Alphabet’s (GOOG, GOOGL) Google has played many parts in the mythology of AI — leader, innovator, and even lagger. Though Google was initially caught flat-footed as the popularity of OpenAI’s ChatGPT surged, it remains impossible to talk about artificial intelligence without talking about the search giant.
Naturally, Google Cloud, which raked in more than $26 billion in 2022, is front and center in the enterprise AI race with Amazon’s (AMZN) AWS and Microsoft’s (MSFT) Azure. That means that for Brian Goldstein, Google Cloud’s global GM of AI go to market, life has changed a lot over the last year.
Goldstein and I first met when I moderated a panel he was on at UCLA, and I was intrigued by his candor — he’s willing to humorously bristle at the mention of ChatGPT, bringing into focus a reality: Google’s had the advantage of being a verb for search for so long, but the market has shifted — and the lack of that similar advantage in AI stings.
Especially since there’s so much history there — Goldstein showed me an interview with Google founders Larry Page and Sergey Brin from 2000 in which the two men say, point-blank, that they believe the future of Google is AI.
Goldstein sat down with Yahoo Finance to unpack what the future of AI in enterprise looks like, why companies need to get their data in order, and more.
The following interview has been edited for length and clarity.
Tell me the story of AI from your perspective, and Google’s.
It’s a great question, let me try to parse through both points of view. The evidence lies in Larry [Page] and Sergey [Brin] discussing Google becoming an AI-enabled search platform right from the company’s inception.
So, I don’t consider AI as something new to Google. We’re the company that either invented or played a role in inventing and then open-sourced many of the pivotal advancements that have shaped this entire market and ecosystem, enabling it to mature at today’s pace.
The significant shift today, or I should say in the past year or even the last 20-some years, is the intense spotlight on AI. People now understand and pay attention to it; it’s suddenly highly relevant. Personally, my experience with AI stems from my role at Google, overseeing a large data market organization, catering to customers of various sizes and needs across the entire portfolio. Then, there was this pivotal moment…
Are we going to say it? Are we going to call it the ChatGPT moment?
A magic moment definitely emerged. The tone and tenor of our customers and prospects changed.
[C-suite and boardrooms] wanted to learn, not just chat, about how generative AI could impact our business. They sought reliable insights, and few places could offer that assurance, except Google.
I was unexpectedly given the chance to enter these spaces and discuss the potential of generative AI for businesses. It was a remarkable shift — from spending nearly 30 years knocking on doors to now having doors knocked down, with people asking, “Can you please come in and help us, teach us?” That, to me, is the magic.
Was it an overnight shift or a slow realization?
I have to tell you, it feels like it happened overnight. I’ve never in my career experienced a shift like that. The move to mobile, the internet, or SaaS, those things happened over the course of years.
This was a moment where we went from business as usual to business not as usual in the course of days. And it hasn’t stopped at all … If anything, the demand has increased precipitously. There’s a hunger for the knowledge, there’s a hunger for the experience.
I want to go back to something you’ve said to me previously: “We took a big step forward in generative AI, but we need to take a step back and get data right.” What does that mean?
There’s been this incredible groundswell of excitement, and everybody knows about this. We’re all talking about it around generative AI and jumping in and doing the project and sharing the impact.
But that all being said, at the other side of these projects, what we’re seeing is that organizations did not have their data house in order. For one, they had not appropriately connected all the disparate data sources that make up the most effective outputs in a model.
Two, so many organizations had not cleansed their data, making certain that their data is as appropriate and high value as possible. And so we’ve heard this forever — garbage in, garbage out. You can have this great AI project that has all the tenets of success and everybody’s really excited. Then, it turns out that the data pipeline isn’t great and that the data isn’t streamlined — all of a sudden your predictions are not as accurate as they could or should have been.
The models are harder to continue to train, and they’re not as good as they ought to be. You potentially have a space here where you’re not mitigating bias, and there’s inaccurate data risk that can lead to all kinds of challenges.
Let’s say there’s a CEO reading this, and this person wants to get their generative AI project off the ground, and still needs to get their data in order. What would you tell them?
I think you should choose a partner, a technology partner, who can come in and join forces with you and hold hands and be accountable with you — not just providing software and services, but to also be responsible for thinking through the dynamics of what a project would look like.
What are the priorities for your business? How can we help you figure out where the low-hanging fruit is and where the riskier projects are?
What does the overall future of AI look like?
You cannot discount the impact of this multimodal world that we are entering where we’re leveraging text, video, image, and sound. All these things coming together is going to happen in a way that, even though we’re starting to see it in our real lives — it’s hard to fathom just how impactful some of this is going to be.
I’ve imagined my own domain evolving in a way where, for example, it becomes very commonplace that for a customer conversation, there’s an AI [assistant] that’s helping go-to-market professionals appropriately adjust tone, tenor, and types of engagement that they’re having with the party on the other side.
AI will connect all these disparate resources in a way that allows you to gather insights in real time, and provide a provocative approach to business outcomes that’s going to be entirely game-changing.
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