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Hello, everyone. Here is Ricardo Vargas, and this is the 5 Minutes podcast. And today I want to talk about something that is becoming one of the most critical topics in project management today, the emerging risks of artificial intelligence. We are entering a moment where AI is no longer just a tool. It's becoming an active agent in decision-making, execution, and even in shaping the outcomes of projects. And recently, there has been a lot of attention and discussions around new systems like the METOS model developed by Anthropic. These systems are not just generating text or helping in simple tasks. They are capable of reasoning, interacting across multiple steps, and in some cases, operating almost like autonomous agents. And this is where the risk landscape changes completely. Traditionally, when we think about project risks, we think about things like delay, cost overruns, scope creep, or resource constraints. But AI introduces a completely new category of risks, the emergent risks. These are risks that are not explicitly programmed. They are not fully predictable and often not even visible until they happen. For example, an AI system interacting with other systems can create unexpected behaviors. It can generate outputs that are technically correct but strategically wrong. Or worse, much worse, these results can be manipulated. by an external agent that is not acting in good faith. And this brings me to one of the biggest concerns right now. Cybersecurity. AI is becoming both a powerful defense tool and a powerful attack surface. On one side, we can use AI to detect anomalies, predict attacks, and strengthen security. But on the other side, AI can be used to automate vision, generate malicious code, bypass controls, and even simulate human behaviors to deceive systems. And when you bring these into the project environment, the implications are huge, truly huge. Imagine a project where decisions are partially supported or even driven by AI. Now imagine that this AI is compromised, biased, or simply behaving in a way that no one anticipates. Who owns the risk? Who is accountable? This is a fundamental shift, because in the past, risks were tied to human actions, process failures, or external events. Now risks can emerge from the interaction between systems that no one fully understands. And this challenges one of the core assumptions of project management, that risks can be identified, analyzed, and controlled. With AI, this is no longer entirely true. We are moving from a world of known unknowns to a world of unknown unknowns on a much larger scale. So what can we do as project professionals? First, we need to rethink how we identify risks. It's no longer enough to list risks at the beginning of the project. We need continuous risk sensing. Second, we need to design controls that assume unpredictability. I'm not saying controls that prevent failure because these controls do not exist. I'm talking about controls that can detect and respond quickly when something unexpected happens. You know that magic off button? If something goes really crazy, maybe turning off is the only possible option. Third, and probably the most important, we need to reinforce human accountability. No matter how advanced AI is, responsibility cannot be delegated. Because the moment something goes wrong, it's not the AI that will be held accountable. It's us. So as we adopt these powerful technologies, we need to be very clear about one thing. AI can accelerate projects, AI can improve decisions, but AI can also introduce risks that are fundamentally different from anything we have managed before. And understanding these risks is no longer optional. It's essential. Let's think about that this week. I hope you enjoyed this podcast and see you next week with another 5 Minutes podcast.
