May 14, 2024

Why GenAI is ‘Magic Tech’ Democratizing Business Intelligence, with Danny Lange, VP of Data Analytics at Google Cloud

Jessica Denny
Why GenAI is ‘Magic Tech’ Democratizing Business Intelligence, with Danny Lange, VP of Data Analytics at Google Cloud

Table of Contents

Danny Lange likes his coffee black, and on his desk there’s only a computer. But everything else about his life is anything but simple. 

In 2023, Lange joined Google Cloud as Vice President of Data Analytics following a storied career building machine learning platforms at Unity, Uber, Amazon, and Microsoft.  

Lange’s path to Silicon Valley started in Denmark where he grew up, raised mostly by his grandmother because his parents traveled with a circus—his dad a highline walker and his mom a bicycle acrobat. “School was not the central thing,” Lange said. “I was the first in my family to go to high school, first to go to university. I couldn’t get far enough away from the circus. I didn’t like clowns.”

Lange did get far away from the circus, earning a PhD in computer science at Technical University of Denmark and eventually moving to Tokyo, then Seattle, then San Francisco. In his tenure, he has worked on the edge of every seismic technology shift since the 1980s—including hypertext at CERN, OnStar for GM, and Java Aglets at IBM.

The AI revolution we are experiencing now, he says, is different. “We have never seen anything like this in history,” Lange said. “It is a very special moment. This stuff finally works. It works better than I ever expected, and it keeps working better and better.” 

What generative AI can do now and what it will be able to do in the near future, Lange considers to be like “magic technology.” 

With AI to help us understand data, assess a situation, give advice, and support decisions—that’s going to democratize business intelligence. And Lange wants to be part of making it happen.

A Magic Moment for Magic Tech

From a young age, Lange was curious about how things worked, and he credits a next-door neighbor for igniting his interest in computers. 

One day when Lange was about 10 years old, that neighbor popped his head over the backyard fence. He was an electrical engineer and invited Lange to learn about electronics and integrated circuits. Lange was fascinated with the digital parts of electronics, with machines that could count and perform logic. 

The major technology shifts Lange has witnessed since then have been what he considers fundamental whereas AI is transformational. We moved from the typewriter to computerized word processing. The World Wide Web gave us access to information without going to a library or waiting for a newspaper delivery. 

“Past tech advances sped up human capabilities. AI exceeds human capabilities.” – Danny Lange

“It’s not like you can type fast or get information fast. No, you can actually be helped at the deep intellectual level with decision-making,” Lange said. “It is changing the core of how intellectual work takes place. Past tech advances sped up human capabilities. AI exceeds human capabilities.”

Take, for example, the use of chatbots to process a lengthy email thread—Lange’s current favorite AI application. It can save the time it takes to read the entire exchange, quickly deliver an executive summary of what was discussed, and summarize the opinions of each participant. AI can be asked about the points made and will help craft a response based on a stated position.

On a grand scale, Lange thinks these capabilities will change the way professionals make decisions. “Sometimes we claim it is data-based, but in reality, it’s often just gut-based. I see very big and important decisions being made based on very little analysis,” he said. “AI is going to take away people looking at numbers and dashboards and then trying to guess which direction things should go.”

‘We’re All Going to Be CEOs’

With its supernatural ability to process massive volumes of data at lightning speed, AI is forecast to do everything from pick stocks to perform heart surgery. A Chinese gaming company and a Polish drinks company went so far as to appoint AI bots to their CEO positions. 

But Lange sees beyond the big dreams and the gimmicks. 

“To say AI is going to be the CEO—that’s completely wrong thinking,” said Lange. “We’re all going to be CEOs. We are all going to make decisions with these tools in our hands.” 

As humans, we simply cannot process huge amounts of data. We fall into routines and rely on what has worked in the past, but “AI systems provoke us to think differently,” Lange said. 

People can spar with AI, use it to probe data, uncover answers, or be confronted with points of view they hadn’t considered. It’s an opportunity many business leaders would welcome. A recent survey revealed C-suite executives are open to “a significant amount of support from AI.”

And the most exciting part is that this can happen across the entire enterprise, not just in the boardroom.

“I think that many more people should be equipped with the ability to make well-informed decisions in their companies and that is absolutely going to enable businesses to scale much more effectively,” Lange said.

Lange notes an important caveat, “Generative AI can advise and provide insight, but it is not the boss. At the end of the day, we are making the decisions.”

“Generative AI can advise and provide insight, but it is not the boss. At the end of the day, we are making the decisions.” – Danny Lange

As users have already seen, AI is not perfect. It can be biased, presenting skewed information. It can hallucinate, making up information and presenting it as facts.  It is the responsibility of humans to ensure data fed to the AI algorithms is complete, accurate, clean, and organized—and to cross-check AI outputs accordingly. 

In other words, what AI provides is options, not answers. 

“Software used to be deterministic, giving the same result every time—it’s black or white, it’s true or false,” Lange said. “What we are experiencing now is way more complicated. We actually have more responsibility than ever.”

Big Data is Back in a Big Way

A buzzword stretching back to the 1990s, ‘big data’ has been a term as difficult to wrangle as the data itself. Today, Lange says, “data is bigger than ever.”

“The first time around with big data, we didn’t have the necessary tools to analyze it,” he said. “We produced big data. We stored it, we processed it, but we couldn’t really make sense of it.” 

Now that generative AI can analyze vast volumes of information, it’s beckoning a comeback for big data buzz. “GenAI is like having a whole army of data scientists with PhDs analyzing your data,” Lange said. This is the work of Lange and his team at Google—letting AI loose on vast amounts of data to find trends, anomalies, and knowledge needed for making meaningful decisions. 

“GenAI is like having a whole army of data scientists with PhDs analyzing your data.” – Danny Lange

Companies that invested in big data over the past two decades have a big advantage because the analytical tools are finally catching up. “That data is probably worth more than anyone thought it would be,” Lange said. “AI allows you to distill that information.” This means decision-makers can look to AI for help answering strategic business questions about customers, deals, products, pricing, operations, and more.

Of course, privacy concerns still haunt big data. Many people bristle at custom online content or commercial goods recommendations that feel a bit too accurate. Lange expresses optimism around that topic as well. “Big data has become so rich and machine learning so advanced, that content and experiences can be personalized without your private information being revealed.”

“Leading companies are using big data today to optimize these experiences while not violating the privacy rules,” Lange said. (In a related article, People.ai founder Oleg Rogynskyy recently spoke about the AI-driven approach to persona data for optimizing go-to-market activities.) 

Lange’s Legacy: Enabling Developers’ Imaginations

Looking back on his childhood, Lange describes his grandmother as “pure love.” She was completely blind and fully committed to caring for him, filling the gaps when his parents were away. 

Lange also speaks highly of the neighbor who inspired his love of computers. That same neighbor became the priest of a church north of Copenhagen, and he eventually led the wedding ceremony when Lange married his wife, Eva. They raised four children which Lange calls his proudest achievement. 

At this point in his career, Lange is looking toward another achievement—a dowry of sorts for tomorrow’s tech geniuses.

“What if millions and millions of people can develop applications that use AI to accomplish something?” This is Lange’s hope. 

As humanity faces seemingly insurmountable global challenges, such as those brought on by climate change, autonomous systems can help. “We need clever systems that help you understand how to fix some of these problems without making a whole bunch of new problems,” he said. 

At Google Cloud, Lange and his team are focused on building AI tools people can use to solve problems. “But all of those tools also have APIs that allow developers to build tools we cannot imagine, and we’re already seeing that happening,” Lange said.

“What I want to leave behind is the ability for people to create surprising applications and solutions that I just would never have imagined possible.”

Danny Lange likes his coffee black, and on his desk there’s only a computer. But everything else about his life is anything but simple. 

In 2023, Lange joined Google Cloud as Vice President of Data Analytics following a storied career building machine learning platforms at Unity, Uber, Amazon, and Microsoft.  

Lange’s path to Silicon Valley started in Denmark where he grew up, raised mostly by his grandmother because his parents traveled with a circus—his dad a highline walker and his mom a bicycle acrobat. “School was not the central thing,” Lange said. “I was the first in my family to go to high school, first to go to university. I couldn’t get far enough away from the circus. I didn’t like clowns.”

Lange did get far away from the circus, earning a PhD in computer science at Technical University of Denmark and eventually moving to Tokyo, then Seattle, then San Francisco. In his tenure, he has worked on the edge of every seismic technology shift since the 1980s—including hypertext at CERN, OnStar for GM, and Java Aglets at IBM.

The AI revolution we are experiencing now, he says, is different. “We have never seen anything like this in history,” Lange said. “It is a very special moment. This stuff finally works. It works better than I ever expected, and it keeps working better and better.” 

What generative AI can do now and what it will be able to do in the near future, Lange considers to be like “magic technology.” 

With AI to help us understand data, assess a situation, give advice, and support decisions—that’s going to democratize business intelligence. And Lange wants to be part of making it happen.

A Magic Moment for Magic Tech

From a young age, Lange was curious about how things worked, and he credits a next-door neighbor for igniting his interest in computers. 

One day when Lange was about 10 years old, that neighbor popped his head over the backyard fence. He was an electrical engineer and invited Lange to learn about electronics and integrated circuits. Lange was fascinated with the digital parts of electronics, with machines that could count and perform logic. 

The major technology shifts Lange has witnessed since then have been what he considers fundamental whereas AI is transformational. We moved from the typewriter to computerized word processing. The World Wide Web gave us access to information without going to a library or waiting for a newspaper delivery. 

“Past tech advances sped up human capabilities. AI exceeds human capabilities.” – Danny Lange

“It’s not like you can type fast or get information fast. No, you can actually be helped at the deep intellectual level with decision-making,” Lange said. “It is changing the core of how intellectual work takes place. Past tech advances sped up human capabilities. AI exceeds human capabilities.”

Take, for example, the use of chatbots to process a lengthy email thread—Lange’s current favorite AI application. It can save the time it takes to read the entire exchange, quickly deliver an executive summary of what was discussed, and summarize the opinions of each participant. AI can be asked about the points made and will help craft a response based on a stated position.

On a grand scale, Lange thinks these capabilities will change the way professionals make decisions. “Sometimes we claim it is data-based, but in reality, it’s often just gut-based. I see very big and important decisions being made based on very little analysis,” he said. “AI is going to take away people looking at numbers and dashboards and then trying to guess which direction things should go.”

‘We’re All Going to Be CEOs’

With its supernatural ability to process massive volumes of data at lightning speed, AI is forecast to do everything from pick stocks to perform heart surgery. A Chinese gaming company and a Polish drinks company went so far as to appoint AI bots to their CEO positions. 

But Lange sees beyond the big dreams and the gimmicks. 

“To say AI is going to be the CEO—that’s completely wrong thinking,” said Lange. “We’re all going to be CEOs. We are all going to make decisions with these tools in our hands.” 

As humans, we simply cannot process huge amounts of data. We fall into routines and rely on what has worked in the past, but “AI systems provoke us to think differently,” Lange said. 

People can spar with AI, use it to probe data, uncover answers, or be confronted with points of view they hadn’t considered. It’s an opportunity many business leaders would welcome. A recent survey revealed C-suite executives are open to “a significant amount of support from AI.”

And the most exciting part is that this can happen across the entire enterprise, not just in the boardroom.

“I think that many more people should be equipped with the ability to make well-informed decisions in their companies and that is absolutely going to enable businesses to scale much more effectively,” Lange said.

Lange notes an important caveat, “Generative AI can advise and provide insight, but it is not the boss. At the end of the day, we are making the decisions.”

“Generative AI can advise and provide insight, but it is not the boss. At the end of the day, we are making the decisions.” – Danny Lange

As users have already seen, AI is not perfect. It can be biased, presenting skewed information. It can hallucinate, making up information and presenting it as facts.  It is the responsibility of humans to ensure data fed to the AI algorithms is complete, accurate, clean, and organized—and to cross-check AI outputs accordingly. 

In other words, what AI provides is options, not answers. 

“Software used to be deterministic, giving the same result every time—it’s black or white, it’s true or false,” Lange said. “What we are experiencing now is way more complicated. We actually have more responsibility than ever.”

Big Data is Back in a Big Way

A buzzword stretching back to the 1990s, ‘big data’ has been a term as difficult to wrangle as the data itself. Today, Lange says, “data is bigger than ever.”

“The first time around with big data, we didn’t have the necessary tools to analyze it,” he said. “We produced big data. We stored it, we processed it, but we couldn’t really make sense of it.” 

Now that generative AI can analyze vast volumes of information, it’s beckoning a comeback for big data buzz. “GenAI is like having a whole army of data scientists with PhDs analyzing your data,” Lange said. This is the work of Lange and his team at Google—letting AI loose on vast amounts of data to find trends, anomalies, and knowledge needed for making meaningful decisions. 

“GenAI is like having a whole army of data scientists with PhDs analyzing your data.” – Danny Lange

Companies that invested in big data over the past two decades have a big advantage because the analytical tools are finally catching up. “That data is probably worth more than anyone thought it would be,” Lange said. “AI allows you to distill that information.” This means decision-makers can look to AI for help answering strategic business questions about customers, deals, products, pricing, operations, and more.

Of course, privacy concerns still haunt big data. Many people bristle at custom online content or commercial goods recommendations that feel a bit too accurate. Lange expresses optimism around that topic as well. “Big data has become so rich and machine learning so advanced, that content and experiences can be personalized without your private information being revealed.”

“Leading companies are using big data today to optimize these experiences while not violating the privacy rules,” Lange said. (In a related article, People.ai founder Oleg Rogynskyy recently spoke about the AI-driven approach to persona data for optimizing go-to-market activities.) 

Lange’s Legacy: Enabling Developers’ Imaginations

Looking back on his childhood, Lange describes his grandmother as “pure love.” She was completely blind and fully committed to caring for him, filling the gaps when his parents were away. 

Lange also speaks highly of the neighbor who inspired his love of computers. That same neighbor became the priest of a church north of Copenhagen, and he eventually led the wedding ceremony when Lange married his wife, Eva. They raised four children which Lange calls his proudest achievement. 

At this point in his career, Lange is looking toward another achievement—a dowry of sorts for tomorrow’s tech geniuses.

“What if millions and millions of people can develop applications that use AI to accomplish something?” This is Lange’s hope. 

As humanity faces seemingly insurmountable global challenges, such as those brought on by climate change, autonomous systems can help. “We need clever systems that help you understand how to fix some of these problems without making a whole bunch of new problems,” he said. 

At Google Cloud, Lange and his team are focused on building AI tools people can use to solve problems. “But all of those tools also have APIs that allow developers to build tools we cannot imagine, and we’re already seeing that happening,” Lange said.

“What I want to leave behind is the ability for people to create surprising applications and solutions that I just would never have imagined possible.”

Why GenAI is ‘Magic Tech’ Democratizing Business Intelligence, with Danny Lange, VP of Data Analytics at Google Cloud

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