Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 629: Google’s surprise release: Will Gemini Enterprise Compete with ChatGPT and Microsoft Copilot?

Starting point is 00:00:00 This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. Meet Firefly AI Assistant, now live and Adobe Firefly, the all-in-one creative AI studio. Just describe what you want to create and the assistant handles the rest, orchestrating multi-step workflows across Photoshop, Premiere Express, and more in one conversational interface. You direct the outcome. The assistant accelerates execution. Just when you thought we had enough large language models,

Starting point is 00:00:50 we technically have another new offering from Google. That's because they just announced Google Gemini Enterprise in Google Gemini business, technically different from their Google Gemini Pro and Google Gemini Ultra offerings. So not only on today's show are we going to. uncover what all that means and help you differentiate between those kind of personal and now enterprise versions of Google Gemini. But we're also going to look at, okay, is Google Gemini going to be a key player in Enterprise AI? Well, I think so, but let's dive in and talk about it. I'm excited for today's show. I hope you are too. What's going on, y'all? Welcome to Everyday

Starting point is 00:01:35 AI. My name is Jordan Wilson, and this is your daily live stream podcast and free dealing news that are helping everyday business leaders like you and me, not just keep up with AI, but how we can get ahead to grow our companies and our careers. If that's what you're trying to do, you're in the right place, starts here with the unedited, unscripted, live stream podcast. But to take it to the next level,

Starting point is 00:01:53 go to our website at your everyday AI.com. Make sure you sign up for the free daily newsletter. We're going to be recapping the highlights of today show, as well as keeping you up to date with all the other AI news happening today. But y'all, the big news is Google Gemini Enterprise. You know what? I think it's about time. I think there's been so much confusion. And I can see how this actually might be more confusing because even as we speak,

Starting point is 00:02:21 I've been playing around with the new Google Gemini business version. So there's kind of an enterprise and a business version, but we'll say it's in the enterprise tier. So I'm technically using a Google Gemini Pro and a Google Gemini Ultra. which are personal plans. And then I have a Google Gemini business. And it's completely different. So in some instances, you might say this is actually a bad move for Google

Starting point is 00:02:52 because now they have even more product offerings. And it's a little confusing. But I'm actually going to say, it's a good move for Google. I can't tell you how many times I do trainings, right? And one question I always ask because I'm curious, I have people raise their hands. I say, you know, hey, who in here uses, you know, Microsoft Outlook, you know, in Microsoft products and, you know, I don't know, maybe two thirds.

Starting point is 00:03:18 And then I say, okay, what about the rest of you? Google and then, you know, the rest of the audience raises their hands. And with those people that have their hands up, I say, how many of you use Gemini consistently? And obviously, you know, over the last, you know, quarter or two, the number of hands in the room would usually stay up. But earlier on, no, right? Like a year ago, even, you know, when there would be dozens of people or more that would be Google customers, no one was using Google Gemini. And I think one of the reasons is, well, it was disjointed.

Starting point is 00:03:56 It was confusing. And even Google at one point had worse connections to Google Docs and Gmail. and all the Google products then chat GPT and Anthropic did. But I'm going to tell you this. I've been very impressed. But I'm going to wait on my reactions. And let's just get straight into what we're going to be going over. So today we're going to simplify the unique features debuting in Google Gemini Enterprise.

Starting point is 00:04:26 And there's one that I think is the key feature. I'm going to explain the differences between the new tiers, which are enterprise and business, versus the previous Gemini offerings, pro and ultra. And I'm going to give you my prediction on if Google Enterprise will compete with ChatGVT Enterprise and Microsoft Copilot. So what the heck's new? What is this Gemini Enterprise? Well, they just released it yesterday as their first big take at a unified workplace AI system.

Starting point is 00:05:00 So it costs $30 per user per month matching Microsoft Copilot. 365's offering, but they do have the cheaper offering with the business plan at $21 a month, and I'll show you the difference. And, you know, some people, if you're listening, you might think, oh, like, what's the big deal, right? Well, pricing is a big deal, right? Especially when you have the enterprise organizations that have tens of thousands of employees. So the difference between paying $30 a month versus, you know, Chad, GPT, Enterprise,

Starting point is 00:05:35 The last pricing I saw for that's around $60 a month. A lot of companies might have to look at this, right? Also, Gemini Enterprise consolidates agent building, enterprise search, and governance in a single interface. And I think that's an important step forward. I'm going to share in a little bit how Google has told the story of Gap, Figma, and HCA health care and how they've been able to get some measurable gains using Google. Gemini Enterprise. And we're going to talk about some users, the chase for users here in a little bit as well. All right. There's essentially, I think, six key elements. And this is from Google that kind of

Starting point is 00:06:19 constitute Google Gemini Enterprise. So one would be the world class models, right? Most third-party benchmarks do have Gemini 2.5 Pro as the world's most powerful model, depending on what benchmark mark you look at. Sometimes it's GPT5 Pro from OpenAI, but many, including probably the most important or the one that I give the most credence to, which is L.M Arena, which is essentially the blind taste test of AI models. Gemini 2.5 Pro has been on top for a while. So you get obviously access to the world's most powerful models. The agentic platform. So you can chat with Gemini to search and analyze information and orchestrate agents to automate workflows. They do have a no code agent builder, which I've used.

Starting point is 00:07:10 And anyone from marketing to finance can build their own custom agents grounded in their data. Next, you can enjoy a suite of Google made agents like deep research, a notebook LM agent and coding agents delivering value from day one. Again, this is from the Google website. Also, you can ground agents in your business reality. So you can securely connect your company's data, wherever it lives in Google workspace and even Microsoft 365, huge advantage there, as well as business apps like Salesforce and SAP or data stores like Big Query.

Starting point is 00:07:47 Let's give your agents relevant context. Also, you can deploy and manage with confidence, according to Google. You can centrally visualize, secure audit, and govern all your agents with Gemini Enterprise, helping you to meet your security compliance in sovereignty required. within your organization, and you can leverage Google's rich, agenic AI partner ecosystem. So you can automate cross-platform workflows using Google's built-in connectors to partner apps, accelerate your AI journey with their service partners, and find innovative partner solutions at the agent marketplace. So a little bit of copy there from Google's homepage on Google Gemini Enterprise.

Starting point is 00:08:29 So why? All right. So reading this from Google again. So they say, that it connects content across your organization to generate grounded and personalized answers. That's the thing that's going to be interesting once it rolls out, once it rolls out, and once we start getting some real world public feedback on this. So they mentioned this in their keynote, but that over time that Google Gemini for Enterprise is going to become predictive. It's going to know and understand what you want and what you are going to act, based on personalization and just the sheer amount of data that it has access to. So you can obviously process large volumes of enterprise data.

Starting point is 00:09:17 You can sync and search your data across different SaaS systems, such as Salesforce, Jira, and Confluence. You can enforce access controlled search results and generative answers at scale. Yeah, so a lot of great features. So what Google is trying to put this out as as the new front door for AI, that is their words. And I kind of respect that positioning because the problem is Google's have like 10 side doors. And I think Microsoft has like 50 back doors, right? I feel the questions all the time from, you know, small businesses, entrepreneurs, all the way up to, you know, Fortune 100 companies.

Starting point is 00:10:08 And these are the questions I get all the time, right? People are like, oh, well, what's the difference between using Google Gemini? You know, if I have a pro account, if I'm using Google Gemini in workspace, if I'm using Google Gemini in Word, if I'm using Google Gemini in Vertex, right? So technically, you could make the argument that in the same way that I have, you know, two windows open right now with two technically different versions of Google Gemini, my personal account and now my business account. But I think it makes sense. I think eventually Google may start consolidating certain things inside the platform. So I like that.

Starting point is 00:10:48 And also what they're trying to do is replace the fragmented tools that they have right now with one interface for all workplace AI interactions. Yes, you get access to all the latest models as well as V-O-3, video generation and image generation, as well as their no-code workbench. So you can build multi-step agents without any programming skills. I do want to see under the hood a little bit more on that. I've been using it for a little bit, you know, so far.

Starting point is 00:11:21 I haven't been super impressed with the no code builder. You know, maybe as I get more reps in, I'll be a little bit more impressed. You know, I kind of been comparing it to Open AIs agent builder that they just released. So Open AIs seems to have more features, a little bit more, you know, bells and whistles. The Gemini I one doesn't seem that great. But ultimately, it comes down to. performance. So we'll see how it performs. And I'm sure that Google is going to add on to this over time. Also, they do have the pre-built Google agents for deep research, which I'm going to talk

Starting point is 00:12:02 about that here in a little bit. I do like one new feature in this as well as pre-built agents for data science and customer engagement workflows as well. And well, even if you're a Microsoft 365 organization, you can connect that enterprise data to Google Gemini Enterprise. So let's quickly break down the different tiers. All right. So on the personal plan side, so let's just say non-team, you have your Google Gemini Pro that costs $20 a month that also, you know, most people have that and they don't even know it.

Starting point is 00:12:40 So essentially if you're paying for Google One, so if you have a, you know, paid workspace account, right, you have your, you know, Google Drive storage, right? If you have a paid business account, you have access to Gemini Pro and you might not know it. The problem is, and it's been one of my biggest gripes since day one with Google Gemini, which it's gotten better over the last like four or five months. But so many things, I've always had to use my personal Gmail. I couldn't use my work account in the same way that I could use my personal account with Google Gemini. There were certain features and functions that just didn't work, right?

Starting point is 00:13:23 So even I pay for a Google Ultra, Gemini Ultra, which is $250 a month, but I use that on my personal Gmail. Because in Gemini Ultra, there's certain features that just weren't available if you had a workspace account. So now I like that Google is finally trying to hopefully tear that door down. And I hope that we see these other features and modes. And I throw modes out there in particularly. I hope we see these other modes and features make their way into Gemini Enterprise and Gemini business. Specifically two ones that I use so many times every single day would be their gems, Google Gems. And I love that you can use Google Gems as an example inside of Google Sheets.

Starting point is 00:14:10 So I don't see gems inside of my Google business account. And I didn't see any mention of them in Gemini, enterprise so Gemini business or Gemini enterprise and then the other one canvas mode right so I would love to see canvas mode but don't see those so far all right so you have your Gemini pro personal plan $20 a month Gemini Ultra personal plan $250 a month comes with a bunch of you know other perks as well you get 30 terabytes of storage who can use 30 terabytes of storage my gosh uh I think you also get like YouTube premium some other things if you're on that Gemini Ultra Plan.

Starting point is 00:14:49 But now let's go to the kind of team or business tiers, the new ones that were just announced yesterday. So your Google Business, Google Gemini Business, that's the one that I'm on, costs $21 per month per user. And this is for small teams who need lighter controls. And then the Google Gemini Enterprise, that starts at $30 per month per user.

Starting point is 00:15:14 And that also allows you to connect to some higher tier data such as Microsoft 365, Salesforce, and SAP. So I don't have all those connection options on the business plan, but I also don't think I'm a small business. I don't think I'll qualify for the Gemini Enterprise plan. I reached out to the sales team. I haven't heard anything back, but I did kind of get off the wait list for Gemini business fairly quickly.

Starting point is 00:15:41 So I do have a little comparison chart here. but the biggest things I think between the Gemini business and the Gemini Enterprise, well, you get other agent, pre-built agents, you get other data sources, like I said, on the enterprise plan. So I do have a comparison here. And I'm going to be sharing it in the newsletter as well. So if you want to check that out. But I'll say this. If you're a smaller, medium-sized business, you just may not.

Starting point is 00:16:15 qualify for Gemini enterprise, right? And there's a limit to 300 seats on the business plan. So it depends on, you know, will you even qualify for the Gemini enterprise? You know, yes or no, who knows? But if not, I do think with Gemini business, you're going to get a bulk of, you know, what everything that was announced, right? The grounded data, which I'm going to talk about, the agent builder and just the new platform, kind of the new, you know, Google front door to AI. You will get access to all of that. And speaking of grounding, that is the thing I'm most excited about and I'm going to talk about. But first, get a pause for a quick word from our partners.

Starting point is 00:16:59 This podcast is supported by Google. Hey, folks, Stephen Johnson here, co-founder of Notebook LM. As an author, I've always been obsessed with how software could help organize ideas and make connections. So we built NotebookLM as an AI first tool for anyone trying to make sense of complex information. Upload your documents and NotebookLM instantly becomes your personal expert, uncovering insights and helping you brainstorm. Try it at notebooklm.com. Here is the one feature. And speaking of NotebookLM, it's grounding. Okay? And Let me, I'm going to oversimplify this.

Starting point is 00:17:43 All right. So if there's any data dorks in the audience, please, please excuse me. I'm going to simplify this, okay? If you've used notebook LM and then you've used Google Gemini, you probably can understand the difference between grounding versus true generative answers. Let me give you a new example. Actually just did a, you know, show on notebook LM recently. I think that was yesterday or the day before.

Starting point is 00:18:14 And I talk about how big of a deal grounding is because it cuts down on the hallucination rate and it increases trust and transparency. Right. So grounding is when you have to enter or rely on your data for a response. So the best example is notebook LM. If you upload, I don't know, a bunch of sources. about the 1993 Bulls, one of the best teams ever. You know, I'm from Chicago. So, and my name's Jordan.

Starting point is 00:18:50 So if you upload in notebook, L.M, a bunch of information about the 93 bulls. And then you ask it about the 94 bowls. It'll say, don't know. If you ask it, what's the weather today in Chicago? It'll say, don't know, right? If you upload that same information into Google Gemini, into a gem or something like that. And you ask about the 94 bowls, it'll tell you.

Starting point is 00:19:15 If you ask it about the weather in Chicago, it'll tell you. And then the problem, and this isn't a problem with Google Gemini, it's a problem with all large language models, chat, GPT, Claude, et cetera, copilot, everything, right? Even when you upload your data. And if you have specific instructions, right, if you're using a project or a GPT or even just in the body of a chat, and you upload. a file if you upload your documents, even if you tell the model, hey, only use this, don't use your own training data.

Starting point is 00:19:46 Don't query the internet. Half the time, it's not going to pay attention to you, right, unless you're pretty decent at prompting. That's why grounding is so important. It starts and it filters through the ground up through your data. So personal Gemini accounts don't have that, right? Yes, you can connect kind of this. their apps, I believe is what they're called, right?

Starting point is 00:20:12 So you can, you know, speak or chat with Gmail or speak or chat with a certain Google Drive document. But it's not always super accurate, right? And I've detailed that over the last, you know, year and a half on this channel, maybe a little bit more on the YouTube channel. It's gotten much better. But there's a huge difference between, you know, essentially connect, like connecting a a file to your chat

Starting point is 00:20:41 and having an enterprise large language model that is grounded in your data. That's why I love Notebook LN. It is literally only going to look at the data that you give it in nothing else. That's not quite the level that we're looking at with Gemini Enterprise,

Starting point is 00:20:58 but I've been extremely impressed in my very limited testing so far in its ability to ground answers in the data that it has access to. Okay. And you know what? I wasn't planning on this, but, you know, I'm probably do a quick demo. Actually, I won't be able to do that one live, right? It's tough to do some demos live that are connected to your personal data, right? Because I don't have the ability to connect all these other third party platforms because I don't use them. So a lot of it's like my Gmail and, you know, my Google Docs and I don't want to accidentally, you know, put someone's email out there.

Starting point is 00:21:35 but I'll do another show maybe in the coming weeks and just have screenshots and show the comparisons. So anyways, the Gemini Enterprise connects securely to your company-wide data system. So anything, obviously, on the Google side, as well as Microsoft 365, Salesforce, SIP, and others. And the enterprise platform includes role-aware access controls, ensuring employees only see what they have authorized access to see. That's huge as well. Because when you talk about enterprise, you have to understand data security, you know, user permission, authorization, all of those things. And there's also inside this, there's a central governance layer that also manages all agents,

Starting point is 00:22:20 data connections, and security from a single council. So I have a little visualization here on the data access approaches. So if you've used Google Gemini's apps, if you've used Google, Gemini in workspace apps or if you've just used it from the personal side of Google Gemini, essentially how it works, even when you're connecting via an app. Okay. So if you connect inside Google Gemini and you're chatting with your Gmail app as an example, what it does is it will go through and semantically search for a message that you give

Starting point is 00:22:59 it based on a keyword, right? Uh, and normally it'll do an okay job. But essentially what is doing is it's doing a manual file selection. It has a limited context access. And it's a fairly basic integration. If you're using the personal version of Google Gemini and you're connecting even to your Google products via their connected apps. It's really just a file by file basis, which if you know exactly what you're looking for, if you have all your settings correct, and if you prompt Google. Gemini the personal version well, you'll usually get an accurate response.

Starting point is 00:23:39 But those are big ifs, right? On the Google to Gemini enterprise side, it's completely different. I mean, we're talking about automated data federation, comprehensive, contextual understanding. In my couple examples, I was honestly kind of shocked, right? I was. I was like, my gosh, this is really, really good. Right?

Starting point is 00:24:03 The difference with notebook LM is you're manually adding all of your files one by one. So you almost have like an expectation that, hey, it's like, it's almost like I help build this thing. So I know what's, you know, I know what's under the hood. When I was using the Google Cheminide business, you know, I just connected everything. And I was like, this is, this is actually pretty impressive. It has a multi-system integration as well as the real time data access. And it is grounded. So if you're asking it a question about your data, it just knows, right?

Starting point is 00:24:38 I was even trying to trick it and trip it up using abbreviations that I didn't think it would know. And it got it. Surprisingly so because it looked through multiple, it looked through my calendar, it looked through my Gmail, and it looked through my Google Docs. And it connected, it kind of triangulated a certain acronym or abbreviation. that I didn't think it would be able to figure out. And it did. And I was fairly impressed by that, right? It's not often I'm impressed by these things.

Starting point is 00:25:13 All right, Google did give a couple of use cases. I'll just mention one here because you can go read about the rest. They mentioned how HCA Healthcare, one of their pilots in the Google Gemini Enterprise, said that the nurse handoff automation estimated to save millions of annual hours. millions of annual hours by using Google Gemini on the enterprise side. Also the best buy one, pretty cool. They said they achieved a 200% increase in customer self-service and 30% more resolved in queries.

Starting point is 00:25:48 All right. Enough chatting up the features. Let's get to the good stuff. Is it too little too late for Google Gemini? Let me be honest. 15 months ago, 18 months ago, I think most people, including myself, would say, you know, Google Gemini might not even be top three.

Starting point is 00:26:17 Right. I think there was a period of time, maybe about early 2024, where it was definitely OpenAI number one, Anthropic Claw number two, and probably Microsoft co-pilot number three. Right? And Google was like,

Starting point is 00:26:35 Yeah, all right, yeah, there. You know, number four, maybe they can catch up top free. And I think one of the reasons was that they didn't have a front door to AI. It was a very fragmented approach. And I think one of the reasons why when I would go around to both in-person rooms and digital rooms and, you know, asking all the people who used Google, hey, how many of you use Google Gemini? And so few hands went up. And I think one of the reasons is it had a problem connecting to its own services. Google Gemini had a ton of issues connecting to its own services.

Starting point is 00:27:15 Even Google search, right? Even Google search. I've detailed this way, like way too much probably, especially in late 2023 and early 2024. So you have to think, is it too little too late? Like I said, the enterprise platform looks impressive. everything on paper, you heard the features. They're checking all the boxes.

Starting point is 00:27:38 But Chad GPD is the user leader by a lot. And Microsoft is the literal operating system owner, right? And I don't think you have to worry about Apple. So is it too little too late for Google, Gemini, to be a the top-tier enterprise AI company? Let's look. So right now, Chad Chb-T says they have 800 million weekly active users. All right.

Starting point is 00:28:13 Google Gemini last reports 450 million, but they are gaining. And they are gaining especially across their different platforms like Notebook, Notebook L.M, nano banana, right? They're coming out with all these, you know, other products that, you know, I do see now that they're integrating into the enterprise platform as well. The enterprise platform has a direct tie-in into notebook LM. You can use their very viral V-O-3, their image generator as well. And then you have Microsoft Copilot with 100 million monthly active users.

Starting point is 00:28:52 So 100 million Microsoft Copilot, Google Gemini across their apps, 450 million. But can anyone catch ChatGBT, Well, you know, chat GPT, that's just total users, 800 million. Microsoft copilot, I would guess that the majority of theirs, not 100 million, but they have a pretty high percentage of paid users because of their early on stranglehold on the enterprise. They were the first enterprise company to come out with AI for the masses. But Google Gemini, I would say, is far behind. You know, most enterprise companies I talk to, they are.

Starting point is 00:29:33 on Microsoft co-pilot, many of them aren't fans. Many of them are also using chat GPT at the same time. So, you know, I think what it boils down to is number one, can Google Gemini convert a lot of their kind of middle tier businesses, ones that maybe aren't quite big enough to want or need Microsoft co-pilot, you know, can they win over the, Mac crowd, right? Because if you're Windows PC organization, which so many, especially in the US, so many enterprises run on, you know, Windows PC. So for everyone else, right? So you think, okay, who's the Mac crowd, right? Startup, small medium businesses. A lot of them were early on

Starting point is 00:30:23 flocking to chat GPT. And Chad GPT's enterprise, right? I think they've reported that I think it's more than 90% of the Fortune 500 use chat GPT. So can Gemini cut into each of their lead? And I think, yeah, maybe they can. But before, I'm going to end on that. Before, I'm going to give you some of my thoughts so far by using Gemini business. So the Asian builder, it's okay. I don't have a ton of practice in it so far.

Starting point is 00:30:58 it's a little limited in how you can build the agents, right? It's not one of those, you know, when you see that the kind of nodes, right? That's what I have on my screen. It's similar if like, if you're looking at a screenshot, it's similar to Open AIs, agent builder that they just released last week, but, or this week, but the agent builder has way more configuration instructions, right? And I think it's also like when you're working with nodes like these drag and drop little boxes on a canvas, you assume you can move them all over and, you know, have all these tears. And I don't know, maybe I'm just not good at it yet, but it seems very limited in functionality so far in terms of what you can do to customize the agents.

Starting point is 00:31:48 However, the performance in my limited testing is pretty good. Right. So it's maybe one of those things. If I had, you know, if I had, you know, SAP data, if I had, you know, Salesforce, if I had these other platforms, maybe I would get more utility out of the agent builder. But it's simple, straightforward. And the performance is good so far. May not be super robust and flexible, but for what you need, it may do the job. One of their agents I like, obviously, is their deep research agent.

Starting point is 00:32:24 And one of the reasons I like this is because it also connects to any of your connectors, right? So, you know, whether it's the Google products, Confluence, Gira, OneDrive, Outlook, et cetera, right? Any of your connectors, you can run their deep research agent across all of that data. And it's dynamic. So overall, my thoughts personally. The first, I mean, if you look back at it, The first iterations of Google's main AI products, aside from Notebook LM, haven't been very good. Some of them have been bad, right?

Starting point is 00:33:07 Remember Bard? Bard wasn't good. First version of Google Gemini wasn't good. When Google rolled out Gemini in workspace, it was bad. Not that it wasn't good, it was bad. It got better, right? Google AI studio was okay, but it was clunky. Now it's a beast, right?

Starting point is 00:33:29 Google Gemini itself when it came out was bad, right? Like I said, but Google Enterprise or Google, you know, Gemini Enterprise or Gemini business is actually starting off really good, right? First version of Chat ChbT also, full disclosure, absolutely terrible. Absolutely terrible. I hated it. I didn't use it. Right.

Starting point is 00:33:53 Or I was using other versions of that technology, you know, at the time through other platforms. First version of ChatGBTGPT was awful. First version, Claude was awful. Right. So it's not like I'm picking on Google's first iteration of AI products. That's just the truth. But when I'm using Gemini Enterprise, I'm like, wait, this is pretty impressive, right? And let me give you just one example.

Starting point is 00:34:19 So I ran the same prompt. connected to and I ran it across four different platforms. So I ran it across my Google Gemini Pro account, my new Google Gemini business account. That's grounded keyword there. Okay. Then my chat GPT pro account and then my paid Claude account too. I forget if that's a pro or what the heck it's called. All right.

Starting point is 00:34:51 Same prompt. I connected all of the same things. I connected my Gmail, my Google Calendar, and my Google Drive. Ran the same prompt. A couple times, different variations, trying to trick each system each time. I couldn't trick Google Gemini business. I couldn't. It didn't get anything wrong either.

Starting point is 00:35:19 In the sourcing, because it's a grounded model, was extremely impressive. It was markedly better. And at least for me, because I suck at keeping up with things, and because of the podcast, I get so many emails, I can't keep up.

Starting point is 00:35:36 One of my kind of recurring prompts or actions is always, you know, checking my calendar against my Google Drive, against my Gmail. And now I'm going to be using, I'm going to be using this new Google Gemini business for that. And it is ridiculously good. All right.

Starting point is 00:35:59 So final take? Well, I don't think that Google Gemini overnight is going to take away very much market share from Chad GPT or co-pilot. However, I do think they're going to take small market share. from each of them. Because it makes sense. I think for certain companies, it makes sense. I think for companies even

Starting point is 00:36:31 that are Microsoft PC companies, well, I think Google Gemini can win share from them because unless they are deeply ingrained and have a great internal Microsoft training program at your company, well, Google Gemini

Starting point is 00:36:50 integrates with the Microsoft 365, you know, suite of products. Not all of them, but the main ones, right? So I think they can take market share from them. What about chat, GBT, right? Well, the fact that you are grounded in data, right? So for me, for me, I use Gmail. I love chat, GBT. the fact that I can ground everything in this new Gemini business and Gemini Enterprise means

Starting point is 00:37:25 that I'm going to be using Chad GPT less. The difference between a large language model being grounded in your data versus it, you know, going through kind of more of a, you know, going out and looking at files individually. It's a huge difference. And from a pricing perspective, too, right? Gemini Enterprise, half the cost of Chad GBT, BT Enterprise. So for me personally, I would still probably use both, right? But I know many enterprises, right?

Starting point is 00:37:57 If you're paying for tens of thousands or, you know, thousands of seats, you got to make a decision. So a lot of people, when they roll out an enterprise account with Chad GPD as an example, they start with, you know, 100 seats and then they go up to 500, and then they go up to a thousand. So I think that Google Gemini actually has a legit shot at picking off a decent amount of business. I think they can pick off for Microsoft co-pilot just because their models are better overall, top to bottom. And Microsoft is starting to diversify their models from not just Open AI. And I think they may pick off some either current enterprise customers or prospective enterprise customers from OpenAI. as well on price.

Starting point is 00:38:46 But the big takeaway here, Google before this, I don't think that they were a top two player in team enterprise AI, right? For developers, IT, right, their vertex platform, Google AI Studio, but for teams, I don't think before this,

Starting point is 00:39:09 Google was a top two player. Now they can be. All right. And it's going to be more competition at the top, which means that we all win. So that's my final take. I hope this show was helpful as we went over the new features in Google Gemini Enterprise. So if you missed anything or if you just need a little more clarification, don't worry. We're going to have it all in the newsletter. So make sure you go to your everyday AI.com. Sign up for the free daily newsletter. If this was helpful, if you're listening on the podcast,

Starting point is 00:39:45 please make sure to subscribe, like, and follow the show. Thank you for tuning in. Hope to see you back tomorrow and every day for more everyday AI. Thanks y'all. Meet Firefly AI Assistant. Now live in Adobe Firefly, the Allman One Creative AI Studio. Just describe what you want to create in your own words, and the assistant handles the rest,

Starting point is 00:40:08 orchestrating multi-step workflows across Adobe Creative Cloud apps, including Photoshop, Premiere Express, and more in one conversational interface. You direct the Outcast, come while the assistant accelerates execution. Stand control with the ability to step in and refine at any time. See it today at firefly.adobie.com. And that's a wrap for today's edition of Everyday AI.

Starting point is 00:40:36 Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit Your EverydayAI.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next. time.

Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 629: Google’s surprise release: Will Gemini Enterprise Compete with ChatGPT and Microsoft Copilot?

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.