Your employees are absolutely using AI and 25% or more are using ChatGPT

It is time to make AI standard issue for anyone who works in front of a computer. It is common to hear that 95 percent of large-scale AI projects fail according to MIT’s 2025 State of AI in Business report. I say SO WHAT. We are focused on the wrong thing and we are not talking about what moves the needle. 

While enterprise AI pilots may struggle, there is a wave of progress happening at the individual level that we aren't really talking about. According to recent OpenAI research (available below), 28 percent of employees are now using ChatGPT for work even if their company does not officially approve or pay for it. Employees are delivering results with or without company support. Is there a security risk? Absolutely. What is your company doing about it? Simply putting a note against AI usage in your policy handbook is not enough! 

When you look across all AI tools, about half of all employees are leveraging AI in some way. That means in any typical workplace two out of every four people are using AI regularly, even if the company does not officially sanction any tools. 

The value is clear. A Federal Reserve Bank of St. Louis study found that over half of frequent AI users save at least three to four hours of work each week. Harvard and MIT found that knowledge workers using generative AI produce work that is up to forty percent higher in quality compared to those who do not use AI. What is the real difference? The 95 percent failure rate applies to bigger enterprise projects using AI. Meanwhile, the real opportunity is to start small. Everyday tasks can lead the way to bigger and much more valuable AI automation. Hit me up! What do you see happening at your company? 

See more details of the study here: OpenAI Study 

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AI’s 95% Failure Rate Looks Just Like Cloud’s Early Struggles

**AI’s 95% Failure Rate Looks Just Like Cloud’s Early Struggles** MIT says 95% of AI pilots flop. Sounds scary, right? But this is not the end of the world. In fact, it looks a lot like the early days of cloud computing. Fifteen years ago, most cloud projects went nowhere. Security fears, messy migrations, and grumpy IT teams kept things stuck in pilot mode. Today, AI pilots are tripping on the same issues. Poor workflow fit, bad data, and unrealistic hopes keep projects from scaling. Here is the good news. Cloud eventually became the backbone of business. AI will get there too and probably faster since it is standing on cloud’s shoulders. So yes, most pilots fail. Think of them as practice rounds. The companies that stick with it and learn from the flops will be the ones cashing in when AI finally clicks.

We Are the QA for AI

We Are the QA for AI In my last post I wrote about Anthropic’s postmortem and how AI bugs do not look like the bugs we are used to. They hide in the answers. They are not obvious crashes. That leads to this. In the past if you wanted to complain or suggest a feature you went to a support page. Maybe you submitted a ticket. Maybe you took a screenshot of the bug and attached it. Then you waited. Maybe someone read it. Maybe they did not. AI is different. The thumbs up and thumbs down buttons are right there in front of you. No forms. No support tickets. Just a quick signal. And that signal matters. It is the easiest way to shape how AI learns and how reliable it becomes. This is still new. Most people do not think of themselves as part of QA. But with AI we all are. Every tap is a way to make the system better. I am an advocate for this. If you want better AI at work and in life, smash those buttons. **Labels:** AI Feedback, AI Reliability, Human Feedback, AI QA, Responsible AI

Bugs in AI Do Not Look Like the Bugs We Are Used To

Bugs in AI Do Not Look Like the Bugs We Are Used To When software would break in the past it was often obvious. The screen froze. The app crashed. You knew you had a bug. AI is different. When it breaks the system keeps going. It still gives an answer. But something is off. A word out of place. A weaker response. A sentence that does not sound right. Anthropic’s postmortem showed this. Claude slipped Thai characters into English text. That is not a crash. That is a bug hiding inside an answer. This matters. The risk is not that AI stops working. The risk is that it keeps working while giving you something that is just a little wrong. And at work a little wrong can be a big problem. This is why the like and dislike buttons matter. They look small. But they are signals. They are how the system learns what can be trusted and what cannot. Smashing those buttons is part of keeping the AI useful. The old bugs broke software. The new bugs break trust. **Labels:** Anthropic, Claude, AI Reliability, AI Bugs, AI Trust

Microsoft Pushes Copilot Deeper Into Everyday Work

# Microsoft Pushes Copilot Deeper Into Everyday Work Microsoft is bringing Copilot everywhere. Starting in October the Copilot app will automatically appear on Windows devices with Microsoft 365 apps like Word, Excel and PowerPoint. In Power BI it is turned on by default. In Windows 11 it is being built deeper into the system. In retail it is being tested as a shopping assistant. This is what adoption looks like. Not a big launch. Not a dramatic shift. Just a steady blending of AI into the tools people already use. And it leads to a simple question. Will people even notice. Will they know when it is Copilot formatting, writing, or analyzing. Or will it feel no different from normal software doing its job. That may be the real turning point. AI is not something you start using one day. It is something that slowly becomes part of everything you already use. **Labels:** Microsoft, Copilot, AI Adoption, Windows 11, Microsoft 365, AI Integration

The Global AI Divide: Can Cell Phones Help Close the Gap?

The Global AI Divide: Can Cell Phones Help Close the Gap?

Newly released reports today on AI adoption do not surprise me. They show that clearly wealthier countries are moving fast while developing nations are being left behind. It reminds me of the early spread of the internet. At first, only a few places had real access, and it widened the gap before mobile phones helped bring more people online.

This makes me wonder about AI. Could cell phones play the same role again? Most people in the world may never own a powerful computer, but billions already have a phone in their pocket. If AI tools are built to run well on mobile devices, access could spread much faster. The question is whether large language models can become small enough and efficient enough to run locally on phones. With the right advances in chips and model design, this could become reality.

The big question is whether new phones and networks will make this possible. Will the next generation of mobile technology help close the divide, or will AI stay concentrated in the wealthiest nations? The answer will shape who really benefits from this revolution. **Labels:** global AI trends, AI adoption, Cell Phones, Local AI, AI inequality, mobile AI, digital divide

ChatGPT’s Branching Chats Feature: One Prompt, Many Possibilities

ChatGPT’s branching chats feature lets you explore multiple ideas without losing your original thread! This is perfect for writers, learners, and brainstormers who might smash up many different topics into one chat window as they work.

Do you ever find you are having multiple conversations in one chat with AI and wish take a part of that chat and create a new just with just that part. Sort of like you could explore “what if” without starting over? Today ChatGPT’s released is new branching chats feature which does exactly that. It lets you 'fork' a conversation at any point, testing out new ideas or directions while keeping the original thread intact. You can find this feature by clicking on the '...' three dots at the end of the chat and selecting 'Branch in New Chat'

How can you use it:

• Try different tones, answers, or questions side by side
• Keep your main idea while experimenting freely in another branched chat
• Perfect for writing, brainstorming, or learning new concepts

Branching turns every chat into a flexible workspace. Start once and explore endlessly.