A Nose for Elevating New Technology Leaders
Evaluating Talent for Next Level Leaders in the Age of AI
This paper addresses one of the most critical challenges facing technology organizations today: identifying and developing the next generation of leaders who can navigate an increasingly AI-driven landscape. Drawing from extensive experience across diverse domains—including defense, enterprise technology, and high-growth startups—this comprehensive guide moves beyond traditional promotion practices that often fail to distinguish between high-performing individual contributors and those with genuine leadership potential.
The paper introduces a systematic framework centered on five key leadership characteristics—commitment, curiosity, outcome orientation, people leadership, and technology leadership—along with practical "sniff tests" that allow managers to evaluate these traits in real-world scenarios. Rather than relying solely on AI-generated performance metrics or intuition, the authors provide concrete examples and actionable assessment tools that help organizations make confident leadership decisions. The guide also thoughtfully examines how AI tools can augment but not replace human judgment in the critical process of identifying and nurturing technology leaders.
This resource fills a significant gap in leadership development literature by focusing specifically on the unique challenges of technology leadership transitions and providing immediately applicable evaluation methods that can prevent costly promotion mistakes while building stronger, more effective teams.
What's inside
- Predictive Framework — Systematic approach using five core characteristics to identify leadership potential before promotion decisions.
- Practical Assessment — Real-world "sniff tests" that evaluate leadership readiness through actual work experiences.
- Risk Mitigation — Methods to distinguish between high performers and genuine leadership candidates.
- AI-Informed Balance — Strategic guidance on using AI tools while maintaining human judgment in leadership decisions.
- Pages
- 28
- Publication Date
- September 16, 2025
- Topics
- AI · Leadership
- Formats
- epub · pdf
- License
- Creative Commons BY-NC-SA
