Should CIOs have a backup plan for AI?

**Brian Gracely** (0:05)
Good morning, good evening, wherever you are. Welcome back to The Enterprise AI Show. I'm your host, Brian Gracely. And today, we're gonna dive into a topic that might be a little controversial. I don't know if it'll be totally controversial, but it does feel like we're starting to see some data points. And it's always challenging in this market as to which data points you trust, which ones you don't trust. But more importantly, as you're starting to see some data points move in a certain direction, is that just a blip in the radar because this stuff is changing so fast, and the trends sort of change, and something new comes along? Or is it the beginning of just some data starting to fill in the blanks and answer some questions that we really weren't sure about, but we're now starting to get sure about? So we're going to dive a little bit today into sort of this thesis of, as we're starting to see some data points that are implying that the cost of AI is beginning to go up, whether that is because of supply and demand reasons, so sort of lack of accelerator chips or lack of data center buildout, lack of power, or whether we're seeing a number of the larger players get close to IPO and their numbers are, they are what they are, but in order for them to get to the expectations that have been set by some of these, they're going to have to grow significantly, which in many cases means that prices are going to go up.
What does that mean if you are an enterprise CIO and you're thinking about, where am I today? What are the costs I'm paying today? One of the benefits I'm getting out of those costs today. And if my numbers go up significantly, they go up 2x, 3x, 4x over the next year, year and a half, do I need to start thinking about a plan B? Do I think about an alternative that might be better value to my company or is just something that we can afford because we like the value of what we're getting out of the technology or we like the output of what we're getting out of the technology, but we're not sure that we like that value level anymore. So we're going to dig into that right after the break.
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And we're back. Brandon, I'm not sure you're going to enjoy this show that much. We usually enjoy this. We usually do Cloud News of the Month, AI News of the Month. This one, I'm not sure where you're going to sit. I feel like you are very well qualified for this, but I'm not sure you're going to enjoy this one this month. And here's this week. This is my thesis, and I kind of want to bounce an idea off you. So as a number of these IPOs are now starting to come along, we're starting to see some numbers come out, we're starting to see some things happen around the industry. And you're never quite sure these days whether or not a couple of data points are a trend or whether they're just fodder for Twitter traffic or whatever it is. But there does seem to be a little bit of a trend right now that's kind of hinting at the idea that AI is getting more expensive and whether that's more expensive because of just shortages of CPUs and data centers and stuff, or whether everything's been subsidized for the last couple of years and we've gotten used to $20 a month. But here's my thesis, and I kind of want to get your ideas on this, and this is open-ended. But let's say you're a CIO, right? You're an enterprise CIO, you've been paying Microsoft or OpenAI or Google or something to give folks a chat bot within your organization. And you're starting to realize, hey, you're sort of similar to that Uber CIO who said, hey, I ran out of token, my token budget in the first quarter of the year. What do you do if you're starting to realize that you've got AI expectations for your company, and you're looking at your numbers and you're like, I can't afford this, right? At a high level, you're like, I don't know that we're going to be able to afford a year of AI at the rate that we're going.