Why Leaders Must Develop an Intuition for AI

 

I am frequently asked by executives whether effective leadership in the age of artificial intelligence now requires technical fluency, whether they must learn to code, understand models, or master the mechanics of algorithms. My answer is consistently no. What leaders do need, however, is something far more important: an intuition for how AI creates value and how it reshapes judgment, decision-making, and accountability.

The most profound shift AI introduces is not technical, but conceptual. For decades, technology discussions in organizations have focused on automation, using systems to execute predefined steps more efficiently. AI moves us decisively into an era of augmentation, where systems actively participate in shaping decisions and triggering actions. This requires leaders to rethink how value is created. Instead of simply being data-driven, organizations must become decision-driven: starting with the decisions that matter most, then designing data, models, and workflows to support or even execute those decisions. Once leaders grasp this, AI conversations naturally become strategic rather than technical.

Although AI is often framed as a collection of impressive capabilities, generating content, writing code, visualizing data, automating workflows, its essence is much simpler. At its core, AI compresses the distance between data and action. Historically, data science and analytics relied heavily on human intervention. Data was cleaned, transformed, analyzed, and handed off to people who interpreted results and decided what to do next. That paradigm still exists, but it is no longer the only one. Increasingly, intelligent systems are capable of moving data through a defined process and producing outcomes directly. The difference is comparable to using a navigation app that recommends a route versus a self-driving system that takes you to your destination.

 Much of the confusion surrounding AI stems from the tendency to conflate different approaches. Robotic process automation excels at executing repeatable, rules-based workflows. Traditional machine learning focuses on learning patterns from historical data to enable prediction, classification, and forecasting. Generative AI represents a fundamental shift: models are pre-trained, and value is created through human intent expressed via prompts, often augmented with organizational data. Agentic AI goes further still, allowing systems to reason, retain memory, and act autonomously within defined boundaries. These are not competing technologies, but complementary design patterns. The leadership challenge is knowing which to apply, where, and under what level of human oversight.

This is where intuition becomes indispensable. Leaders must develop a feel for which activities should remain human-led, which can be augmented by AI, and which can be delegated to machines entirely. This is not a binary decision; it is a spectrum. Misjudging it can lead to either underutilizing AI or over-automating critical areas of judgment and responsibility. Developing AI intuition allows leaders to navigate this spectrum thoughtfully.

AI also disrupts long-held assumptions about creativity, learning, and strategy. It is often argued that machines cannot assist with open-ended or creative work. In practice, AI can significantly extend human creativity, helping leaders explore strategic options, stress-test assumptions, and synthesize complex information under time pressure. In learning and development, AI challenges traditional curricula but also offers the opportunity for deeply personalized, adaptive learning at scale. In research and analysis, AI no longer just crunches numbers; it interprets them, providing context and insight that once required teams of analysts.

Ultimately, developing intuition for AI is not about mastering tools or terminology. It is about understanding how human judgment changes when machines can reason and act alongside us. Leaders who build this intuition will engage AI with confidence, ask better questions, and design organizations that use intelligence, human and artificial, responsibly and effectively. Those who do not will find themselves reacting to AI-driven change rather than shaping it.

 

About Me:

Dominic “Doc” Ligot is one of the leading voices in AI in the Philippines. Doc has been extensively cited in local and global media outlets including The Economist, South China Morning Post, Washington Post, and Agence France Presse. His award-winning work has been recognized and published by prestigious organizations such as NASA, Data.org, Digital Public Goods Alliance, the Group on Earth Observations (GEO), the United Nations Development Programme (UNDP), the World Health Organization (WHO), and UNICEF.

If you need guidance or training in maximizing AI for your career or business, reach out to Doc via https://docligot.com.

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