Historically, every major technological leap has enabled more, not less: more experimentation, more products, more services, and more jobs. When electricity, the steam engine, or the internet were adopted, the boldest companies didn’t shrink their ambitions. They expanded aggressively, took risks, and created entirely new markets. So why is AI being treated differently?
One reason seems to be risk aversion. Many companies, especially large and established ones, are focused on short-term gains, shareholder expectations, and operational efficiency. They see AI as a way to "optimize" — to cut staff, automate workflows, and increase margins — instead of using it as a foundation for new lines of business or transformative innovation.
But this is a shallow use of a deep technology.
Imagine instead a company using AI not to downsize teams, but to multiply their output. They could afford to hire more people, putting more creative minds to work, while AI acts as an accelerator — automating repetitive tasks, generating prototypes, coordinating agents, and simulating large-scale systems. This opens the door to projects that previously seemed too complex or costly: personalized education platforms, open-ended scientific research, AI-driven drug discovery, sustainable agriculture systems, or highly efficient digital public services.
Yes, these kinds of projects are risky. But they also offer disproportionate rewards, both financially and socially. Companies that bet on bold, transformative uses of AI — instead of simply optimizing existing processes — are the ones that will shape the future, just as Google did with search or SpaceX with aerospace.
Ironically, AI can also reduce the cost of failure. It allows for faster prototyping, quicker insights, and tighter feedback loops. This makes bold experimentation more feasible than ever.
The real obstacle is not the technology, but a lack of vision and courage. Playing it safe with AI might improve short-term profits, but it limits long-term growth and impact. Companies that adopt a more ambitious mindset, and treat AI as a collaborator rather than a replacement, have the chance to redefine what is possible.
So the question shouldn’t be, "How many people can we replace with AI?" It should be, "What are the things we’ve never dared to try that AI now makes achievable?"