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Hello everyone. Welcome to the 5 Minutes Podcast. In the past years, I have been studying neural networks, artificial intelligence, and machine learning, trying to identify the best use for this kind of tool to improve the results of our projects. And of course, the best way to do that is to evaluate the impact that that specific will have on project management in general and the complexity to implement that. Let me give you an example. Let's suppose that we find a way of using such a sophisticated way, artificial intelligence that we don't need people managing projects or managing teams. This would be absolutely transformative. If I cannot find I could not find a word that is more powerful than transformative in this case. It's just an absolute disruption of what project management is. However, the complexity of doing something like that, it's very high because most of the time we need to understand artificial intelligence is when you have data and the computer learns by using different methods and trying to predict behavior. And this is, for example, what DeepMind did on AlphaGo, for example. You start playing and at some point, you become such a master playing that game that you don't repeat any kind of mistakes. So for example, when the game starts in the first round, the AI loses everything and does really crazy moves in the game. However, over time, these mistakes, just disappear and it becomes an absolute master of that game. But when it's behavior, it's not easy. For example, it's not easy for me to take a project manager and transform that role into a completely artificial intelligence-based activity.
For example, AI to negotiate complex things. I'm not talking about negotiating the price of something. I'm talking about negotiating motivational aspects for your team because your team is not very motivated for that kind of job or the deliverable or the benefits of your project. This is a very complex environment. This is a very complex environment to manage. However, I want to share with you six possible use for artificial intelligence, and I want to frame them in a two-by-two matrix of impact and complexity to make it. Let's start with low impact and low complexity. I can tell you two tasks that will fall on this first estimated task effort. And what is that? It's, for example, based on the productivity, based on previous results of a specific resource or a group of resources, you can estimate the force that will be required to do another task. For example, I know, for example, that someone does this in 10 minutes. If the task becomes twice the size, it will spend 20 minutes. This is what is called in the past parametric modeling. But you use parametric modeling using artificial intelligence. The second one and this I already had a venture on that is the automation of administrative tasks, it's the use of chatbots. It's you automatically scatter a meeting based on specific behavior. For example, if that task becomes late, you create this condition, modeling that using AI, you can automate this kind of tool. This is also not extremely complex. However, both of them, have limited impact, moving a little bit more towards complexity, increasing complexity with the same low, low-to-meet level of impact in the planning of low complexity projects.
It's something like imagining a canvas-like Canva for social media, where you produce, for example, designs for your social media, for project management, for example, you want an event and then machine learning identifies based on some questions or based on some information you provide. What would be the best sequence of tasks? What would be the best scheduling for that? What would be the best set of resources? However, this is for low-complexity projects. It's almost impossible for you to take a nuclear power plant and try to use AI to repopulate this project. It would be a fantastic endeavor, but it's extremely complex to make now go into the high impact and meet complexity portfolio management. And this is for me, I would say one of the sweet spots today. Using AI. It's for using AI to help you to select the best set of projects for your strategic intent. You have, for example, a strategic direction. And based on this direction and based on previous years, previous projects, and learning capability, you can use AI to suggest to you what would be the best portfolio of projects. For example, you should do this project or that project, or you should do that project and this new project. So these would be a fantastic exercise on portfolio management and these are very impactful this is already happening in many areas now going into the high complexity and the high impact and these are excellent use, but I don't see this very close to us using the current technology.
It's very complex to make it. One is cost and risk forecast. It's to forecast risks. It's, for example, using data and using, for example, AI to see the possibility of COVID 2028 instead of COVID 19. So this is a super complex. It's like a weather forecast. Why do we have such a big challenge to forecast the weather? Because there are so many parameters that it's pretty much impossible for you to model all variables. And the other one and this is my dream. This is my dream is what I call team fitting based on the type of task, based on the type of project I will suggest to you who should do the task and will suggest to you which kind of profile you should hire to execute that specific project. So it's not only a mix and match. No, it's the use of AI to say, okay for you, if you have limited resources, it's better that you invest in this person with these skills than that other person with that other skills. And this is all using AI. This would be an absolute game-changer to the industry with a massive impact, but the complexity to do that is very high. But I truly believe that these will happen at some point in our future. So this is what I have for the podcast today. So think always about these uses of AI, because I think this is a technology that will be really part of our life.
And see you next week with another 5 Minutes Podcast.