Adaptability is the New Job Security in 2026

Joe Depa, the global chief innovation officer at EY, predicts that adaptability will become the new job security in 2026. As artificial intelligence continues to transform jobs across industries, Depa argues that the ability to adapt and change is going to be the most important component for career longevity.

Depa oversees innovation, AI, and data strategies at the Big Four consulting firm. He shared three essential strategies for staying current amid rapid technological changes: continuous education, learning from mentors, and practical application. While acknowledging that professionals may not be able to outrun AI, Depa believes they can move with it by embracing adaptability as a core skill.

The concept of job security is undergoing a fundamental transformation. According to Joe Depa, traditional measures of stability are being replaced by a new metric: adaptability. In the context of rapid AI advancement, the ability to pivot and learn is becoming more valuable than static expertise.

Depa serves as the global chief innovation officer at EY, where he leads strategies for AI, data, and innovation. He emphasizes that training and upskilling will be the factors that differentiate both talent and organizations in the future workforce. The executive's prediction for 2026 suggests that professionals who resist change will find themselves at a significant disadvantage.

The core message is clear: while technical skills remain important, the capacity to continuously evolve those skills is paramount. As Depa states, "The ability to adapt and change is going to be the most important component." This shift requires a mindset that views learning not as a finite process completed in youth, but as a lifelong necessity.

The first pillar of Depa's strategy is relentless self-education. He advocates for both formal education and independent study to stay up-to-date. "You've got to always be learning and challenging yourself to learn every single day," Depa said.

Depa practices what he preaches. He returned to school to obtain a Master's in Analytics from Georgia Tech to deepen his understanding of software development, programming, and data science. His motivation was practical: he knew he would be managing data scientists and programmers and wanted to understand their perspective.

However, Depa notes that the landscape changes rapidly. Since earning his degree in 2020, he observes that software development has "completely changed." To keep pace, he listens to podcasts and reads articles about the latest news, particularly regarding AI.

Depa is not alone in this approach. Other leaders, such as Oliver Jenkyn of Visa, also dedicate regular time to learning. Jenkyn reportedly blocks off four hours a week to study complex topics like stablecoins or semiconductor history, demonstrating that high-level executives prioritize continuous education.

Beyond solo study, Depa stresses the importance of collaborative learning. He describes leaning on personal mentors as "critical" for professional growth. "All of us should have our own personal advisors — mentors around us that we can call," Depa said.

At EY, this philosophy is institutionalized through the global AI advisory council. This council comprises 20 top AI leaders who assist the firm in navigating the complex AI landscape. The group meets regularly to provide feedback on various plans and strategies.

For Depa, this council serves as a vital testing ground. "It's a really nice forum for me to test what's coming next," he explained. The diverse opinions help challenge his thinking and prevent blind spots. However, Depa clarifies that formal advisory boards are not the only way to gain perspective. He notes that having relationships with people you can check in with for different viewpoints is "increasingly important."

The final, and perhaps most crucial, component of Depa's strategy is practical application. He warns that education and mentorship are insufficient if not implemented. "That whole learning experience is going to really help create new brain dynamics for you to learn the next thing and the next thing," Depa said.

Practical application can take many forms, from "vibe coding" to creating actual applications. Depa encourages getting hands-on with tools, even if it leads to failure. He views failure as a natural part of experimenting with new ideas and technologies.

Getting comfortable with the discomfort of failure helps build a resilient mindset focused on continuous growth. "If you do it enough times, your brain will start to appreciate that process of formal learning, having a team of advisors, and then applying it and learning and growing," Depa said.

This emphasis on hands-on experimentation is shared by other technology leaders. John Stecher, Chief Technology Officer at Blackstone, also highlights the value of tactile engagement with technology. Stecher reserves time each weekend to experiment, such as using AI to write code for home automation. "It's tactile and tangible," Stecher noted, reinforcing the idea that doing is essential to learning.