Water, too, is rising in strategic value: It’s essential for both chip manufacturing and data center cooling, yet aging infrastructure, community opposition, and climate-driven scarcity pose risks to project execution. These constraints should drive adoption of water-efficient innovations, but also reward developers with a proven record of community engagement.
Spending on data center cooling is poised to grow 18% annually, and projects to become a $16.9 billion market by 2028.9 Industrials selling efficient cooling solutions, reducing the electricity burden of AI infrastructure, are well-positioned.
Affordability
Data centers use vast amounts of power, straining the grid, and some consumers are already seeing this in their electricity bills.10 Data center servers now consume more than one-fifth of Ireland’s power, and as of October 2025, energy prices had spiked 26% in one year—the second-largest increase across EU countries.11
In Virginia, home to “Data Center Alley,” electricity prices are up 13% from last year and about 30% from 2021 levels. Some governments are taking steps to protect retail consumers, such as large load tariffs for hyperscalers. Still, these interventions may not cover the full costs of additional generation and transmission, and may struggle to reverse the public’s negative perception of data centers.12
Communities have been pushing back, citing concerns about higher electricity costs and increased water usage. This pressure led Google to cancel a project in Indianapolis in 2025, while Amazon pulled out of a proposed data center in Tucson. We expect to see AI-linked affordability debates in the 2026 midterm elections, and for leading tech companies to try to secure public trust through community engagement.
Corporate adoption and the impact on jobs
AI’s impact on the workforce seems both empowering and uncertain: It could revolutionize access to information, but may also disrupt career paths. We expect job rotations and enhancements over the near term, but long-term impacts on job creation will likely take decades to materialize. Still, we think investors should focus on emerging trends that could be leading indicators of change.
It’s early days, but we’re monitoring increasing unemployment in AI-influenced roles (e.g., software developers), particularly amongst younger workers. Workers under 30 in technology-related occupations have seen unemployment climb 3% just this year, strongly outpacing that of older industry colleagues as well as young peers in other occupations.13
We see opportunity for education technology platforms, as they are positioning themselves to personalize learning, improve outcomes and match candidates to jobs—a market forecasted to more than double by 2030 and reach $348 billion.14
The need for cybersecurity
AI is making an impact on cybersecurity—both good and bad. Generative AI tools are improving efficiency for bug fixes and threat detection, while AI agents and model governance create business segments for enterprises. While benefits abound, these tools also open up a new threat landscape. Anthropic recently reported the first instance of an AI-orchestrated cyber espionage campaign15. Moreover, the broader social impacts of deepfakes and misinformation are still being assessed. Threats to public trust and critical infrastructure only increase the value of transparency and protection. While the software sector faces uncertainty, cybersecurity spend should increase as AI penetration deepens.
Our conclusion
For AI investors, these findings present potential risks, but also open opportunities for first movers. Companies that address concerns head-on with responsible governance will likely win market share as public support for transparency, ethics and regulation gains momentum.16
Interest in AI and adoption of the technology have grown rapidly in three years, and we strongly expect that trend to continue. However, the AI infrastructure boom is a double-edged sword, driving economic growth while exposing potential bottlenecks— investment areas to watch. We think investors should focus on power and critical resources as strategic assets, while societal impacts are increasingly important to the growth of AI infrastructure.