In this article
On 20 July 2026, the global research firm Gartner published a striking forecast: worldwide spending on AI models and platforms will reach about $64 billion in 2026, up 63% from $39 billion in 2025. The short message for a business owner: AI is no longer a side experiment — it has become a real budget line that companies are racing to fund. And the winners are not the ones who buy the most expensive model, but the ones who manage where and how they use it to reach a measurable outcome.
The numbers at a glance
According to Gartner's 2026 forecast:
- $64 billion in total spending on AI models and platforms in 2026 (up from $39 billion in 2025).
- +63% year-over-year growth for this specific slice of the market.
- +117% growth in spending on generative AI models — the fastest-growing segment.
- +37% growth in spending on AI platforms.
- +210% growth in domain-specific language models (DSLMs) — the biggest jump by percentage.
In the wider picture, Gartner expects total worldwide AI spending to reach $2.59 trillion in 2026, a 47% increase, and calls this the "inflection year" when enterprises — not just the tech giants — start spending seriously on AI.
Why the jump now?
Three forces are combining. First, the wave of generative models and AI agents moved AI from demo to real work inside the business. Second, the price war between model providers cut usage costs sharply, so running a worthwhile use case is finally economical. Third, locally, Saudi Arabia has declared 2026 the "Year of Artificial Intelligence" and poured investment into infrastructure and sovereign models — turning adoption into a competitive edge rather than a luxury.
What it means for your business
The most important part of Gartner's report is not the big number — it is who will capture it. Gartner says plainly that the biggest winners will be the providers who help companies manage where and how AI is used. In other words, the era of "which model is strongest?" is over, and the era of "which outcome do I want, at the lowest cost?" has begun. Note that the fastest-growing segment is smaller, specialized models (+210%), not the giant ones — because businesses have discovered that a small model tuned to a specific task is often cheaper and more accurate than a huge general one.
How to spend wisely, not heavily
- Start from a use case, not a model: pick an expensive, repetitive problem (customer service, request triage, data entry) and build around it, instead of buying "AI" with no goal.
- Measure ROI from day one: choose a number you want to move (hours saved, response time, conversion rate) and track it before and after.
- Match the model to the task: use a small or specialized model for high-volume work, and reserve the expensive frontier model for only the hardest reasoning.
- Watch usage and cost: put caps and alerts on token consumption, just like any other operating bill.
- Govern data and access: connect models to your systems through an API with clear rules on what is sent and stored, rather than pasting sensitive data into public tools.
"Enterprise AI budgets are coming under greater scrutiny, with increased focus on usage efficiency, cost control and measurable outcomes." — Arunasree Cheparthi, Senior Principal Research Analyst at Gartner.
Where Origami fits
As a technology company, we do not sell you "a model." We build a system around it that serves your business: we choose the right tier for each task, connect it to your systems (store, ERP, WhatsApp), and put a dashboard on top that measures return and cost. That is how you capture value from the $64 billion wave instead of just paying its bill with nothing to show.
Sources
Frequently asked questions
How big is the AI models and platforms market in 2026?
Gartner forecasts about $64 billion in 2026, up 63% from $39 billion in 2025.
Which parts of the market are growing fastest?
Domain-specific language models are forecast to grow 210%, followed by generative AI models at 117%. Growth is tilting toward specialization, not just scale.
What does this growth mean for a small or medium business in Saudi Arabia?
It means AI has moved from experiment to a core budget line. The key is not to spend on a model for its own sake, but on a measurable outcome — and to start with one clear, high-return use case.
How do I control AI costs?
Start with a single use case, measure its return, pick the smallest model that does the job, and put caps and alerts on token usage just like any operating bill.
Follow Origami in Google
Pin Origami as a preferred source and our articles will surface first for you in Google Search and Top Stories.
