The Dilemma Behind Companies’ Dual Anxieties

Amid rapid AI iteration, corporate anxiety is no longer a single, narrow confusion about how to use a technology. Instead, it is the result of two layers of uncertainty—one from the broader macro environment and the other from on-the-ground implementation—stacking on top of each other. This has become a widely felt pain point across industry today. On one hand, AI evolves so quickly that what is cutting-edge today may be outdated tomorrow. On the other hand, once AI is deployed, how can its value be demonstrated so that the business realizes tangible gains? These two questions together form the anxiety weighing on today’s enterprise users.

Chen Xudong attributes companies’ core anxieties to two main dimensions. The first is the systemic uncertainty brought by shifts in the macro environment: sharp swings in input prices such as oil and precious metals, frequent changes in geopolitics and regulatory rules, and the ongoing pressure to raise productivity—all of which make it difficult for CEOs to make steady strategic judgments. The second is anxiety about getting AI applications into real-world deployment. Although global spending in AI this year is expected to reach US$2.5 trillion and AI’s commercial value is widely viewed positively, most companies have yet to see clear results from their AI initiatives. The “afraid of falling behind, yet afraid the investment will be wasted” mindset has left many firms hesitant in their AI planning.