The best barometer for AI's enterprise value is not replacing the bottom 5% of workers. A better goal is empowering most employees to become 10x more productive. This reframes the AI conversation from a cost-cutting tool to a massive value-creation engine through human-AI partnership.

AI boosts productivity, but competitors have the same tools. Instead of cutting staff, companies must leverage AI's efficiency to expand output tenfold to survive. Businesses that shrink their teams will be out-produced and ultimately lose market share to those that grow.

The primary business use of AI is not to cut costs by replacing workers, but to expand revenue by enabling the creation of more products and services. This productivity boom drives demand for more employees, particularly engineers, to capitalize on new opportunities.

Don't view AI through a cost-cutting lens. If AI makes a single software developer 10x more productive—generating $5M in value instead of $500k—the rational business decision is to hire more developers to scale that value creation, not fewer.

Contrary to the popular job-loss narrative, companies heavily using AI are growing faster and hiring more people to manage increased demand. Studies from Wharton and hiring data from platforms like Indeed show that AI tools create leverage, enabling new businesses and expanding existing ones, thus increasing the overall need for human workers in new or adapted roles.

Contrary to fears of mass job replacement, businesses are primarily leveraging AI as a growth engine. Instead of simply cutting operational costs, firms are using AI-driven productivity gains to take on more clients, increase their scope of work, and capture greater market share, reframing the technology's impact as expansionary.

Contrary to popular belief, AI adoption drives business growth so rapidly that companies often need to hire more staff to manage the increased demand. A Wharton study found the vast majority of enterprise leaders using AI planned to increase their human workforce, shifting the focus from job replacement to job transformation.

A common but flawed reaction to AI-driven efficiency is to ask 'how many fewer people do we need?' The more powerful question is 'how much more can we build now?' AI unlocks the potential for teams to tackle previously impossible goals, making it a time to accelerate.

The idea that AI will enable billion-dollar companies with tiny teams is a myth. Increased productivity from AI raises the competitive bar and opens up more opportunities, compelling ambitious companies to hire more people to build more product and win.