302 | ChatGPT 1B user milestone but slips below 50% market share, GLM 5.2 takes the lead in coding, Microsoft CoPilot Cowork now available, and more AI news for the week ending on June 19 2026

**Isar Meitis** (0:00)
Hello and welcome to a weekend news episode of the Leveraging AI Podcast, the podcast that shares practical, ethical ways to leverage AI to improve efficiency, grow your business and advance your career. This is Isar Meitis, your host, and we had a very interesting week this week. Nothing crazy major happened, but lots and lots and lots of small things did happen. And we are going to talk about all of them in this show. So this is going to be more of a rapid fire, beginning to end kind of session, but in bulk of specific topics. The first topic we are going to talk about is the burning competition in the AI space and a few interesting things that happened this week. We are going to talk about AI security and governance as a big topic as well. As it is becoming a bigger and bigger issue, we are going to talk about agentic platforms. Again, not surprising. I think that's going to be a weekly thing from now till forever, or at least in the foreseeable future. So we have a lot of things to cover, so let's get started.
The first topic I want to talk about is that OpenAI just reached a huge milestone which is reaching over a billion monthly active users in just three years after it has launched its platform, or three and a half years if you want to be more specific, which is significantly faster than any other platform in history. So Facebook took eight years to get to a billion users, YouTube took eight years to get to a billion users, TikTok took five years to get to a billion users, and ChatGPT did this in about three and a half years.
That being said, Sam Altman has been very clear in the past few months that profitability doesn't seem something is even on the horizon. But with that being said, it is very unclear how OpenAI is actually going to become profitable. If you want, the quote from a few weeks ago from Sam Altman who said, and I'm quoting, no current plans to make revenue and no idea how we may one day generate revenue. And his plan is basically once they reach AGI, asking the AGI to give them ideas how to become profitable. But what he's saying, that's not his worry. His worry is about developing better and better AI solutions to support humanity. And so when you hear this, when a company is growing to a billion users and still bleeding crazy amounts of money on the year they're on the verge of IPO, it is very interesting to see how the IPO is going to go forward. We're going to talk a lot more about this as we hear multiple sides of the OpenAI story. To me, the bigger story that nobody talked about when they were mentioning the 1 billion users, which is definitely impressive, is that they reached 900 million users and crossed that sometime in beginning of Q4 of last year. So they were growing significantly faster before and they kind of plateaued since. And while 1 billion users is a huge milestone, it seems to be on the slowdown of adoption of ChatGPT specifically, definitely not AI as a whole. Now, to make it more specific, another big milestone happened this week, which is ChatGPT's global market share decreased below 50% for the first time. So in the beginning of May, which was the last time we got this number, they were just above 50%.
And now the latest news at the end of May is 46.4% global market in the AI space. That is still a huge lead over number 2, which is Gemini at 27.7.
But it is definitely a shrinking gap from a percentage perspective. And if you're wondering about where Anthropic is in that mix, they are at 10.3, seeing an explosive growth, but still from a market share perspective, significantly smaller than ChatGPT and Gemini. So Claude's year-over-year growth has been 640%, while ChatGPT's has been 62%.
So 10x faster growth in percentages. Again, in total numbers, they are still significantly smaller or not in total numbers, but in total percentage of global market share. All this data is basically based on Sensor Tower report that just came out.
Now, if you're wondering where are all the other players, such as Grok from SpaceX, previously XAI, and Proplexity and Meta and DeepSeek, and all of those collectively account for less than 5% of the total AI-assisted market space right now, which is basically telling you it's a three-horse race and that's it. It is ChatGPT, Gemini and Claude, and it is very obvious that in this race right now, ChatGPT and Claude from Anthropic are focusing completely on enterprise and businesses, while Gemini is still more focused on consumer, and they're slowly making moves into the enterprise space. It wasn't like a code red like happened in ChatGPT a few months ago, at the beginning of the year where they flipped everything they did, and then they canceled Sora and took very clear actions to push Codex and focus on enterprise and code usage. By the way, the Tuesday episode this week is going to be how to use Codex for things that are not creating code, which I think you will find a lot of value in if you did not jump ship yet to the Claude universe and you're still in ChatGPT and just want to grow in the agentic direction. Or if you have moved to the Claude universe, and you're considering what's happening on the OpenAI side, it will definitely open your eyes on how much progress they made with Codex. But back to the news, another thing that OpenAI is doing right now to aggressively push their dominance or their market share in the enterprise space, they just announced that they're launching a partner network and they're investing $150 million in that. So on June 14th, they announced OpenAI partner network and that they're going to be investing, like I said, hundreds of millions of dollars to help enterprises move beyond AI pilots into real world impact. They are in the process of training 300,000 consultants by the end of 2026 That's a very aggressive timeline. The network launch partners are the elite of the elite. It's Accenture, Bain, McKinsey, PWC, all the obvious suspects. And the goal is to create a huge capacity to help and implement AI across different companies around the world. The partners progress through select, advanced and elite tiers based on their sales performance, technical capability, deployment experience, and with specific specializations in different areas such as Codex, cybersecurity, AI agents, etc. So it is an entire training program that is designated to help other companies, again, consulting companies help other businesses implement specifically OpenAI platforms in a successful way. They've shared multiple success stories with, for me, the most exciting and impressive one is in early deployments, Paycheck achieved 80% reduction in wait time and 30% reduction in effort for payroll processing. That is very significant. And I can tell you from the work that I am doing with companies, so I'm working with multiple companies around the world, from small businesses to large enterprises and holding companies and helping them implement AI through multiple platforms, not specifically OpenAI. And the benefits that I'm seeing are incredible. And the biggest benefits come when you train the actual people in the organization on how to implement AI themselves versus hiring consulting companies to do it for you. Now, I'm not saying there's anything wrong with hiring consulting companies, but the benefit of having employees from multiple departments know how to do this themselves is a huge benefit because they themselves are the people doing the work. They understand the pain points, they understand limitations, they understand the exact processes and their ability to create magic is absolutely incredible. And again, I'm seeing this time and time again. I just did a workshop this past week to a large organization. This was the second workshop in two weeks for the same organization. And between these two workshops, one of the people came and developed an incredible dashboard that takes together information from multiple sources and is going to dramatically improve their efficiency and reduce the amount of fees they're currently having and improve their cash flow by being able to deliver what they're delivering in a more effective way, taking into consideration multiple priorities and data points. He did it on his own and he did it a week after the first training that he got before the second training. And the reason he was able to do this is the fact that he understands exactly what the pain points are. He understands the data and he understands what benefits he can gain by doing very specific things and getting into specific insights, which will be very hard for a consultant to understand. I mean, it's doable, but the consultant will have to interview, review and create programs and plans and do a lot of things that are just overhead when the people are doing the actual work just understand what's going on. And they can do this very effectively if they are taught how to do this, which is exactly what I'm doing. And so I highly recommend to you if you are looking for ways to accelerate and improve the efficiency of your organization, don't miss out on this really incredible technology and come and find somebody. It doesn't have to be me, but to train your actual people on how to implement AI effectively because the results are life changing. It is really very, very different than anything we've seen so far. But now back to the news and back to OpenAI and why they're doing what they're doing, which relates back to something you heard me say multiple times in this show, is that OpenAI themselves has stated that the model capabilities are no longer the limiting factor. I've been saying this for at least a year now. All the models are good enough to do probably 80 or 90 percent of the knowledge work we're doing today. If you know what you're doing, if you can connect your data effectively and securely, etc. And so this is exactly why they've established this group or this partnership program, so they can have other people help companies solve that, including change management at scale, including driving adoption, including all the things that are not related to how powerful or capable the model is. Staying on the topic of adoption and competition in the space, Microsoft and Anthropic finally made Microsoft Copilot CoWork generally available.