The future of AI and the impact on demand for workspace

As artificial intelligence (AI) advances are increasingly integrated across a diverse range of industries, its potential to reshape employment patterns and real estate demand is gaining increasing attention. Recent advancements in AI, particularly generative AI, are driving a renewed focus on how technology will impact the future of work and space requirements. Stakeholders in the real estate sector need to understand whether AI-driven shifts in employment patterns will alter space requirements or whether AI-enhanced operations could help to optimise the services and environments provided.

However, the big challenge remains in assessing AI’s exact impact on real estate. The data is still emerging, and much of the analysis is more theoretical, making it difficult to predict precise outcomes. The three most frequently targeted outcomes of AI use cases are improved efficiency, enhanced creativity and productivity, and the optimisation of customer experiences. The key question is whether these outcomes will correlate with reduced demand for employment, as new technology enables employers to deliver more with fewer resources. Alternatively, we might see a net gain in employment (and demand for workplaces) as new roles are created and knowledge workers come together to drive business growth in new products and services, all powered by AI systems.

The speed of AI adoption, the potential for disruption, and ultimately, the aggregate impact of AI on labour demand, needs to be assessed on a sector-by-sector basis. The scale and pace of disruption, whether positive or negative, will vary according to the digital maturity of business processes and the range of manual, routine tasks currently performed by lower-skilled employees.

The flow of VC funding is a useful indicator of where will see the greatest potential for AI-driven transformation. 18% of VC funding in Europe in Q2 2024 was directed towards AI startups, with significant investment in the UK. In the first half of 2024 alone, the UK attracted $2.1 billion in VC funding for AI startups, underscoring its role as a leading hub for AI innovation in Europe.

While the flow of VC is a useful leading indicator, the scale of this disruption is likely to be driven by investments from big tech companies. Companies like Microsoft, Apple, Google, Nvidia, Amazon, and Meta have reached a combined market capitalisation of $12.7 trillion. More relevant, however, is their collective investment into AI. According to estimates, big tech companies are expected to invest over $1 trillion into AI over the next five years. Given increased regulatory scrutiny, large-scale mergers and acquisitions have slowed down, leading the giant tech companies to focus more on direct investments and strategic partnerships, to influence industries, and drive innovation without the complications of regulatory barriers.

Successful startups are set to see partnership and direct investment opportunities from big tech as a key accelerant of their business growth. However, it’s not just startups that benefit from these relationships. Established companies are also forming strategic partnerships with big tech to leverage AI tools.

Examining the specific sectors attracting these investments helps us to understand the potential impacts on real estate demand:

• Healthcare: Big tech’s influence in healthcare is growing rapidly. For example, Google has invested heavily in AI-driven healthcare solutions, including its partnership with Hyperfine for portable MRI machines and its in-house development of algorithms for breast and lung cancer detection. Nvidia is also advancing in healthcare IT with cloud-based tools like Clara and BioNeMo, and through a collaboration with Segmed and RadImageNet to generate and commercialise synthetic medical imaging data. Given the scale of AI investments such as these in healthcare by big tech companies, there is potential for increased real estate demand for medical facilities and research labs, as these technologies are integrated into healthcare infrastructure.
• Banking and Finance: The banking sector is leveraging AI for fraud detection, risk management, and customer service automation. Increased investment in fintech and AI-driven financial services could lead to greater demand for office spaces tailored to tech-driven financial operations, although this will be balanced against the widespread automation of more administrative roles and potential offshoring of lower margin activities.
• Renewables: AI's role in optimising energy production, storage, and distribution is driving investments in the renewables sector. This could result in the need for specialised facilities and offices for companies focused on sustainable energy solutions. Government policies promoting the adoption of renewable energy solutions could be a further catalyst for growth.
• Manufacturing: AI-driven automation and predictive maintenance are transforming manufacturing processes. Partnerships between big tech companies and established companies in this sector have already led to significant increases in operating efficiency. For instance, Microsoft are collaborating with Siemens to develop AI co-pilots for manufacturing, which help to streamline coding and debugging processes, leading to greater efficiency. Similarly, Nvidia’s partnership with BMW has led to a 30% improvement in manufacturing efficiency, showcasing how strategic collaborations can drive significant advancements in industrial operations. Investments in AI for manufacturing can lead to the development of smart factories, impacting demand for industrial real estate. Overall, it is possible to envisage a reduction in demand for manufacturing space due to AI technologies.

The growth of AI in the UK is also driven by several other key factors:

• Government policies and initiatives: The UK Government supports AI research and innovation through funding for research centres, tax incentives for tech companies, and public-private partnerships. These initiatives could create a conducive environment for AI startups to thrive, bolstering the UK's position as a leader in AI innovation.
• Technological advances: Continued advances in machine learning, natural language processing, and computer vision capabilities will drive widespread AI adoption across various sectors. Enterprises are increasingly using these technologies to enhance operations, improve decision-making, and create new products and services, accelerating AI's development and deployment in industries like healthcare, finance, retail, and manufacturing.
• Industry-specific solutions: AI is helping to address unique challenges and opportunities within different sectors, such as improving diagnostic accuracy and patient outcomes in healthcare, enhancing fraud detection and risk management in finance, optimising supply chains and predictive maintenance in manufacturing. As these solutions evolve and become more sophisticated, they have the potential to drive significant efficiency gains and innovation. The extent of future growth, however, will depend on the rate of AI adoption, regulatory frameworks, and the continued development of these technologies across various industries.
• Skilled talent: The availability of skilled talent is essential for AI growth. The UK, with its strong academic institutions and research centres, is a hub for AI talent. This concentration of expertise continues to attract startups and established companies, ensuring a steady supply of skilled workers to support the growing AI ecosystem.
• Tech ecosystems: A collaborative ecosystem where startups, corporations, research institutions, and government entities work together, is vital for AI growth. In Europe, tech ecosystems are flourishing, providing platforms for knowledge exchange, innovation, and commercialisation of AI technologies. These collaborations are particularly evident in AI clusters and innovation hubs, which are becoming focal points for AI development and deployment.

Comparing the stages of AI development in San Francisco and the UK offers valuable insights. San Francisco, with its established tech ecosystem, provides a glimpse into a potential future for the UK. Significant investments and technological advancements in AI R&D have positioned San Francisco at the forefront of AI innovation. These developments have already led to notable AI-driven office take-up in San Francisco, where AI-related companies have accounted for 25% of office leasing since 2023 (to H1 2024), totalling 2.3 million sq ft. The lessons from San Francisco's experience can help to predict the trajectory of AI development in the UK and suggests demand for office space to come from the sector. However, not all AI-driven growth will translate into similar real estate demand, as market dynamics differ significantly.

While the comparison of AI maturity between San Francisco and the UK paints a promising picture of potential growth and innovation, the actual impact on real estate demand is far from certain. The success of AI startups and their impact on office space demand depend on multiple factors, including market conditions, regulatory environments, and technological advancements. Moreover, while AI has the potential to create jobs, particularly in knowledge economies like London, it also poses significant risks for markets heavily reliant on call centres and customer service roles. A recent McKinsey report highlights that by 2030, up to 30% of current hours worked could be automated in both Europe and the US, driven by the rapid adoption of generative AI.

While there are positive signals that AI can drive job creation in sectors requiring innovation and creativity, potentially increasing demand for office space, it could also lead to a net reduction in employment in certain sectors. Industry specific impacts further illustrate this dynamic. In healthcare, AI can augment the work of doctors and nurses, leading to better patient outcomes and potentially more jobs, but it could also automate administrative tasks, reducing the need for support staff. In finance, AI’s role in risk management and customer service could create high-value jobs but also eliminate others. Similarly, manufacturing may see increased efficiency and output from AI-driven processes but a decrease in manual labour roles.

The ongoing trend towards hybrid and agile working models adds further complexity when assessing future demands for space, as companies continue to explore different hybrid and distributed working arrangements that may reduce their need for permanent office space, even when headcount is being increased. Additionally, the adoption of AI technologies might lead to a redistribution in the location of certain roles. Creative R&D roles and corporate functions could grow in core markets augmented by AI, while other roles might be nearshored or offshored to lower-cost locations, driven by process efficiencies and workflow automation.

As we look ahead, the relationship between AI and real estate demand is complex and multifaceted. The potential for AI to either increase or decrease office space requirements hinges on factors such as industry type, the maturity of AI technologies, and the strategic decisions of individual companies. Real estate stakeholders must, therefore, approach AI as both a potential driver of change and a source of uncertainty. Flexibility and adaptability in planning and strategy will be key to navigating this evolving landscape, with trends toward hybrid working models, nearshoring, and automation adding further layers of complexity, making it essential for companies to remain agile and responsive to shifting demands.