Dan D'Azio (Dan Diasio) - EY global AI consulting leader

speaker

26 appearances 1 recordings 1 series first heard Jul 2026 last heard 31 Jul

Dan D'Azio (Dan Diasio) - EY global AI consulting leader’s voice in public audio — every appearance, attributed to the second.

Trend

recordings per month · last 12 months

Recordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.

Appearances

newest first · ▶ plays the moment

WSJ What’s News · Token Costs Have Execs Rethinking AI Rollouts · 31 Jul 2026 podcast

82%.

of corporations are now concerned about the token costs that they're seeing inside their business.

For many corporations, the era of unlimited AI access is ending.

I mean, I think for many corporations, the era of unlimited AI access is ending.

Companies are now starting to put a price on intelligence in their organization, which means they're making decisions around who should have access, where do you start to apply these premium frontier AI models,

which departments might require more tokens, like the R&D department might get a larger allocation than, say, in the human resources department.

And they're also starting to look forward to where they might be able to build a proprietary strategy.

We saw that 82% of corporations are now concerned about the token costs that they're seeing inside their business.

And nearly every one of them says it's causing their business to start to rethink what their approach to AI scale out has been.

Now, it's not all just downside.

Two thirds of companies we see are putting controls in place to be able to monitor token usage so they can start to use that data to make allocation decisions.

There's really three components to that total cost.

One is the amount of tokens you're consuming with a specific activity.

So the higher computationally intensive areas like building out software or maybe doing a detailed study require more tokens.

There's also the cost of the model that you're producing.

some of the latest and greatest frontier capabilities that are pushed out by the frontier AI firms, those latest and greatest models might be five times more expensive than some of the less capable models that are in their portfolio.

So the model that you pick

actually has a pretty big outcome on cost.

And then the third bit is it does come down to the lack of predictability.

For many times, a specific task might take, let's say, 20,000 tokens, but because of some configurations on data, it might get stuck and retry again and again, and that could start to really increase the meter to several hundred thousand tokens to be able to perform that task.

Showing 1–20 of 26 · page 1 of 2