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1 episodes · 19 quoted claims
Matt Renner says most early enterprise AI proofs of concept failed, defined as not ending up in a production system that drove value.
“the majority did fail, and failure being defined as it didn't end up in a production system that was driving value, right?”
Citibank's first AI use cases with Google Cloud focused on efficiency and compliance, such as making large volumes of documents easier to search.
“So I can use Citibank as a good example. So when we started working with Citibank and AI, their first few use cases were exactly down the path you just mentioned”
Google Cloud and Citibank built a system called CitiSky, which Matt Renner describes as focused on customer experience.
“So you look at the system we built called City Sky with them, and and again, in this specific case with that product, uh, it's all around customer experience.”
Matt Renner describes Honeywell as a company more than 130 years old with about one hundred divisions.
“So Honeywell, 130 plus year, maybe 140 by now, 130 plus year, incredible company, one hundred divisions, right?”
Honeywell used its manufacturing and product data to create a new AI-based services business that generates revenue.
“What if we were to actually create businesses with AI and actually create a revenue stream around a services business that was related to a lot of these products”
Matt Renner says Honeywell's CTO set up an AI review panel along with execution and monitoring processes.
“their their CTO is is it actually does a really admirable job of this. And she and she had set up, you know, frankly, everything from a review panel, uh, for AI to the execution and and the monitoring of this.”
Matt Renner says Google Cloud spent about fifteen years convincing customers to move data to the cloud.
“we spent, well, in in in Google Cloud's case, about fifteen years convincing people to move data into the cloud, but not just move it.”
Matt Renner says many early cloud adopters used lift and shift, moving data without modernizing it, which he likens to outsourcing.
“There's a fair number of folks who just moved it over, lift and shift and didn't really modernize where the data was. It was just basically an outsourcing scenario.”
Google Cloud offers BigQuery as a data store and is developing an agentic data lake, according to Matt Renner.
“We have a phenomenal store in BigQuery, and now we've got our our, uh, a lot of things going on with with our our agentic data lake that we're putting out there at this point.”
Matt Renner says Gemini Enterprise, Google Cloud's agent orchestration platform, is the fastest-growing product in the company's history.
“we have one called Gemini Enterprise, which is the fastest growing product in our history to ever hit the ground.”
Matt Renner says the A2A protocol is currently the most dominant standard for letting agents from different vendors talk to each other.
“A two A is the is the most dominant one at this point. So it can talk to agents, uh, in your orchestration platform”
Matt Renner describes Google Cloud's agent orchestration platform as a neutral 'Switzerland' that works across vendors' agents.
“And and again, we're we're more of a Switzerland, i if you will, orchestration platform for agents as you go through it.”
Matt Renner says that in his experience AI is moving jobs around rather than eliminating them, and workers may need to change skills.
“This isn't eliminating jobs, it is moving jobs around, right? Meaning folks are going to have to probably have a a thought process of of maybe changing skills”
Matt Renner describes a three-bucket approach to AI projects: ambitious ideas, improving existing operations, and routine tasks, and says the best companies run all three at once.
“You've got top buckets which talk about the art of the possible. Think big, right? We go there. Then you've got kind of a bucket that's more of the middle ground”
Matt Renner says Google acquired the cybersecurity consulting firm Mandiant about seven years before the interview.
“We made an acquisition of Mandiant about seven years ago as we were starting entering in into this era”
Matt Renner says Google completed its acquisition of Wiz in March, the largest acquisition in Alphabet's history.
“We made an acquisition here was the single largest acquisition in Alphabet's history in Wiz that we completed here in March.”
Matt Renner argues that AI models mainly find vulnerabilities, so customers also need tools to remediate, track and monitor them.
“the model's only going to scan for the most part. It's going to find your vulnerabilities. But now what?”
Matt Renner predicts most customers will use multiple AI models to scan for security problems.
“most customers, I think, are going to use multiple models before it's all said and done to make sure they've found all the problems”
Matt Renner says governments, including the US government, are highly concerned about attackers using AI models against key infrastructure.
“If you talk to the governments globally, you talk to our US. government, it is way up there on concerns when it comes down to.”