March 27, 2024

Playing the AI Long Game with Brian Goldstein, GM of Data, Analytics, and AI at Google

Mariah Petrovic
Playing the AI Long Game with Brian Goldstein, GM of Data, Analytics, and AI at Google

Table of Contents

The interview process at Google is notoriously intense. It’s seven steps, involves virtual and in-person interviews numbering in the tens, and can take up to four months to complete. When Brian Goldstein decided to apply seven years ago, he didn’t do it lightly. He approached it thoughtfully and shared what he was going through with his children as an example of what you can achieve when you really go for it. “I saw that as a huge hurdle, a target that I was committed to achieving. I dropped a lot of things in my life and put a focus on that.” 

This ability to become totally obsessed with a goal is something that Brian applies in his personal life as well. Each year he chooses a fitness goal that stretches him beyond what he thought he was capable of achieving. Last year he rode the Triple Bypass in Colorado, a massive 118 mile road bike race between Evergreen and Avon with almost 10,500 feet of elevation change in a single day. “The reason I'm doing these things is because it allows me to reset my baseline,” he explained. “It allows me to rethink what is hard so when life or work gets challenging, I can call back and think, ‘Well, I've been there. So maybe this isn't as hard as I'm making it.’”

Brian brings this commitment and intensity to his role as GM of Data, Analytics, and AI at Google. Similar to the way he models pursuing a stretch goal to his kids, he models a long-game approach to technology to his customers. He has the uncanny ability to deeply understand the challenges his enterprise customers are facing and become laser-focused on how Google can help them achieve their strategic objectives – even when it means he has to tell them they’re not yet ready for AI. 

Combat AI FOMO by Developing an AI Roadmap the Right Way

Brian takes his responsibility as a trusted advisor and partner in a company’s AI and data journey very seriously, knowing that the decisions and investments companies make today will impact them for years to come. It’s no wonder that he’s found a home at Google, a company known to care more about the “How” than the “What”, and equally concerned with the right answer as the speed at which you get there. 

Brian takes a thoughtful approach to help company leaders manage the sense of urgency they feel when it comes to AI today. To combat the FOMO (fear of missing out) associated with such a fast-moving technology, Brian encourages his customers to think strategically about how adopting a new AI tool will add value to the business and their own customers. That way, even when you’re moving fast, you can continue to move confidently. He also likes to remind them that we’re just scratching the surface of what is possible with AI and encourages them to think bigger, more strategically, and longer term than short-term efficiency gains. 

“I always like to couch any AI conversation by reminding everybody that, despite all of the incredible hype and excitement, it is so early,” explains Brian. “I can't frankly overstate that enough, because I think it's the lens through which we need to look at basically everything, particularly in generative AI. It's not that AI hasn't been around for a long time, because it has. But it's really, really early in terms of applying its principles and its promise to business.” 

Brian said that once that reality sinks in, it’s exciting to watch customers start to think bigger than short-term efficiency gains. “When it comes to AI, companies tend to take an existing process almost every time, and then simply apply AI technology to make it better,” explains Brian. “And that's great. But what I'm most excited about is the next phase of AI evolution where enterprises are thinking about ways to take these technologies and principles and apply them in ways that improve experiences and products for their own customers. And when that happens, we're going to see exponential value created.”

How to Turn the AI House of Cards into a Fortress Built with Data 

Prior to starting his current role at Google in late 2023, Brian led a tiger team dedicated to expanding the enterprise AI market at the company. It was an exciting role for him, working across every function and with customers in every region. Through that process, Brian realized that as compelling as generative AI is, most of his customers simply weren’t ready for it. Nearly all of them shared a common problem: their data wasn’t ready for AI. 

It was dispersed across business applications, trapped in GTM team’s communications, incomplete, siloed, and in many cases, simply inaccurate. And there is a singular truth when it comes to AI (one that People.ai’s CEO Oleg Rogynskyy also talked about). You can have the greatest technology, the coolest UI, and the most brilliant engineers building your AI tools; but if you don’t have comprehensive and accurate data to feed your models, AI is not going to add measurable value to your organization or your customers. An MIT Technology Review survey among CIOs found that 68% agreed that unifying their data platform for analytics and AI was crucial to their enterprise AI strategy. And 72% said that data problems were the most likely factor to jeopardize AI/ML goals.

True to Brian’s character, he realized that to help customers gain true value from AI, he first had to take a step back and help them get their data right. “This notion of FOMO is so rampant that in many cases, people throw all logic and reason out the window,” said Brian. “They forget that if we just rush into AI, knowing that all our data sources aren't connected properly, we’re just setting ourselves up to be disappointed. We're not going to get the output that we seek. You wouldn't do a finance automation project that way. You wouldn't do an HR lifecycle automation project that way. No. First, you would get your organizational data structure in order. You would make sure it's integrated. And you would solve that problem first. And I see this over and over again.” 

Despite the pressure to deploy AI at any cost, Brian encourages his customers to crawl and then crawl some more until they start to prove outcomes and can gain trust within their organizations. Only then can you start to walk and run. “The pace of acceleration enabled by AI is exponential and dramatic and something none of us have seen during our careers. In this environment, data becomes absolutely crucial because outcomes show up a lot faster than they did before,” said Brian. 

“We used to think in terms of 24 and 36 months projects and now we can solve something in days or weeks. So in the same span of time, you can do maybe 30 projects. Well, if all 30 of those projects are leveraging data that is low quality or disconnected, you’re going to generate low-quality or incorrect outputs that aren’t valuable to your organization. You’ve also created confusion internally and potentially jeopardized trust with your customers. Without approaching AI the right way, with the right data foundation in place, you can very quickly and exponentially create a challenge that's hard to climb back from.” - Brian Goldstein, Google

He says that many technology companies, including Google, are getting better at helping customers focus on solving their data problem first. “Oftentimes we help our customers realize, ‘No, we're not quite ready for the project yet,’” explains Brian. “We try very hard to help them see that they could go forward and use our solutions. But neither of us are going to win because they're going to end up on the other side with something that's not super fruitful or useful to them or their customers.”

When Every Company is Suddenly an AI Company, How Do You Choose the Right One? 

Google has been synonymous with technology innovation for over 25 years. It has changed the way we interact with information in our day to day lives over and over again with innovations like Google Search, Google Earth, Google Translate, the Android phone, and so many others. Most recently, the company launched Google Gemini, a multimodal generative AI model that can generalize and seamlessly understand, operate across and combine different types of information including text, code, audio, image and video.

In addition to product innovation, Google has long attracted some of the most brilliant and talented minds in technology and business across the globe. Brian says that this is one of the reasons he has stayed at the company for so long. “The breadth and depth that I find in the humans that I get to interact with in my own organization and in the company broadly is still amazing to me. They really are in so many ways, the best at their craft and some of the most caring, authentic, and empathetic people that I've come across in my life”

Brian acknowledges that Google might not be the right AI partner for every company but stresses the absolute importance of doing your homework and making the right choice for your organization. “I think the most important decision that you can make right now is, who are you going to partner with?” explains Brian. “Who are you gonna choose to hold hands with and be on the journey with together? When you don't know what's coming, it's really important to know who's got your back.”

According to Brian, many organizations are forgetting the second most important thing when choosing a technology partner. Do your company values align? “We’re at an inflection point in AI technology when we have to ask ourselves who we are as a company. What do you stand for? What matters to you? And then I think you need to apply that lens when you're deciding who to partner with.”

Finding Humanity in Technology

One thing that was very clear throughout my conversation with Brian is how much he truly cares about people. He genuinely wants the best for each of his customers, no matter what that means for him. This unconventionally altruistic approach to a sales leadership role has carried over to his relationship with his team. Mentoring and investing in other people has been a steel thread throughout his career. “I enjoy helping people and frankly, it gives me a lot of satisfaction,” Brian said. “Over the course of that time I've had the opportunity to see a lot of these people go off and do the thing that really kind of fits in place for them and makes them feel alive and helps them feel like they've connected to their passion. Candidly, I think it's incumbent on all of us to reach across that proverbial aisle and help invest in other people.” 

As a sales leader at one of the biggest technology companies on the planet, the best career advice Brian ever received might not be surprising. But it definitely rings true. “Long, long ago, when I was very professionally young and impressionable, a senior leader said, ‘I call everyone back, no matter what,’” shared Brian. “I took this to heart and it has proven super fruitful for me time and time again. You just never know when that connection is going to open up a door to a new way of thinking or an opportunity you didn't see before.” 

He paused a moment before adding, “It takes me longer than it used to. So for those of you reading, that doesn't mean I'll call back today. But I will call you back.”

Learn how to select the right AI vendor for your GTM organization with our comprehensive GTM AI Vendor Guide including key things to look for in a vendor and comprehensive RFP template.

The interview process at Google is notoriously intense. It’s seven steps, involves virtual and in-person interviews numbering in the tens, and can take up to four months to complete. When Brian Goldstein decided to apply seven years ago, he didn’t do it lightly. He approached it thoughtfully and shared what he was going through with his children as an example of what you can achieve when you really go for it. “I saw that as a huge hurdle, a target that I was committed to achieving. I dropped a lot of things in my life and put a focus on that.” 

This ability to become totally obsessed with a goal is something that Brian applies in his personal life as well. Each year he chooses a fitness goal that stretches him beyond what he thought he was capable of achieving. Last year he rode the Triple Bypass in Colorado, a massive 118 mile road bike race between Evergreen and Avon with almost 10,500 feet of elevation change in a single day. “The reason I'm doing these things is because it allows me to reset my baseline,” he explained. “It allows me to rethink what is hard so when life or work gets challenging, I can call back and think, ‘Well, I've been there. So maybe this isn't as hard as I'm making it.’”

Brian brings this commitment and intensity to his role as GM of Data, Analytics, and AI at Google. Similar to the way he models pursuing a stretch goal to his kids, he models a long-game approach to technology to his customers. He has the uncanny ability to deeply understand the challenges his enterprise customers are facing and become laser-focused on how Google can help them achieve their strategic objectives – even when it means he has to tell them they’re not yet ready for AI. 

Combat AI FOMO by Developing an AI Roadmap the Right Way

Brian takes his responsibility as a trusted advisor and partner in a company’s AI and data journey very seriously, knowing that the decisions and investments companies make today will impact them for years to come. It’s no wonder that he’s found a home at Google, a company known to care more about the “How” than the “What”, and equally concerned with the right answer as the speed at which you get there. 

Brian takes a thoughtful approach to help company leaders manage the sense of urgency they feel when it comes to AI today. To combat the FOMO (fear of missing out) associated with such a fast-moving technology, Brian encourages his customers to think strategically about how adopting a new AI tool will add value to the business and their own customers. That way, even when you’re moving fast, you can continue to move confidently. He also likes to remind them that we’re just scratching the surface of what is possible with AI and encourages them to think bigger, more strategically, and longer term than short-term efficiency gains. 

“I always like to couch any AI conversation by reminding everybody that, despite all of the incredible hype and excitement, it is so early,” explains Brian. “I can't frankly overstate that enough, because I think it's the lens through which we need to look at basically everything, particularly in generative AI. It's not that AI hasn't been around for a long time, because it has. But it's really, really early in terms of applying its principles and its promise to business.” 

Brian said that once that reality sinks in, it’s exciting to watch customers start to think bigger than short-term efficiency gains. “When it comes to AI, companies tend to take an existing process almost every time, and then simply apply AI technology to make it better,” explains Brian. “And that's great. But what I'm most excited about is the next phase of AI evolution where enterprises are thinking about ways to take these technologies and principles and apply them in ways that improve experiences and products for their own customers. And when that happens, we're going to see exponential value created.”

How to Turn the AI House of Cards into a Fortress Built with Data 

Prior to starting his current role at Google in late 2023, Brian led a tiger team dedicated to expanding the enterprise AI market at the company. It was an exciting role for him, working across every function and with customers in every region. Through that process, Brian realized that as compelling as generative AI is, most of his customers simply weren’t ready for it. Nearly all of them shared a common problem: their data wasn’t ready for AI. 

It was dispersed across business applications, trapped in GTM team’s communications, incomplete, siloed, and in many cases, simply inaccurate. And there is a singular truth when it comes to AI (one that People.ai’s CEO Oleg Rogynskyy also talked about). You can have the greatest technology, the coolest UI, and the most brilliant engineers building your AI tools; but if you don’t have comprehensive and accurate data to feed your models, AI is not going to add measurable value to your organization or your customers. An MIT Technology Review survey among CIOs found that 68% agreed that unifying their data platform for analytics and AI was crucial to their enterprise AI strategy. And 72% said that data problems were the most likely factor to jeopardize AI/ML goals.

True to Brian’s character, he realized that to help customers gain true value from AI, he first had to take a step back and help them get their data right. “This notion of FOMO is so rampant that in many cases, people throw all logic and reason out the window,” said Brian. “They forget that if we just rush into AI, knowing that all our data sources aren't connected properly, we’re just setting ourselves up to be disappointed. We're not going to get the output that we seek. You wouldn't do a finance automation project that way. You wouldn't do an HR lifecycle automation project that way. No. First, you would get your organizational data structure in order. You would make sure it's integrated. And you would solve that problem first. And I see this over and over again.” 

Despite the pressure to deploy AI at any cost, Brian encourages his customers to crawl and then crawl some more until they start to prove outcomes and can gain trust within their organizations. Only then can you start to walk and run. “The pace of acceleration enabled by AI is exponential and dramatic and something none of us have seen during our careers. In this environment, data becomes absolutely crucial because outcomes show up a lot faster than they did before,” said Brian. 

“We used to think in terms of 24 and 36 months projects and now we can solve something in days or weeks. So in the same span of time, you can do maybe 30 projects. Well, if all 30 of those projects are leveraging data that is low quality or disconnected, you’re going to generate low-quality or incorrect outputs that aren’t valuable to your organization. You’ve also created confusion internally and potentially jeopardized trust with your customers. Without approaching AI the right way, with the right data foundation in place, you can very quickly and exponentially create a challenge that's hard to climb back from.” - Brian Goldstein, Google

He says that many technology companies, including Google, are getting better at helping customers focus on solving their data problem first. “Oftentimes we help our customers realize, ‘No, we're not quite ready for the project yet,’” explains Brian. “We try very hard to help them see that they could go forward and use our solutions. But neither of us are going to win because they're going to end up on the other side with something that's not super fruitful or useful to them or their customers.”

When Every Company is Suddenly an AI Company, How Do You Choose the Right One? 

Google has been synonymous with technology innovation for over 25 years. It has changed the way we interact with information in our day to day lives over and over again with innovations like Google Search, Google Earth, Google Translate, the Android phone, and so many others. Most recently, the company launched Google Gemini, a multimodal generative AI model that can generalize and seamlessly understand, operate across and combine different types of information including text, code, audio, image and video.

In addition to product innovation, Google has long attracted some of the most brilliant and talented minds in technology and business across the globe. Brian says that this is one of the reasons he has stayed at the company for so long. “The breadth and depth that I find in the humans that I get to interact with in my own organization and in the company broadly is still amazing to me. They really are in so many ways, the best at their craft and some of the most caring, authentic, and empathetic people that I've come across in my life”

Brian acknowledges that Google might not be the right AI partner for every company but stresses the absolute importance of doing your homework and making the right choice for your organization. “I think the most important decision that you can make right now is, who are you going to partner with?” explains Brian. “Who are you gonna choose to hold hands with and be on the journey with together? When you don't know what's coming, it's really important to know who's got your back.”

According to Brian, many organizations are forgetting the second most important thing when choosing a technology partner. Do your company values align? “We’re at an inflection point in AI technology when we have to ask ourselves who we are as a company. What do you stand for? What matters to you? And then I think you need to apply that lens when you're deciding who to partner with.”

Finding Humanity in Technology

One thing that was very clear throughout my conversation with Brian is how much he truly cares about people. He genuinely wants the best for each of his customers, no matter what that means for him. This unconventionally altruistic approach to a sales leadership role has carried over to his relationship with his team. Mentoring and investing in other people has been a steel thread throughout his career. “I enjoy helping people and frankly, it gives me a lot of satisfaction,” Brian said. “Over the course of that time I've had the opportunity to see a lot of these people go off and do the thing that really kind of fits in place for them and makes them feel alive and helps them feel like they've connected to their passion. Candidly, I think it's incumbent on all of us to reach across that proverbial aisle and help invest in other people.” 

As a sales leader at one of the biggest technology companies on the planet, the best career advice Brian ever received might not be surprising. But it definitely rings true. “Long, long ago, when I was very professionally young and impressionable, a senior leader said, ‘I call everyone back, no matter what,’” shared Brian. “I took this to heart and it has proven super fruitful for me time and time again. You just never know when that connection is going to open up a door to a new way of thinking or an opportunity you didn't see before.” 

He paused a moment before adding, “It takes me longer than it used to. So for those of you reading, that doesn't mean I'll call back today. But I will call you back.”

Learn how to select the right AI vendor for your GTM organization with our comprehensive GTM AI Vendor Guide including key things to look for in a vendor and comprehensive RFP template.

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