The Resilient Spirit of Cities in the Generative AI Revolution

The Resilient Spirit of Cities in the Generative AI Revolution

In recent years, the narrative surrounding major urban centers like San Francisco, New York, and Seattle has been dominated by tales of a "brain drain," as remote work capabilities and high living costs have spurred a migration toward more affordable cities such as Miami, Phoenix, and Houston.  

This trend, documented by sources ranging from Axios to The Wall Street Journal, suggests a seismic shift in where and how America's workforce chooses to live and work. Yet, this narrative of decline misses a critical piece of the puzzle: the enduring strength of traditional innovation hubs in the face of the Generative AI revolution.  

The Resilience of Innovation Centers

Despite the exodus, SkyHive data reveals that cities like San Francisco, San Jose, Seattle, and New York continue to lead as America's premier innovation hubs, particularly in the burgeoning field of Generative AI. Job postings for roles in this cutting-edge technology sector remain concentrated in these areas, outpacing those in the rapidly growing cities of Miami, Phoenix, Houston, and even Washington, D.C.

This contrast raises a pivotal question: if the demand for Generative AI expertise is booming in traditional centers, how are shifts in population affecting the talent supply necessary to fuel this demand?

This graph shows online job postings for Generative AI jobs in 2023 across different cities. The size of the bubble is proportional to the demand for Generative AI skills, and the numbers show the ranking of the cities according to demand from employers in the top 50 largest cities.    

GenAI concentration


A Tale of a Growing Talent Gap

Our analysis indicates a widening gap between the demand for and the supply of Generative AI talent, most pronounced in the very cities leading the charge in innovation. This gap suggests a complex challenge: while these cities are generating new opportunities, attracting the necessary skilled workforce is becoming increasingly difficult.

This graph shows the increase in the demand-to-supply ratio (with demand being employers hiring, and supply being the talent) for each city. The national ratio is indexed to 100 in 2022, and all the other values are relative to that.  

Increase in GenAI demand


A closer examination of New York and the D.C. metro area, two regions with similar profiles, illustrates this dynamic vividly. Following the release of ChatGPT-4 in April 2023, New York's demand for Generative AI skills surged at a rate significantly outpacing that of D.C. This divergence underscores New York's robust foundation for embracing and driving technological advancements.


GenAI posting concentration

The supply side tells a different story. While the D.C. demand-to-supply ratio is 56 percent above the national average, New York faces a demand-to-supply ratio 55 percent above D.C., almost 2 1/2 times above the national average.

GenAI demand vs. supply

This imbalance points to the critical challenge of filling specialized roles, despite both cities having an ample supply of general roles like software developers. Roles such as machine-learning engineers and artificial-intelligence developers, crucial for the advancement of Generative AI, are proving particularly difficult to staff.

This next graph shows the demand for Generative AI roles vs. the total supply of roles. For example, in 2023 there was a demand of 950 machine-learning engineers with GenAI skills in New York City, and a supply of 1,417 machine-learning engineers (not specifically with GenAI skills).  

However, this graph does not show the overall demand (not specific to GenAI) for machine-learning engineers, which was around 2,764.

So even without taking into consideration the additional demand for machine-learning engineers with GenAI skills, the existing overall demand is above the supply. And if we look into the near future, the demand for machine-learning engineers will probably double or triple, which implies that there will be significant shortages.

While there is a limited talent pool for specialized occupations like AI developer and machine-learning engineer, the supply for more general technical roles such as software engineer and full-stack developer remains abundant.  

demand vs. supply by region


Strategies Forward: Shaping AI's Innovative Landscape

In the era of Generative AI, equipping America's workforce with the necessary skills is paramount. Here's a concise strategy:

Prioritize AI education: Expand AI and machine-learning education at all levels to build a future-ready talent pool.

Support continuous reskilling: Facilitate lifelong learning through online courses and industry partnerships to keep the workforce adaptable to AI advancements.

Ensure accessible learning: Make AI education available to all, targeting equitable access to bridge the digital divide.

Cultivate educational partnerships: Promote collaboration between academia and industry to align training with real-world needs.

By focusing on these educational strategies, we can prepare individuals for the future, fostering an innovative and resilient workforce in the face of rapid technological change.

Compiled by Bledi Taska, VP, Head of Analytics, at SkyHive, and Matej Mavricek, Senior Manager, Data & Product Analytics

About SkyHive  

SkyHive is a Certified B Corporation that uses ethical artificial intelligence to drive global reskilling initiatives, transition from jobs to skills, and create a more inclusive labor economy.

SkyHive was named one of the “Next Big Technologies Working for Social Good in 2023” by Fast Company, and a World Economic Forum Global Innovator.  

Leading enterprises and innovative government organizations use SkyHive’s cloud-based applications, Human Capital Operating System™, and SkyHive’s Quantum Labor Analysis® to power the future of work at its most granular level: skills.  

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