Discussion Guides
Situational Leadership® Book Discussion Guide
Use the questions in this guide to stimulate insightful discussion into how you can use the core concepts of the …
Many leaders are adopting AI to accelerate their impact, using it to streamline decisions, draft communications and synthesize complex information. The technology offers speed, clarity and efficiency in ways that feel almost irresistible. Yet not all AI adoption is a good thing.
Some leaders are unintentionally leaning on AI to avoid the harder, messier parts of leadership, like ambiguous situations and interpersonal conflict, because AI feels faster, cleaner and more predictable than navigating human complexity. When leaders use AI to replace judgment, presence or accountability, it becomes a crutch.
The future of effective leadership depends on using AI in ways that strengthen distinctly human capabilities, not substitute for them. As a leader, you can learn to recognize when AI is supporting leadership versus when it’s quietly eroding it, and what to do to stay on the right side of that line.
Overreliance on AI rarely looks dramatic. Instead, it shows up in small, everyday behaviors that gradually shift responsibility away from the leader. The key is to spot these early warning signs before they become habits that weaken leadership capability. Three common patterns reveal when AI crosses from a support tool to a crutch.
Leaders can start to rely on AI to make sense of situations they haven’t taken the time to understand themselves. They ask a chatbot to diagnose a struggling team member from a few bullet points or request a synthesis of a conflict the leader has never observed firsthand. The tool provides an answer, but it lacks the context that only direct observation can provide.
Decisions made this way feel efficient but miss the organizational history, team dynamics and relational nuances that determine whether an intervention will actually land. Over time, leaders who hand off judgment this way stop building the diagnostic skill that effective leadership requires.
Consider the director who asks AI to analyze low engagement scores and recommend a plan, then implements the solution without ever speaking to the team. The intervention lands flat because it wasn’t built on actual context. Or the new leader who pastes a peer’s Slack messages into a chatbot to decode their meaning instead of asking a clarifying question. The AI’s interpretation feels confident but misses tone, history and relational dynamics it cannot access.
AI-generated scripts, talking points or feedback drafts are efficient, but leaders who default to using them sidestep the emotional labor of a hard conversation. The feedback from AI is polished but disconnected.
Team members notice when language doesn’t sound authentic, sensing when a leader is reading rather than speaking from genuine engagement with the situation. The conversation may check the box procedurally, but it fails to do the relational work that builds trust and accountability. Leaders who consistently avoid this emotional labor don’t develop the capacity to navigate difficult moments with skill. They then become increasingly dependent on AI to handle what they find uncomfortable, creating a vicious cycle.
If a leader delivers AI-drafted performance feedback in a one-on-one, the feedback may be technically accurate, but the employee walks away feeling processed rather than seen. Trust erodes quietly. The same erosion happens when an executive uses AI to write every tough all-hands message. Over time, the team stops believing the words, and the leader’s voice loses credibility.
Leaders can start treating outputs as final answers rather than inputs that require interpretation. The AI doesn’t know your organization’s history, politics or values, but its fluent and confident tone can feel authoritative enough to shortcut a leader’s own reasoning.
When leaders stop practicing the reasoning that evaluates context, weighs trade-offs and considers second-order effects, they lose the skill. The tool becomes a substitute for analytical capacity, resulting in cognitive atrophy that can be hard to overcome. Decisions made this way may be fast, but they lack the judgment that comes from wrestling with complexity rather than outsourcing it.
An HR leader who selects a final candidate based solely on an AI-generated ranking of resumes makes an efficient decision but an uninformed one. The ranking didn’t account for team dynamics or the growth trajectory the role supports. Three months later, when the fit isn’t right, the efficiency of the decision becomes its own liability.
AI excels at analysis, pattern recognition and content generation, but leadership requires additional capabilities like communication, adaptability and critical thinking. Leaders who lean on AI to bypass these responsibilities risk weakening the trust, credibility and team cohesion that keep organizations aligned during change.
As AI’s capabilities grow, core soft skills shouldn’t diminish. They become more essential because they address crucial workplace needs that AI cannot fulfill.
AI can summarize a meeting transcript, but it cannot notice the signals that reveal what’s really happening beneath the surface. It can’t notice:
Emotional discernment shows up during a restructuring announcement, when a leader notices two team members exchange a glance and stay silent. That single observation prompts a quick private check-in that surfaces a concern never captured in surveys or transcript summaries. The leader addresses the issue before it becomes a larger problem because they were present and attentive in ways AI cannot replicate.
While AI tools can produce a strategy summary, they cannot decide what the strategy means for this team, given everything they’ve just been through. A leader’s meaning-making ability helps teams interpret uncertainty, connect their work to purpose and navigate ambiguity.
For example, a leader sits with their team after a strategic pivot and reframes the change in terms of how it affects day-to-day responsibilities, what remains constant and what growth paths it creates. Engagement holds steady. A peer team that received only the leadership memo without this meaning-making conversation sees turnover spike. The difference isn’t the quality of the memo. It’s the human work of translation and connection that ties directly to engagement and retention outcomes decision-makers care about.
AI is great at drafting messages, but only a human can stand in front of the team, acknowledge what went wrong and stay in the room afterward. That’s courageous presence. It means showing up in hard moments, taking responsibility publicly and modeling the behavior the team needs.
When a project misses a critical deadline, the leader who gets on camera to own the miss, name what will change and answer unscripted questions builds credibility rather than losing it. The team’s confidence in leadership goes up because they witnessed accountability in real time.
AI is a powerful tool, but it becomes a liability when leaders use it to avoid the real work of leadership.
The healthiest approach is one where AI accelerates operational tasks but never replaces the relational, emotional and meaning-making responsibilities of leadership. Leaders who strengthen these capabilities build the trust, alignment and resilience that carry teams through change.
The Center for Leadership Studies (CLS) offers training that builds the human leadership skills AI cannot replace. Our Situational Leadership® Essentials course provides the foundation for diagnostic judgment and adaptive communication. The Situational Change Leadership™ course equips leaders to guide teams through the ambiguity, disruption and rapid change that AI adoption itself accelerates.
Contact us today to learn how to strengthen the leadership capabilities that ensure AI remains a tool, not a crutch.
