As AI handles more routine tasks, uniquely human skills like creativity, strategic thinking, clear communication, and collaboration are becoming table stakes. These former "soft skills" are now mandatory for career growth and resilience.

As AI handles technical tasks, uniquely human skills like curiosity, empathy, and judgment become paramount. Leaders must adapt their hiring processes to screen for these non-replicable soft skills, which are becoming more valuable than traditional marketing competencies.

As AI advances, the half-life of technical skills shrinks to 2.5-5 years. Leaders must cultivate appreciating 'soft' skills like judgment and adaptability by embedding them into performance metrics (KPIs, OKRs), rather than just verbally encouraging them. Employees won't prioritize what they aren't evaluated on.

As AI handles technical tasks, the value of hard skills diminishes. The most crucial employee traits become "human" qualities: buying into the company vision, emotional intelligence, and self-awareness. These are the new competitive advantages in talent acquisition.

A top VC's most important interview question is now "How have you used AI in your daily life this week?" The key is identifying individuals who are running towards the new technology and embracing change. This mindset is uncorrelated with age or seniority, making it the most critical hiring signal.

For roles leveraging new technologies like AI, where tools are nascent and constantly changing, competency is a fleeting metric. Instead, hire for curiosity. A curious mind will adapt, learn, and master new tools as they emerge, making them a more valuable long-term asset.

Skills like curiosity, courage, creativity, compassion, and communication—often dismissed as "soft"—are becoming your primary competitive advantage. As AI handles more technical and routine work, these uniquely human capabilities are essential for innovation and long-term career survival.

Sendbird updated its job descriptions for 'AI-first' roles to de-emphasize years of experience. Instead, they screen for high curiosity, agency, and energy, believing these traits are better predictors of success for employees who must constantly learn and build with new tools.

Since AI tools are new and their use is often restricted at legacy companies, prior experience is a poor predictor of success. Artemis prioritizes a candidate's eagerness to learn and operate at the cutting edge, teaching them their intensive, multi-instance workflows upon joining.