ICONIQ Releases 2026 State of AI Report
What the latest data says about token spend, finance automation, model strategy, pricing, and AI-product gross margins.
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ICONIQ just dropped their 2026 State of AI Report. There are a few slides finance folks should take a closer look at:
Token Spend
Every CFO is trying to figure out the “right amount” of token spend. We don’t want companies wasting money but we also don’t want to slow down the business at such a pivotal time.
It’s a tricky place to be in. Right now it is likely leading to overspending at most companies, but it has been an acceptable tradeoff for most companies trying to maintain high growth.
The chart below shows token spend for internal-facing tools.
In general I think it’s stupid to spend a relatively large amount on internal tools when your headcount is small. Your team is probably too focused on internal-facing stuff and not product.
Building Is More Expensive Than You Think
While everyone can build now, not everyone fully appreciates the cost/time that goes into building a fully working internal app (particularly your non-engineering teams).
And then if you are embedding AI into the tool you are building then those costs can also rack up quickly. And then the maintenance, bug fixes, new use cases, etc….so few companies have really built something internally before that they are facing a lot of this for the first time now. Cost is usually higher than you expect.
AI Not Taking Finance Jobs Yet?
Somewhat surprised to see FP&A automation at the bottom of this list of productivity impact from AI. Also, interestingly, it is one of only two functions where higher growth companies see lower productivity gains from AI. Kinda makes sense… there is a lot more art than science (that AI can handle) when a company is growing fast.
Why will we grow 100% next year? “Um…because the CEO said that’s what he wants.”
AI Use Case: Close Faster
FYI - every board member I talk to thinks their portcos should be closing the books faster… Both accounting and FP&A. Everyone wants their numbers sooner!
💡 Plug: I am working with goClose to build cool accounting tools (will either be free or very affordable) for companies who don’t want to spend tens of thousands of dollars yet and don’t have the time to vibe code something good.
What Products Are Being Built?
More folks are going after the verticals as their differentiator in a sea of sameness. But also, AI can be a lot more powerful when vertically focused.
Cheaper Models Are Gaining
We want the best but we are starting to see now that much cheaper models get the job done just as well. Also, some of the anxiety around open-source models is disappearing as companies find solutions to reduce concerns.
Most Popular Models
No big surprises with the most popular models, but it is interesting that companies on average use 3.3 model providers (slight increase from 6 months earlier).
This is likely at least partially from a push to be more efficient in AI spend. You still get the best model (Claude/ChatGPT) but we want to use low-cost models for other things.
Pricing AI Products
A lot more variability in pricing strategies today…
Companies are spending more time on their pricing strategy in 2026 (rightfully so), but I think most aren’t experimenting and updating their pricing often enough
Gross Margins Are Rising
Can’t use AI as an excuse for low gross margins forever… Make sure you have a plan for higher gross margins with your AI products.
Final Thoughts
A lot of the data from this report just proves that benchmarks go stale REALLY quick in the age of AI. Things are moving too fast to rely on benchmarks from a report 6 months ago.
You kind of have to just ignore what everyone else is doing and use your brain…
Check out the full ICONIQ report here.
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