The productivity gains from individual AI use will become so significant that a wide performance gap will emerge in the workplace. The most talented employees will become hyper-productive and will refuse to work for organizations that don't support these new workflows, leading to a significant talent drain.
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.
While many believe AI will primarily help average performers become great, LinkedIn's experience shows the opposite. Their top talent were the first and most effective adopters of new AI tools, using them to become even more productive. This suggests AI may amplify existing talent disparities.
The career risk from AI is not being automated out of existence, but being outcompeted by peers who leverage AI as a tool. The future workforce will be divided by AI literacy, making the ability to use AI a critical competitive advantage.
AI won't eliminate sales roles but will automate the tasks of lazy, transactional reps, making them obsolete. Conversely, top performers who merge AI-powered insights with human empathy will become unstoppable, creating a more pronounced divide in sales team performance.
AI lowers the economic bar for building software, increasing the total market for development. Companies will need more high-leverage engineers to compete, creating a schism between those who adopt AI tools and those who fall behind and become obsolete.
AI coding assistants won't make fundamental skills obsolete. Instead, they act as a force multiplier that separates engineers. Great engineers use AI to become exceptional by augmenting their deep understanding, while mediocre engineers who rely on it blindly will fall further behind.
AI is expected to disproportionately impact white-collar professions by creating a skills divide. The top 25% of workers will leverage AI to become superhumanly productive, while the median worker will struggle to compete, effectively bifurcating the workforce.
Experience alone no longer determines engineering productivity. An engineer's value is now a function of their experience plus their fluency with AI tools. Experienced coders who haven't adapted are now less valuable than AI-native recent graduates, who are in high demand.
AI disproportionately benefits top performers, who use it to amplify their output significantly. This creates a widening skills and productivity gap, leading to workplace tension as "A-players" can increasingly perform tasks previously done by their less-motivated colleagues, which could cause resentment and organizational challenges.
AI will handle most routine tasks, reducing the number of average 'doers'. Those remaining will be either the absolute best in their craft or individuals leveraging AI for superhuman productivity. Everyone else must shift to 'director' roles, focusing on strategy, orchestration, and interpreting AI output.