AI can give leaders answers in seconds. But getting an answer and making a good decision are two very different things. As AI becomes part of how we research, solve problems, and evaluate options, leaders face an important question: Where does human judgment fit? In this episode of The Leadership Habit Podcast, host Jenn DeWall sits down with decision-making expert Cheryl Strauss Einhorn, creator of the AREA Method and author of The Human Edge: Smarter Decisions in the Age of AI. Together, they explore decision-making in the age of AI, including why leaders need to think critically about the problems they are solving, recognize both human and AI biases, and resist the temptation to outsource their judgment to technology. As Cheryl explains: “The problem with AI is we now have this answer machine. So answers are pretty easy to come by. And so what that means is that human judgment actually becomes far more valuable.” Meet Cheryl Strauss Einhorn Cheryl Strauss Einhorn is a decision-making expert, creator of the AREA Method, and founder of the decision sciences company Decisive, where she helps leaders and organizations solve complex problems and make better decisions. She is also an adjunct professor at Cornell University and the award-winning author of several books exploring decision-making, financial research, and the psychology behind how we make choices. Cheryl’s approach to decision-making grew out of more than two decades in investigative journalism, including over a decade at Barron’s. Her reporting required her to evaluate complex information, question assumptions, weigh evidence, and make high-stakes judgments with significant consequences. That experience ultimately led her to develop the AREA Method, a structured approach designed to help people recognize cognitive biases, expand their thinking, and make decisions with greater confidence and conviction. AI Has Answers. Leaders Still Need Judgment. AI has dramatically changed how quickly we can access information. But Cheryl argues that easier access to answers actually increases the value of human judgment. AI does not inherently understand why you are solving a problem. It does not know your organization, your stakeholders, your priorities, your constraints, or what success looks like for you. That is why Cheryl recommends turning to yourself before turning to AI. “What is the problem that I am solving and why am I solving it?” Without that clarity, leaders risk using AI to solve the wrong problem, even if they do it efficiently. Cheryl points out that even experienced leaders sometimes assume they understand the problem in front of them without taking time to define it clearly. The result can be solving an adjacent problem, addressing only part of the issue, or eventually having to start over. For leaders navigating decision-making in the age of AI, defining the problem is still a fundamentally human responsibility. Know When a Decision Requires a Process Leaders make countless decisions every day, and not every choice requires extensive analysis. But some decisions carry consequences that make a structured process especially valuable. Cheryl recommends looking at three factors: Is the outcome unknown? Is the cost of getting it wrong high? Will the decision have a long-term impact? When all three are present, leaders should slow down and use a deliberate decision-making process. Cheryl’s AREA Method stands for Absolute, Relative, Exploration and Exploitation, and Analysis. The process helps decision-makers examine different perspectives, challenge assumptions and judgments, gather evidence, and build greater confidence in their conclusions. A process also creates something leaders often miss: an opportunity to learn from the decision afterward. Instead of simply asking whether the outcome was good or bad, leaders can look back and evaluate the decision quality, whether they gathered the right information, considered the right perspectives, and followed a sound process. Are You Using AI Like a Surgeon or a Lamborghini Driver? One of Cheryl’s most useful distinctions is that leaders can approach AI and decision-making in two very different ways. When you need one specific piece of information, Cheryl suggests thinking like a surgeon. You make a precise incision, extract what you need, and move on. But many leadership challenges are not that simple. When you are exploring a complicated problem and do not yet know exactly where you need to go, Cheryl suggests thinking of yourself as a Lamborghini driver. AI may be an incredibly powerful and fast machine, but you are still behind the wheel. “You need to direct it.” In this mode, AI can help leaders research, analyze, explore, and refine their thinking. But the leader remains responsible for determining what they are trying to understand and where the process should go next. The distinction matters because using the same approach for every interaction with AI can lead leaders to extract information without first understanding whether it is the right information for the problem they are trying to solve. The Eight Human Moments That Matter in AI-Powered Decision-Making In The Human Edge, Cheryl identifies eight pivotal moments where human thinking remains essential: Defining the problem Assessing motivations Gathering context Researching effectively Analyzing options Recognizing biases Involving key stakeholders Building conviction These moments highlight an important limitation of AI: it cannot automatically know the context surrounding your decision. It does not know your budget unless you tell it. It does not know which stakeholders matter most. It does not know that you have until Tuesday to decide or that your organization is operating under a specific resource constraint. As Cheryl explains: “Something that looks plausible that doesn’t work for your context is something that can fail.” Leaders bring the context. AI can help process information within it. Human Bias Meets AI Bias AI does not eliminate bias from decision-making. In fact, Cheryl points out that leaders now have to contend with two sources: their own cognitive biases and the biases in AI systems. Human biases can include confirmation bias, where we look for information that supports what we already believe; liking bias, where we give greater weight to information from people we relate to or trust; and the planning fallacy, where we underestimate how much time or complexity a project will require. AI can also bring its own imperfections into the process. Its answers may be incorrect, outdated, biased, or based on information that does not accurately represent the situation a leader is trying to solve. But Cheryl also sees an opportunity. Rather than asking AI for an answer and accepting the first response, leaders can use the tool to challenge their own thinking. They can ask for disconfirming evidence, explore opposing perspectives, question the credibility of information, and look for weaknesses in the decision they are considering. The goal is not to have AI validate your thinking. Use it as one resource to strengthen your thinking. Speed Is Not the Same as Quality AI has made speed one of its biggest selling points. But faster decision-making does not automatically mean better decision-making. “Speed and efficacy are often different. The speed of a decision says nothing about the quality of it.” That distinction is especially important for leaders. Our brains naturally develop shortcuts based on previous experiences. Those shortcuts help us move quickly, but they can also cause us to apply yesterday’s assumptions to today’s problem. For high-stakes business decisions, Cheryl encourages leaders to create what she calls a “strategic stop,” a moment to evaluate whether the assumptions, information, and approaches that worked before still apply now. AI may accelerate the process, but leaders still need to know when slowing down will ultimately lead to a better outcome. Don’t Outsource Your Thinking Perhaps the biggest takeaway from Cheryl’s conversation with Jenn is that the future of leadership is not about choosing between human expertise and artificial intelligence. It is about knowing what each is good at. AI can research, analyze, generate possibilities, and surface information at extraordinary speed. But leaders still have to define the problem, provide context, evaluate assumptions, consider stakeholders, recognize bias, and ultimately decide what to do. Cheryl’s goal is to help leaders build the confidence and conviction to solve problems effectively, both with and without AI. “I really hope that people gain confidence and conviction that they can solve problems well, both with and without the machine, and that they don’t ever sacrifice their thinking.” As AI becomes more capable, protecting our ability to think critically is not rejecting technology. It is how leaders make better use of it. Where to Find More From Cheryl Strauss Einhorn To learn more about Cheryl Strauss Einhorn, the AREA Method, and her work on decision-making: Visit areamethod.com Connect with Cheryl on LinkedIn Explore her latest book, The Human Edge: Smarter Decisions in the Age of AI. Build the Leadership Skills AI Can’t Replace AI can provide information. Leadership requires knowing what to do with it. Crestcom helps leaders develop the practical skills they need to make better decisions, communicate effectively, navigate conflict, build emotional intelligence, and lead their teams with greater confidence. Experience Crestcom’s approach firsthand with a complimentary leadership skills workshop. In just two hours, you’ll explore actionable strategies you can put to work immediately and create a personalized plan for addressing your leadership challenges. Request your complimentary leadership skills workshop today. The post The
