Figures in this article reflect AI pricing as of May 2026.
I gave a talk recently at South Coast Technology Leaders called “Stop Chasing AI: Start Solving Problems.” One slide got more reaction than the rest combined. It made a simple point: the AI subscriptions you’re paying for right now are heavily subsidised, and that won’t last.
If you’re experimenting with AI in your business, this matters. You should keep experimenting, but the assumptions you make today about cost are probably wrong.
What AI tools really cost to run
OpenAI is spending far more than it earns. The Wall Street Journal reported that internal OpenAI documents show the company expects operating losses of roughly $74 billion in 2028 alone, before turning profitable somewhere around 2030.
Anthropic, which makes Claude, spends the large majority of its budget on the computing power needed to train and run its models. The company is still running at a loss.
These are the two biggest names in AI, and they’re both spending far more than they earn. The gap is being funded by investors who expect today’s scale to turn into market dominance later.
What that means for your monthly subscription
Your £20 ChatGPT Plus, your £20 Claude Pro, your Copilot, your Cursor account. None of them reflect the real cost of running the models behind them.
Take Claude Code, which a lot of developers use for writing software. A heavy user can run up compute costs many times higher than the price of their subscription. The provider absorbs that gap because they want you to build your work around their tool. Once your workflows depend on it, switching becomes difficult, and that is what the providers are counting on.
Uber used the same approach with cheap rides, WeWork with cheap office space, and Amazon Prime with free shipping: subsidise growth, build dependency, raise prices later.
Signs that AI prices are already rising
Anthropic has changed how it bills business customers, moving towards charging based on actual usage in place of flat fees. Rate limits have tightened across the major providers in 2026. Claude Code users have publicly complained about quotas running out faster than expected, and Anthropic’s own CEO has said the company is compute-constrained.
OpenAI has also raised prices on its newer models this year. None of this is a crisis. Taken together, these changes point to a gradual move towards pricing that reflects the real cost.
Over the next year or two, I expect three things: free tiers will tighten, paid tiers will get more expensive, and pricing models will shift from flat subscriptions towards metered usage. The era of cheap, unlimited use is ending.
What this means if you’re using AI in your business
Two things matter.
First, experiment now. This is the cheapest these tools are likely to be, and the gap between what you pay and what you get is very large right now. If you’ve been hesitating about trying AI in your business, hesitate less. You’re unlikely to get more capability per pound than you do today.
Second, design with cost in mind. The application of AI you build today might work commercially only because the cost is artificially low. Ask yourself whether it would still work if your AI bills doubled, trebled or went up tenfold. Prices are heading upwards, so this is a realistic test.
This is where many businesses go wrong. They’re adding AI to everything, often where it isn’t the right tool.
When RPA is a better fit than AI
RPA stands for Robotic Process Automation. It’s been around for years. It’s the sort of automation that handles structured, repetitive tasks: copying data between systems, processing invoices, moving information through known workflows. It’s deterministic, which means it does the same thing every time. It’s auditable. It’s cheap to run.
A lot of business activity is better handled by RPA, a script or a rules engine. These are tasks where the logic is stable and the inputs are predictable. AI is the wrong tool for those jobs. It’s slower, more expensive, and less reliable. You don’t need a language model to move a number from column A to column B.
AI is most useful for messy work. Reading unstructured information at scale, like contracts or support tickets. Letting non-technical staff query data in plain English. Spotting patterns in chaotic inputs. Summarising long documents. Drafting content that a human will review.
The sensible approach is to use AI to build your automations. Get Claude or ChatGPT to help you write the script, design the RPA workflow, or build the rules engine. Then let cheap, deterministic infrastructure run it day to day.
McDonald’s is a good example. They ran a three-year partnership with IBM to put AI in the drive-thru, taking voice orders. It was a mess. Videos shared online showed orders filling up with hundreds of chicken nuggets nobody asked for, and bacon ending up on ice cream. They quietly shut the whole thing down in July 2024. That problem didn’t need AI. In my view, better menu design and standard speech recognition would have done most of the job at a fraction of the cost.
What cheap AI makes possible to build now
Because AI tooling is cheap right now, the economics of building your own software have changed.
Three of my own clients are currently building things that wouldn’t have been viable two years ago. One is replacing a CRM that never quite fit the business. Another is cutting expensive licensing costs by building a custom platform from existing intellectual property. A third is building a multi-tenant system to sell their own approach to other businesses.
None of these projects would have made commercial sense before. They’d have needed a £200,000 consultancy engagement and a year of build time. Now they’re being done by small in-house teams with help from Claude Code, Cursor, and GitHub Copilot, in weeks rather than months, at a fraction of the historic cost.
This is the most interesting consequence of cheap AI: things you previously couldn’t afford to build are now within reach.
If you run a service business, the bigger risk is having an offer AI can easily copy. I covered that in my article on how AI is exposing weak web design agency offers.
If you’ve been quietly fed up with software that doesn’t fit how your business actually works, now is a good time to build something that does. Just design it knowing that the underlying AI costs are likely to rise.
Three things to do this week
Here are three practical actions.
One: look at where you’re using AI today and ask whether it would still be viable if your AI costs went up significantly. If the answer is no, you’ll have a cost problem to solve.
Two: look at where you’re using AI for things that RPA, scripts, or rules engines could handle better and cheaper. Move those off AI now.
Three: look at the things you’ve wanted to build for years but couldn’t afford to. The maths might have changed.
If you want to find out where your business sits on the spectrum from AI-vulnerable to AI-resilient, the assessment below takes about two minutes and gives you a personalised report.
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