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Area Development - Site Selection, Facility Planning and Workforce Development

Technology’s Influence on Workforce Development

How can a company develop an analytics-focused talent strategy to meet the needs of AI, specialized skillsets, automation, and beyond?

Workforce Q4 2023
The hype around artificial intelligence (AI) accelerated into high gear this year, catalyzed by the splash made by ChatGPT when it gained 100 million users within two months of launching. Since then, AI has become the latest focus for industry leaders looking to capitalize on the promise of productivity it will bring and by the cost savings that could materialize over time through these gains. But is AI really the magic bullet everyone seems to think it will be? First, it’s important to discern what exactly AI is, and what industry applications are possible through this evolving technology.

Innovation Drives Productivity
AI uses machine learning and deep learning algorithms that learn from experience to understand complex concepts and recognize patterns — which allows for the technology to interpret the nuances of language and independently make decisions. Generative AI, which is a subset of AI, uses advanced algorithms to create new outputs, and is used to generate new content including synthetic data, images, text, and music. AI has the potential to contribute $15.7 trillion to the global economy in 2030 and will drive productivity across a variety of industries in different ways.

For industry leaders looking to implement an AI strategy in their business, talent will be a critical factor in supporting those goals. Tech talent continues to be in ever-increasing demand as a host of new AI roles now need to be filled across sectors. AI has already begun to drive growth in new semiconductor development, as the race to meet the demand for AI chips has scaled and has driven insatiable demand for new data centers to meet the needs of increased computing power. Healthcare and life sciences are also going to be hugely impacted by the evolution of AI, with implications for increased speed of drug discovery and increased personalized medicine.

AI has the potential to contribute $15.7 trillion to the global economy in 2030 and will drive productivity across a variety of industries in different ways. Although AI is perceived publicly to be a threat to job security, the reality is that it’s expected to create more opportunities than it dismantles. As advancements lead to increased productivity and the automation of certain tasks, net demand among some occupations, with a greater emphasis on roles that prioritize interpersonal skills, is expected to grow. Since 2021, AI job postings have increased by 250 percent and are expected to continue to grow. With the continued shortage of skilled labor, the Bureau of Labor Statistics (BLS) projects that data science and information jobs will grow 35.2 percent by 2032, more than triple the average profession rate.

Geography of Talent
In past years, software and hardware companies were most interested in understanding where to best locate technology talent. Now, firms in all industries are seeking out this information. But not all industries are looking for the same type of AI talent.

What is required to develop an AI strategy for a semiconductor fabrication is different than what a pharmaceutical organization would require in scaling up a data science program. Even so, the concentration of companies developing new AI technologies are located in a handful of the most innovative markets across the globe.

AI talent in the U.S. is specifically concentrated in coastal markets, with the Bay Area, Seattle, and New York being the top three, followed by Boston, Los Angeles, and Austin. Proximity to major AI research institutions also plays a major role in the talent landscape, with the Bay Area, Boston, Pittsburgh, and Georgia leading in recent AI talent graduates. Although many urban cores saw sharp population declines during the pandemic, recent Census Bureau data paints an increasingly positive picture for large CBD markets, most of which have seen a slowing or reversal of out-migration. These gateway markets, like New York and Washington, D.C., have the largest number of AI workers, while Austin and San Francisco have seen the fastest growth.

The concentration of companies developing new AI technologies are located in a handful of the most innovative markets across the globe. As firms consider what should drive their real estate location strategy, factors such as government policies, proximity to major research institutions, educational incentives, partnerships, and investment all need to be considered. Federal funding shifts have put higher education institutions at the forefront of AI research, leading to increased innovation and more readily accessible talent. Funded by the National Science Foundation, seven AI institutes have been founded at six universities across the country including University of California, Santa Barbara; University of Minnesota; University at Buffalo; Columbia University; University of Maryland; and two AI institutes at the University of Illinois, Urbana-Champaign.

Strategic Considerations
Increasingly, we are working with clients to proactively incorporate talent data into their location decisions. It’s part of a continuing recognition from leading organizations that better synchronizing workforce and real estate decision-drivers can give them a real competitive advantage in a challenging environment. Some firms feel like AI-oriented talent is a blind spot, while others see it as an opportunity to future-proof their location strategy.

As clients work through the discovery process to clearly align their strategic and operational priorities with their talent and real estate needs, they start to gain clarity on how these factors will translate to their real estate selection priorities. Going through this process helps them understand their current and desired state in objective, quantifiable terms. We also see that while AI and digital talent has invigorated their interest in talent location, walking through a rigorous process helps inspire additional foundational questions about other talent pools, as well as the comprehensive set of factors that should ultimately inform what their future footprint and location strategy should look like.

Leading organizations [recognize] that better synchronizing workforce and real estate decision-drivers can give them a real competitive advantage in a challenging environment. When companies complete these location studies, the obvious question is, “What’s next?” But there is no one-size-fits-all solution. Some firms are choosing to concentrate investment in a multifunctional HQ in gateway markets, while others are reducing their footprint in these markets and instead targeting a combination of secondary or emerging markets for specific segments of their workforce. While an increase in remote working is affording companies access to more distributed talent pools, a majority of companies still plan for their teams to be centered around a physical, unifying location.

Data Will Enable Decision-Making
AI has emerged as a powerful force for productivity and cost savings, but it requires the right talent to drive its implementation effectively. By understanding the nuances of AI and its application across industries, leaders can proactively cultivate the necessary skillsets to stay ahead.

As AI continues to reshape industries, developers must have an analytics-focused location strategy that is closely tied to the organization’s talent strategy to stay ahead of the curve. AI has the potential to drive productivity and fuel growth across sectors, but acquiring the right talent is crucial. Developers must identify key locations for AI expertise by leveraging proximity to research institutions, incorporating talent data into real estate decisions, and striking a balance between remote work and physical collaboration. The time to act is now — shape your talent strategy, secure AI talent, and position your organization for success in the age of AI.

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