Set Low AI Goals. Automate the Obvious. Fail Quietly.

Fortune magazine or the Fortune website has published this article right here that if you're a leader, it will lead you into AI hell. You are going to fail at your project. You're going to fail as a leader. And I want to focus on the two topics, the two points they make in this article that are absolutely flawed and why they're flawed. So the first thing, um, the first point they make that is completely wrong, you should avoid as a leader, is that they say that successful AI adoption in business involves focusing on mundane tasks that can be automated, leading to immediate productivity improvements and freeing up teams for innovation. Focusing on main on mundane tasks leads to innovation. I mean, there's the red flag right there. AI will take you to the next level. It connects dots and looks at all your different data points that you have. It looks at your process, your procedures. It looks at your governance. It looks at what you're doing. It physically can look at what you're doing. It can sense things. It puts all these data points together to identify what you have missed. And one of the two main points of this article here is to focus on mundane tasks, which are predefined tasks that you've been doing forever. So you're spending your huge budget on all these AI technologies, state-of-the-art, and just focus— supposed to focus on mundane tasks. Why? So that you can say we accomplished something, that we used AI, to achieve something. Do you want to be that leader? Do you want to be the leader who says, yes, we've used AI and we have achieved our successful goals that we set out, and your goals were negative? You achieve mundane tasks. The second point in this article that it focuses on, that wants you to believe as a leader around AI is that it says organizations are redefining their metrics for success as AI changes how value is created. Okay. This involves focusing on specific use cases and defining hard and soft KPIs. What it's saying is lower your KPIs, assign KPIs that can be achieved to say that our AI project has achieved its goals. The premise behind AI when you're using it to its maximum is identifying a new revenue model you haven't seen before. The point AI It is supposed to challenge your existing KPIs and for to identify the fact that your existing KPIs weren't even the right KPIs. The point of AI is to identify new procedures, new governance, new processes, new markets. And if all these things are new, How can you put on a KPI around them? You've never seen them before. You've never been in that market before. This article will make you as a failure as a leader going forward. You want to implement AI? Do the opposite. I'm not— I am attacking the article, but I'm not— my point is not to attack the article. My point is to help you. My point is to you, you need to be careful about what you read and what you believe, because I know you're in a situation where you are desperate to find out what is the right thing to do. I have AI advisors. I've created a team of AI advisors, and we looked at this article and we tore it apart a thousand different ways. I was actually shocked that they didn't come back with one positive piece of advice. Not one single piece of advice that was positive. So we're completely in agreement. But that shows you how I lead. I work with a team of AI advisors, the smartest minds in the world, all work with me. When I look at a project, I look at a task, they help me to see it in a 360-degree view and see things that I didn't see before. This article is saying set low KPIs and focus on mundane tasks. I'm saying surround yourself with an AI team, a virtual AI team, an AI advisory board. I set that up for CEOs and leaders all over the world. And then you don't have to listen to articles like this that just absolutely will send you down the wrong way, the wrong path, and you will fail. And I know you're concerned about failing, and I'm here to help you out. Message me if you want to know more and how you can set up your own AI virtual advisory team. Until next time.