A thriving innovation economy cannot be sustained by only creating jobs for the highly educated. The most resilient strategies deliberately select tech sectors like cybersecurity and drone maintenance which offer a wide range of accessible jobs, creating pathways for the existing blue-collar workforce to upskill and participate.
Bringing manufacturing back to the US won't mean a return of old assembly line jobs. The real opportunity is to leapfrog to automated factories that produce sophisticated, tech-infused products. This creates a new class of higher-skill, higher-pay "blue collar plus" jobs focused on building and maintaining these advanced manufacturing systems.
The democratization of technology via AI shifts the entrepreneurial goalpost. Instead of focusing on creating a handful of billion-dollar "unicorns," the more impactful ambition is to empower millions of people to each build a million-dollar "donkey corn" business, truly broadening economic opportunity.
An entry-level, non-tech role within a tech-enabled company can be a powerful entry point. By excelling in the role and clearly communicating long-term career goals, individuals can gain domain expertise and access internal opportunities that bypass traditional requirements like a university degree.
The narrative of AI destroying jobs misses a key point: AI allows companies to 'hire software for a dollar' for tasks that were never economical to assign to humans. This will unlock new services and expand the economy, creating demand in areas that previously didn't exist.
With leaders like Marc Benioff admitting AI will reduce headcount, companies risk a culture of fear. The recommended strategy is for every CEO to publish an "AI Forward" memo that transparently addresses the future of work and outlines concrete commitments to reskilling the existing workforce.
Instead of fearing job loss, focus on skills in industries with elastic demand. When AI makes workers 10x more productive in these fields (e.g., software), the market will demand 100x more output, increasing the need for skilled humans who can leverage AI.
In niche sectors like aerospace engineering, the pool of senior, diverse talent is limited. A pragmatic strategy is to hire the best available senior specialists while intensely focusing diversity efforts on junior roles and internships. This builds a more diverse next generation of leaders from the ground up.
While AI-driven efficiency is an obvious first step, it often results in workforce reduction if company growth is flat. True differentiation and sustainable advantage come from using AI for innovation—creating new products, markets, and business models to fuel growth.
Instead of creating a tech sector from scratch, the most effective path is to identify and invest in tech niches adjacent to a city's existing industries (e.g., Energy Tech for an oil town). This leverages existing talent, infrastructure, and supply chains, making the transition more natural and sustainable.
Most AI applications are designed to make white-collar work more productive or redundant (e.g., data collation). However, the most pressing labor shortages in advanced economies like the U.S. are in blue-collar fields like welding and electrical work, where current AI has little impact and is not being focused.