By Kat Rippy, M.S. & Ashley Seeley, Ph.D.
AI isn’t just coming for the workplace—it’s already here, moving faster than most companies can adapt. It’s in every conference keynote, ad campaign, and strategic plan. Yet despite the buzz, one truth stands out: we still don’t fully understand what an AI-driven future will demand from human talent.
The Disappearing Middle and Resulting Leadership Void
The early signals are undeniable.
According to Korn Ferry (Pearlman, 2025), companies are "aggressively thinning out their management midsections.” Leadership roles are shrinking. Layoffs are rising. And CEO turnover is breaking records—fueled in part by the complexity of leading during relentless AI transformation.
The fallout? Less leadership, less mentorship, and more operational chaos—dragging down productivity, innovation, and company culture. The leaders left standing need a new roadmap to navigate this reality.
The New Talent Dilemma: Where Does Expertise End and AI Begin?
As AI becomes embedded in daily workflows, a new challenge emerges: determining where true capability ends and AI enhancement begins.
Used well, AI is a powerful ally—accelerating research, improving writing, streamlining analysis. But it also introduces hidden risks: unreliable results, dependence on skilled prompting, echo-chamber thinking—and perhaps most dangerously, a blurring of true talent.
Work that once took days now appears polished in minutes. The danger? AI can make average look exceptional. In this new era, separating genuine human capability from AI-enhanced performance is becoming harder than ever.
Case in Point: The Sam and Casey Conundrum
Consider two high-potential employees:
Sam uses AI fluently. His deliverables are clean, fast, and refined. But in meetings, he’s quiet. When asked questions in the moment, his insights lack depth. Is AI helping Sam shine—or is it concealing a skill gap?
Casey, by contrast, is dynamic in conversation, full of strategic insights, and excellent with clients. But her written reports lack polish, and she’s hesitant to adopt AI—missing out on efficiencies that could elevate her work.
These two employees are common in today’s workplace—and they reveal a key leadership dilemma: is AI revealing or obscuring your team members' strengths and weaknesses?
How Leaders Can Respond: Rethinking Talent Assessment
As AI reshapes the workplace, leaders are encountering new challenges: how to accurately assess, manage and support employees who use AI in vastly different ways. To lead well in an AI-enabled environment, managers must go beyond surface-level performance and uncover the human capability underneath. That means creating opportunities for deeper evaluation, coaching, and intentional development.
How to Lead a Team Member Like Sam:
Ask for early-stage drafts or thought outlines before AI refinement.
Increase one-on-one conversations to assess comprehension and independent thinking.
Encourage verbal contributions and live problem-solving in meetings.
How to Lead a Team Member Like Casey:
Offer training on how and when to use AI to enhance—not replace—strong ideas.
Review AI outputs together and guide her in refining content for clarity and impact.
Highlight her strategic thinking and interpersonal value, while helping her use AI selectively to boost efficiency.
Set the Standards for Ethical and Effective AI Use
Leaders must also create structures that support responsible AI integration:
Define clear expectations around when AI is appropriate and when human judgment is essential.
Establish performance standards that assess both process and output.
Build a culture of transparency where AI use is openly discussed—not hidden or over-relied upon.
Form innovation or assessment teams to monitor AI’s role and identify opportunities for deeper integration and guardrails.
AI as a Leadership Tool
AI is neither a replacement for human intelligence nor a definitive measure of success—it is an enhancement tool that, when used effectively, amplifies existing strengths while reducing potential weaknesses. In an AI-accelerated workplace, the challenge for managers is not just to assess what is produced, but to discern how it’s being produced—and what true capabilities lie beneath. Without visibility into how much AI is boosting outputs, leaders risk rewarding the wrong indicators of talent. Leaders who understand this dynamic will be better equipped to support their teams and ensure that AI integration leads to authentic growth and skill development, rather than superficial improvements in work quality.