patch over the problem temporarily, but eventually, that party stops too.

At some point, your margins need to kick in to pay for your product (and customer acquisition and team) and actually generate profit (what a concept…!). If you have zero or negative operating margins on a per-unit basis, that simply won't happen.

The Canva Playbook for AI Sustainability

So what's the solution? I believe it lies in expanding beyond pure AI features.

Let me point to one of my favorite examples: Canva.

Canva has been profitable for eight years straight. Yes, they have AI features built in – you can generate various images using their AI tools, which costs them GPU resources.

But that's not the majority of their product.

Users do all kinds of other things within Canva that don't require expensive GPU compute and they're happy to pay for this comprehensive solution.

This is the playbook AI companies stuck in the negative margin rut need to consider.

Beyond AI: Building Margin-Friendly Features

If you're an AI startup struggling with this challenge, here's my $0.02:

Look for high-value, low-compute features you can add to justify your pricing.

Analytics is one example. Data analytics typically doesn't require heavy compute resources, but customers place enormous value on it. Legacy analytics products command premium pricing precisely because businesses need these insights.

Can you add analytics capabilities that complement your core AI offering?

Editing functionality is another avenue worth exploring. Whether it's for voice, sound, video, or images, editing tools don't necessarily rely on expensive GPU resources.

Users might generate content with your AI (the high-cost part), but then spend most of their time editing and refining that content (the low-cost part).(Without re-prompting).

By building robust editing capabilities, you create value that doesn't drain your margins with every user action.

It's like teaching a hippocorn to accessorize - the horn polish is expensive, but the fancy scarves pay for themselves.

Starting With Sustainability in Mind

The harsh reality is that many AI startups are operating on borrowed time.

Yes, you can keep raising more money to cover your negative unit economics. The venture capital market has been generous to AI companies.

But that approach isn't sustainable long-term.

Eventually, investors will demand profitability, and if your core business model has negative unit economics, you'll face a reckoning.

That's why it's critical to start thinking about this problem from day one.

Ask yourself:

• Which features can I add that provide value without increasing my compute costs?

• How can I differentiate beyond raw AI capabilities?

• What complementary services would my users pay for?

The companies that survive the coming AI winter won't be the ones with the most impressive models or the most VC funding.

They'll be the ones who figured out how to build sustainable margins into their business model from the beginning.

The Path Forward

The AI industry isn't falling apart – but it is maturing beyond the initial hype phase into a phase where economic reality matters.

Smart founders are already pivoting their strategies to address this challenge.

They're diversifying their feature sets beyond pure AI capabilities.

They're finding creative ways to add value without adding compute costs.

They're designing pricing models that accurately reflect their true costs.

The most successful AI companies of the next decade won't just be technological marvels – they'll be sustainable businesses with healthy margins and clear paths to profitability.

So if you're building in this space, start correcting your course now. Don't wait until your burn rate forces the issue.

Add those margin-friendly features.

Rethink your pricing strategy.

Find your path to positive unit economics.

Because in the end, that's what separates the companies that endure from the ones that become cautionary tales. It’s the difference between being a legendary hippocorn and just another unicorn who ate too many donuts.

Now I’m off to plan that Thanksgiving dinner,

Dunky from Hustle Fund

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