Again, maybe counterintuitive, but in the majority of conversations I have with CIOs, CTOs, and CEOs in large enterprises, they are either growing due to AI (in new job functions like FDEs, engineering, etc.) or at a minimum reinvesting efficiency savings back into the business in new areas (sales, marketing, etc.). David Solomon, CEO of Goldman Sachs, articulated this perfectly in a NYTimes OpEd last week. The AI boom is both creating all new jobs in the build out of AI systems and the implementation across sectors, but also freeing up dollars to invest in areas that have been underfunded or have more demand now because of AI. Most businesses have been constrained by how much software they can produce at a given cost, how many sales reps they can hire, how many marketing campaigns they can run, how they can do outbound customer success motions with enough tailoring, how they can find more risk in their business and prevent it, and 100s of other things. When AI makes it possible to do more of this, investment goes back into the business. The companies that better serve their customers win over the long run, and those that just try and find savings end up doing worse.
这点再次说明，也许有些反直觉，但在我与大型企业 CIO、CTO 和 CEO 的大多数交流中，他们要么正因为 AI 而扩张（新增了像 FDE、engineering 等新的岗位职能），要么至少会把效率提升节省下来的资金重新投入业务中的新领域（如 sales、marketing 等）。Goldman Sachs 的 CEO David Solomon 上周在一篇 NYTimes OpEd 中对此做了非常到位的阐述。AI boom 既在 AI 系统建设以及跨行业落地实施过程中创造出全新的工作岗位，也释放出更多资金，用于投资那些过去资金不足、或因 AI 而出现更多需求的领域。大多数企业一直受限于：在既定成本下他们能开发多少 software（软件）、能雇用多少 sales reps、能开展多少 marketing campaigns、能以足够个性化的方式推进 outbound customer success、能在业务中发现并防范多少更多风险，以及其他数百项类似事项。当 AI 让企业有可能在这些方面做得更多时，投资就会重新回流到业务中。从长期来看，那些更好服务客户的公司会胜出，而那些只想着节省成本的公司最终往往会表现更差。