Humans vs. AI: The Emotional Factor
In the fast-paced world of cybersecurity, particularly within identity management, the stakes are high. We help large organizations automate access to applications and manage users’ digital identities throughout their relationship with the organization. While our work revolves around software, I often liken it to a physical machine—one with the potential for significant impact. Just as a mechanical failure can be catastrophic, a simple true/false logic error in our systems could disable doctor accounts, preventing critical patient care, or lock bank tellers out of systems, disrupting customer service. Thankfully, well-defined processes help us mitigate these risks.
Over the past decade, I have transitioned from a junior engineer with hands on the keyboard to an architect and now to leading a team of engineers and architects. Through my exploration with mindtrack.ai and my growing interest in AI, I’ve come to realize how the emotional component inherent in humans will significantly accelerate the adoption of AI agents and whatever comes next.
Yesterday, we executed a large deployment for a major banking client. While technical issues could have arisen, the real challenge leading up to the deployment wasn’t technical at all—it was managing the emotional stress within my team. The solutions we implemented were ones I had personally deployed five or six times before. But for my team, this was unfamiliar territory. Their apprehension, fear, and stress were palpable.
In my daily work, I split my time nearly 50/50 between managing people and working with AI. One of AI’s most powerful traits is its complete lack of emotion. Sure, you can engineer prompts to mimic emotion, but at its core, AI doesn’t care—it simply operates within its guidelines. Humans, on the other hand, bring immense complexity. There are personal stresses—home repairs, caring for a sick parent, job security fears—combined with workplace dynamics, opinions on fairness, and how projects have been handled. Even the tone of client calls can add to the noise. None of this has anything to do with the work or the automation we’re delivering. Yet, it profoundly impacts performance.
Like AI, the systems we implement are emotionless—they execute tasks exactly as programmed. Reflecting on this recent deployment, I would rate the technical execution a C+. I knew the quality could have been better, but I had to balance quality with the politics and emotions at play. However, as my team celebrated and the client sent a grateful thank-you email, I gave myself an A+ for emotional leadership. That recognition felt rewarding.
Reflecting on this, I see how businesses will naturally gravitate towards AI-driven solutions. AI’s emotionless nature allows for more effective delivery, free from the distractions that can hinder human performance. Beyond its exponential speed in delivering code, AI’s lack of emotional baggage is a distinct advantage.
As I look toward the future, I believe our work will become increasingly AI-driven. The challenge for humans will be learning how to coexist with and harness these emotionless machines—leveraging their efficiency while navigating the emotional complexities that come with being human.
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