According to Inc., Amazon plans to cut 14,000 jobs while investing more in AI, and Chegg is laying off 45 percent of its workforce as both companies confront what they call “the new realities of AI.” At the recent Masters of Scale Summit in San Francisco, Box CEO Aaron Levie, LinkedIn’s chief economic opportunity officer Aneesh Raman, and Clara Shih, Meta’s head of business AI, discussed which skills will be most valuable in this changing landscape. Shih argued that entrepreneurship—defined as “pursuit of opportunity without regard to resource constraint”—will be crucial, while Raman emphasized curiosity among the five critical soft skills: curiosity, compassion, creativity, courage, and communication. Levie offered an optimistic long-term view, suggesting AI will ultimately lead to more hiring by increasing worker productivity and leveling the playing field for smaller businesses.
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Why Soft Skills Are Becoming the New Hard Skills
The emphasis on entrepreneurial thinking and adaptability represents a fundamental shift in what constitutes valuable workplace skills. For decades, technical proficiency and domain expertise were the primary drivers of career advancement. However, as artificial intelligence systems become increasingly capable of performing specialized tasks, the human advantage shifts toward capabilities that machines cannot easily replicate. The ability to identify opportunities, pivot quickly, and work effectively with AI systems—rather than simply operating them—becomes the differentiator. This isn’t about replacing technical skills entirely, but rather recognizing that technical skills alone are no longer sufficient for long-term career resilience.
What the Entrepreneurial Mindset Actually Means
When Clara Shih describes entrepreneurship as “pursuit of opportunity without regard to resource constraint,” she’s identifying a crucial adaptation strategy for the AI era. This mindset isn’t about starting companies—it’s about operating with resourcefulness and opportunity-seeking behavior within any organizational context. In practical terms, this means employees who can identify how AI tools can create new value propositions, who understand how to leverage limited resources through intelligent automation, and who maintain what LinkedIn’s Raman calls “learn how to learn quick” capabilities. The most successful workers will be those who treat their roles as dynamic opportunities rather than fixed job descriptions.
The Productivity Paradox and Employment Outlook
Aaron Levie’s optimistic employment outlook deserves careful examination. Historically, major technological shifts have indeed created more jobs than they destroyed, but the transition periods can be brutal for displaced workers. The comparison to advertising agencies adopting Photoshop is instructive but potentially misleading—AI’s impact is broader and faster than previous technological revolutions. While Amazon’s current layoffs might be temporary, the structural changes AI introduces could permanently alter certain career paths. The real challenge isn’t whether jobs will exist, but whether current workers can adapt quickly enough to fill the new roles that emerge.
Practical Preparation for the Coming Changes
Levie’s observation that “if you drop AI into today’s business process, it’s going to actually do very little” reveals a crucial insight: successful AI integration requires rethinking workflows, not just adding technology. Workers and businesses have a narrow window to develop the complementary skills that will make them valuable in AI-augmented environments. This means focusing on judgment, ethical decision-making, creative problem-solving, and the interpersonal skills that Raman highlighted. The most prepared organizations will be those that invest in continuous learning cultures and encourage experimentation with AI tools before competitive pressures force adaptation.
How AI Levels the Playing Field
The potential for smaller businesses to compete with established players represents one of AI’s most transformative aspects. As Levie suggests, companies that previously couldn’t afford expert legal counsel, sophisticated marketing, or advanced product development may gain access to AI-powered equivalents. This doesn’t eliminate the advantages of scale entirely, but it does reduce certain structural barriers. The implication for workers is that career opportunities may become more distributed across organizations of all sizes, rather than concentrated in large corporations. For entrepreneurs and employees alike, understanding how to leverage AI to overcome resource constraints becomes a critical competitive advantage.
