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Google Goes Generative AI for Enterprises

The Six Five team discusses Google going Generative AI for enterprises.

If you are interested in watching the full episode you can check it out here.

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Transcript:

Patrick Moorhead: Google had an event early in the week where they had disclosed… Well, I mean, actually let me step back. Google had talked about Bard and I related that and they showed a bunch of, what I would consider, “consumery” scenarios and they are the leader in search by a mile. But this event went in and talked about their enterprise play. Google has Google Cloud. Obviously, they have Google Workspace. The first thing that came out was an API for developers called PaLM. And I hate to think of face palm. I can’t help it. I didn’t name this, but the big L means large and the big M means model.

And Google is really good at creating APIs. I mean all the way back, gosh, when Google Search started, they led the charge in many respects with API-based computing. They also, in addition, announced what’s called Maker Suite. And Maker Suite is an – what they’re trying to create is an easy-to-use platform that I would say normals can use, where instead of getting right in and having to doing what my son does with C Plus+, it’s a little bit more drag-and-drop and text-based. It’s pretty much everything you would expect to hear from Google.

The other thing that they brought out is, that Google is notorious for – not notorious – but they’re really good in Google Cloud at doing the land-and-expand related to data for enterprise customers. And they have a tool called Vertex AI, which is the east to west total platform for AI, all the way from ingest to running inference models and everything in between. And then, finally, they showed some really slick demonstrations of Google Workspace. Google is the number two productivity package on the planet. A lot of students, a lot of enterprises, use them and they’re in direct competition with Microsoft.

Holistically, I think the big picture here is that Generative AI is creating incredible new use cases that help enterprises (a) increase revenue; (b) decrease costs; (c) increase velocity of getting things done; and I would say (d) getting closer to your customer in a more natural way that satisfies them. So I’m super excited that Google threw their axe into the sea and we have something to compare against everybody else like Microsoft and Salesforce.

Daniel Newman: There was a lot that came out from Google this week, and I think the market was pretty reasonable to have expected it, Pat. I mean the Bard initial launch, I think we would agree, did not go to plan. It did not go to plan for Google. And this is a little bit of what happens when you have years and years of work being prepared for a certain moment in time, and then it’d be like Tesla’s about to launch its next vehicle in 24 months and then the competition comes out with something that’s going to destroy it in a month and then all of a sudden they had to announce the car a week later.

And so Google have been working on this, and I think you and I have been pretty outspoken about the fact that Google, for a long time, has really led this category. It was not something that the market necessarily expected. Microsoft sort of changed the timeline, changed the trajectory, pulled a lot of things forward, and I think Google now is looking across its portfolio, its R&D, its research and its go-to-market plan to figure out, “What can we bring to market quickly to let the industry, let enterprise, let everyone in the cloud space know that we are not going to just allow lying down for Microsoft to have the entire sort of Generative AI narrative in the market.” And so that means they have to hit it from a few ends. They have to hit it for the developers, they have to hit it for the cloud and giving the tools. And then, of course, they need to hit it at the app level.

Where Microsoft has been very successful straight away, and we’re going to talk more about Microsoft later, so I don’t want to over-rotate to them, but this is where the competition lies right now. It really is with Microsoft, is they’ve been very successful in showing and demonstrating at the app level ways that these tools and technologies are going to be available and usable for your everyday knowledge workers. And so this is what Google really needed to lean into with this instead of announcements around Workspace was what are the sort of things that users that are every day…there’s hundreds of millions – is there a billion Workspace – it’s a huge number of workspace users, Pat. I don’t know off the top of my head, but effectively it’s this massive number of users and what are they going to be able to do with it? Well, if you don’t recall for some time now, if you use Gmail, my company, we use Google Workspace. So-

Patrick Moorhead: Yeah. And my backend is Google Workspace too, and I do Microsoft front end, but there’s some things that Workspace is just quicker at.

Daniel Newman: And the same here. We use a lot of productivity tools from Microsoft, but we use Google for our email and a lot of our other workspace. And the point is for a time now it’s been doing some of the generative. This is the things that I think people are missing now because they’re seeing generative in a new light, but you started typing a message, “Dear, Pat, I think we need to…” And it would say maybe, “Move the…” And it would fill in, “Meeting.” It’s been doing this kind of generative thing for us for some time, but now we’re seeing this at a new level. And so Google’s really releasing kind of, “Hey, this is what it’s going to be able to do.” Maybe it would be quickly reply to something based upon your email. Or, by the way, you know how it would send you reminders, Pat? Like, “You need to respond to this.” That was being done with a level of AI machine learning and generative to understand what’s important and what’s not? What needs to be the front?

So I guess the real analysis I want to give here is that Google’s been doing this for a while. This is not new. They’re pulling features forward and they’re making them more advanced. For instance, the ability to maybe conversationally give a concept to your doc in Google Docs or have it proofread or have it edit and rewrite something for you is pretty interesting. We’ve all seen the stable diffusion demos, but Google’s also offering things to be able to do auto-generated images based on inputs from you that could be utilized in Google presentations. So Google Workspace is doing a lot of things that are going to sort of mirror what we’re going to talk about later with M365, and that, I think, is really the pull forward.

So the tools and the plumbing and the picks and the axes, Pat, that were announced are pretty important, but I really think that the market needed to see and needed to hear one more time is that Google is actually not new to this, has been doing it for a while and now you’re starting to see it pull forward. I do think they were put on their heels, but I also think they will catch up in time and it will be a very competitive race, which I always say, Pat, is good for everybody.

Patrick Moorhead: Yeah, competition is really good and I think many of us got bored with AI and Generative AI. Natural language models really kind of woke us up from that slumber.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.

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