Sensemaking: The Leadership Skill That Will Define 2026 & Beyond

Sensemaking is the leadership skill that will define 2026

Sensemaking will define leadership in 2026 because it sits at the intersection of AI, decision-making, and adaptability - three forces that are fundamentally reshaping how work gets done. It’s not a hard skill or a soft skill in the traditional sense. It’s a meta-skill, and it becomes more essential the higher you move in an organization. For executives and senior leaders, it is no longer optional.

This isn’t a trendy leadership concept. It’s becoming a survival competency because the modern operating environment is producing more information, more change, and more uncertainty than most organizations are designed to handle. In that kind of system, the leader who “moves fast” isn’t necessarily the leader who performs well. Often, they are simply the leader who creates momentum - sometimes in the wrong direction.

AI has accelerated this challenge. It has made it easier than ever to generate options, strategies, and recommendations. But it has not made it easier to determine what matters. If anything, it has increased the volume of competing narratives and plausible directions a leadership team can pursue. In parallel, leaders are navigating an always-on stream of news, internal updates, market noise, and urgent requests - each optimized to demand attention. 

The result is predictable: leaders are asked to make high-stakes decisions in an environment that erodes focus and clouds judgment.

This is why the competitive advantage in 2026 will not come from having better answers. AI will ensure that answers are abundant. The advantage will come from having better clarity. Sensemaking is the discipline that produces that clarity.

AI is speeding up problem-solving, but weakening problem identification

Most leaders have been trained, formally or through lived experience, to prove their value through problem-solving. You see an issue, you name it, you take action. In stable environments, that works. In complex environments, it becomes a trap. The game has long been “have the right answer,” but in a world flooded with uncertainty and competing signals, the more valuable capability is identifying the right question.

Under pressure, leaders naturally gravitate toward the first problem they can clearly see. Not because it is the most important problem, but because it reduces uncertainty quickly. It creates immediate relief. It gives teams a sense of forward movement. It signals decisiveness. The challenge is that the first visible problem is rarely the real one. More often, it is a symptom, an outcome of deeper systemic issues such as unclear priorities, competing incentives, weak accountability, unresolved tension, or a culture that has quietly trained people to stay silent until issues become impossible to ignore.

This dynamic is increasingly common in organizations that have experienced sustained disruption over the last several years. In those environments, the primary challenge isn’t effort, it’s focus. Leaders struggle to determine where to allocate attention, energy, and political capital. Predictably, work begins to gravitate toward what feels measurable and defensible: projects with clear metrics, initiatives with visible progress, or tasks that appear urgent simply because they arrived in an inbox.

The real drivers of performance, however, are often less tangible. Teams begin selecting work based on optics rather than strategic importance. People attend meetings out of habit rather than necessity. Leaders say “yes” to maintain relevance rather than protect focus. In the absence of clarity, activity becomes a substitute for direction.

AI intensifies this tendency. It doesn’t just provide answers, it provides them at scale. It produces ideas quickly, recommendations confidently, and strategies persuasively. Under pressure, it becomes dangerously easy to mistake high output for high-quality thinking. The result is a pattern many organizations will recognize: more initiatives, more plans, more movement and less certainty about what problem is actually being solved.

This is where leadership must evolve. The executive role is shifting from problem-solving to problem identification. Not “What should we do?” but “What’s actually happening here?” Not “How do we fix it?” but “What are we really solving for?” Not “What’s the next step?” but “Are we sure we’re working on the right thing?” This reframing is what separates reactive leadership from strategic leadership.

When information becomes abundant, clarity becomes scarce

AI is often positioned as a tool that will improve decision-making. In practice, it is increasingly making decision-making harder. The reason is simple: decisions don’t break down because organizations lack options. They break down because teams lack alignment on the problem. AI can generate endless plausible paths forward, but it cannot tell you which one matters unless leadership has already clarified what success looks like and what tradeoffs the organization is willing to make.

Without sensemaking capability, more information doesn’t create confidence—it creates confusion. Teams get stuck in debate mode. Executives second-guess decisions or reverse direction more frequently. Meetings multiply. Decisions slow down because the cost of being wrong feels higher when there are twenty other plausible options on the table.

Ironically, the more AI helps teams generate solutions, the more ambiguity increases unless leaders can anchor the conversation in meaning, tradeoffs, and strategic intent. This is where sensemaking becomes essential. It is the discipline of turning information into insight, and insight into shared direction. It’s how leadership teams move from “what could we do?” to “what should we do?” and, more importantly, “why this, and why now?”

Sensemaking is the leadership multiplier particularly in an AI-saturated environment

AI is not the threat many leaders assume it is. The bigger risk is subtler: it overwhelms judgment by flooding the organization with plausible answers. In practice, AI increases the speed of execution far more than it improves the quality of thinking. It produces recommendations, narratives, and plans at a pace that can easily outstrip a leadership team’s ability to evaluate what is actually true, what is strategically relevant, and what deserves attention.

This is where sensemaking becomes a leadership multiplier. As an executive, your job is no longer to have the best answers. Your job is to ensure your organization is solving the right problem. That requires more than analysis. It requires disciplined inquiry to clarifying what matters most, surfacing what is being assumed, and distinguishing signal from noise before the business commits resources and momentum.

This isn’t a vague leadership trait or some intangible skill you can’t learn - it’s a practical process. It starts with emotional regulation, because reactive leaders don’t see clearly. From there, the next discipline is discernment to filtering what matters from what is simply volume, urgency, or distraction.

Once the noise is reduced, framing the problem and reframing as needed, clarifying the real problem, focusing solutions and orienting discussions towards what really matters. It is on this foundation that leaders use, and encourage, high-quality inquiry and gather perspectives to surface what’s missing and integrate different viewpoints early. This is where assumptions are tested and critical thinking can stress-test the story the team is telling itself.

Systems thinking helps to identify patterns, root causes, and second-order consequences.

Only then does the process narrow into strategic prioritization—the 1–3 issues that truly matter and finally decision architecture, where clarity turns into execution through explicit choices, tradeoffs, ownership, and next steps.

Emotionally regulated, discerning leaders frame and orient their teams around the right problem, then use inquiry, perspective gathering, and critical thinking, supported by systems thinking, to test assumptions, design experimentation, prioritize what matters most, and finalize clear decisions and next steps.

Sensemaking as an Operating Discipline

One of the most practical benefits of sensemaking is that these capabilities are fully within your control to develop and deploy. You may not be able to control outcomes in a complex environment, but you can control the quality of your framing, inquiry, prioritization, and decisions - and that is often what determines the outcome.

Practically, this shows up in how you run conversations. Sensemaking improves when leaders stop rewarding speed and start rewarding clarity. In meetings, this means pausing early to ask questions like: What are we treating as true? What would change our mind? What is the root cause versus the visible symptom? If we could only focus on one to three priorities, what would they be? These questions may feel slower in the moment, but they prevent expensive cycles of rework, misalignment, and initiative overload later.

Sensemaking is also a discipline of decision architecture. Many executive teams struggle not because they lack intelligence, but because they lack clean decision framing. Too often, decisions are made in rooms where people are answering different questions. AI exacerbates this by introducing more options and more analysis without clarifying the underlying tradeoffs. Strong sensemaking leaders correct this by forcing precision: What decision are we making? What are the constraints? What does success look like? What are we explicitly choosing not to do? When this framing is clear, decision-making speeds up—not because the environment becomes simpler, but because the organization stops wasting energy debating the wrong issue.

This is also how executives prevent change fatigue. Most people can handle change when it is coherent and anchored to a clear narrative of why it matters. What exhausts organizations is constant adaptation without meaning—new priorities, shifting messages, and relentless pivots that feel disconnected from a stable direction. AI accelerates this problem by making it easier to generate new initiatives and new communications at scale. Without sensemaking, the organization becomes busy, reactive, and increasingly cynical. With sensemaking, leaders create coherence: they connect decisions to strategy, reduce competing priorities, and provide context that helps teams understand not just what is changing, but why.

For leaders trying to scale, the real value of sensemaking is that it can be distributed. You do not need to personally interpret every signal or make every decision. What you need is to build a leadership culture that consistently asks better questions, challenges assumptions early, and frames work in a way that makes thinking easier across the system. Over time, this becomes a competitive advantage: fewer wasted initiatives, sharper accountability, faster learning loops, and more consistent execution.

In 2026, the strongest leaders will not be the ones who move the fastest or adopt the most technology. They will be the ones who create clarity in environments where clarity is increasingly rare. AI will ensure everyone has access to answers. Sensemaking will determine whether those answers create performance - or simply create noise.